Forestry, Faculty of
DSpace
UBCV
van der Zwan, Timo William
Doctor of Philosophy - PhD
University of British Columbia
Enzyme-mediated hydrolysis of lignocellulosic materials for their conversion into bioproducts would benefit significantly if high solids concentrations (low water-to-biomass ratios) could be processed effectively. However, the fibrous nature of lignocellulosic biomass makes effective reaction mixing difficult, resulting in mass transfer limitations that reduce process yields. Overcoming these rheological challenges will require a better understanding of the substrate properties that influence slurry rheology, and in particular, how the action of carbohydrate-active enzymes can better facilitate slurry viscosity reduction, or ‘enzymatic liquefaction’. To this end, the work described in this thesis assessed: the underlying causes of the rheological challenge of high-solids bioconversion; the possible mechanisms of enzymatic liquefaction; how liquefaction is influenced by the nature of the substrate; and the roles the various enzymes play in liquefaction. It was apparent that the relationship between substrate properties, slurry rheology and high-solids hydrolysis kinetics is complex and multifaceted. Substrate–water interactions were shown to be a key determinant that influenced the mass transfer boundary and the scaling of yield stress with solids loading. The yield stress profiles of the various pretreated substrates varied extensively, indicating that ‘high solids’ is a relative, substrate-dependent quality. Substrate rheological characteristics, especially slurry yield stress, were shown to be directly linked to liquefaction efficiency and to reductions in hydrolysis yield with increasing solids loading. It appeared that enzyme-mediated liquefaction of biomass was achieved through a combination of material dilution, particle fragmentation and alteration of interparticle interactions. Cellobiohydrolases and endoglucanases were shown to be the key enzymes involved in these mechanisms. However, the effectiveness of the various enzymes was strongly influenced by the substrate’s physicochemical properties and concentration. Notably, an enzyme’s low-solids slurry viscosity-reducing capacity did not necessarily reflect its capacity to catalyze liquefaction at high solids loadings. Furthermore, reaction efficiencies tested at low solids loadings did not reliably predict efficiency at high solids due to substrate-specific rheological differences. In summary, this work provided rheological and enzymological insights into the highly disparate reaction kinetics and rheological challenge prevailing at commercially relevant substrate concentrations.
THE INFLUENCE OF ENZYMATIC LIQUEFACTION AND SLURRY RHEOLOGY ON HIGH-SOLIDS CELLULOSE HYDROLYSIS by TIMO WILLIAM VAN DER ZWAN BSc, Microbiology and Immunology, The University of British Columbia, 2013 A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2018 © Timo William van der Zwan, 2018 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: The Influence of Enzymatic Liquefaction and Slurry Rheology on High-Solids Cellulose Hydrolysis submitted by Timo William van der Zwan in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Forestry Examining Committee: Dr. Jack Saddler, Forestry Supervisor Dr. Scott Renneckar, Forestry Supervisory Committee Member Dr. Steven Hallam, Microbiology and Immunology University Examiner Dr. Vikramaditya Yadav, Chemical and Biological Engineering University Examiner Additional Supervisory Committee Members: Dr. Paul McFarlane, Forestry Supervisory Committee Member Dr. Jinguang Hu, Bioproducts and Biosystems, Aalto University Supervisory Committee Member iii Abstract Enzyme-mediated hydrolysis of lignocellulosic materials for their conversion into bioproducts would benefit significantly if high solids concentrations (low water-to-biomass ratios) could be processed effectively. However, the fibrous nature of lignocellulosic biomass makes effective reaction mixing difficult, resulting in mass transfer limitations that reduce process yields. Overcoming these rheological challenges will require a better understanding of the substrate properties that influence slurry rheology, and in particular, how the action of carbohydrate-active enzymes can better facilitate slurry viscosity reduction, or ‘enzymatic liquefaction’. To this end, the work described in this thesis assessed: the underlying causes of the rheological challenge of high-solids bioconversion; the possible mechanisms of enzymatic liquefaction; how liquefaction is influenced by the nature of the substrate; and the roles the various enzymes play in liquefaction. It was apparent that the relationship between substrate properties, slurry rheology and high-solids hydrolysis kinetics is complex and multifaceted. Substrate–water interactions were shown to be a key determinant that influenced the mass transfer boundary and the scaling of yield stress with solids loading. The yield stress profiles of the various pretreated substrates varied extensively, indicating that ‘high solids’ is a relative, substrate-dependent quality. Substrate rheological characteristics, especially slurry yield stress, were shown to be directly linked to liquefaction efficiency and to reductions in hydrolysis yield with increasing solids loading. It appeared that enzyme-mediated liquefaction of biomass was achieved through a combination of material dilution, particle fragmentation and alteration of interparticle interactions. Cellobiohydrolases and endoglucanases were shown to be the key enzymes involved in these mechanisms. However, the effectiveness of the various enzymes was strongly influenced by the substrate’s physicochemical properties and concentration. Notably, an enzyme’s low-solids slurry viscosity-reducing capacity did not necessarily reflect its capacity to catalyze liquefaction at high solids loadings. Furthermore, reaction efficiencies tested at low solids loadings did not reliably predict efficiency at high solids due to substrate-specific rheological differences. In summary, this work provided rheological and enzymological insights into the highly disparate reaction kinetics and rheological challenge prevailing at commercially relevant substrate concentrations. iv Lay Summary Many of the products modern society cannot live without, such as plastics and fuels, are currently unsustainably produced from fossil fuels. These products can instead be produced renewably and sustainably from plant biomass through deconstruction and conversion with microorganisms and their enzymes, but commercialization of these ‘biorefinery’ technologies is challenged by the complex structure of biomass and the resulting high process costs. This thesis investigated the main processing challenges preventing us from achieving a sustainable biomass-based economy and assessed how these challenges might be overcome. It was clear that the efficiency of enzymatic deconstruction of biomass for its conversion to bioproducts is highly dependent on the nature of the biomass substrate, the enzymes used, and the process conditions. Particularly, this pioneering study showed that improvement of enzyme efficiency at high substrate concentrations needs to be pursued if cost-effective biorefineries are to be established. v Preface All research work reported in this thesis was planned, conducted, and analyzed by Timo William van der Zwan in the Forest Products Biotechnology/Bioenergy laboratory at the University of British Columbia, Vancouver campus, under supervision of Professor John (Jack) N. Saddler. A version of Section 5 was published as Mechanistic insights into the liquefaction stage of enzyme-mediated biomass deconstruction, van der Zwan, T, Hu, J, Saddler, J, 2017, in Biotechnology and Bioengineering 114 (11): 2489-2496. I planned and conducted the experiments and drafted the manuscript. Jinguang Hu and Jack Saddler contributed to the planning, data interpretation and writing of the manuscript. Part of Section 4 is included in a manuscript that will be submitted for publication, titled Laccase-catalyzed grafting of phenolic compounds onto lignin reveals influence of unproductive binding, water interactions and rheology on cellulase interactions with lignocellulose. I planned and conducted the experiments. Richard Chandra helped with experimental planning and drafting of the manuscript. Jack Saddler helped with data interpretation and writing of the manuscript. Section 6 is a version of a manuscript that will be submitted for publication, titled The roles of cellobiohydrolase, endoglucanase and xylanase in enzyme-mediated liquefaction are dependent on the nature and solids loading of the biomass substrate. I planned and conducted the experiments and drafted the manuscript. Jinguang Hu and Alex Sigg helped with experimental planning, protein purification, and in-rheometer reactions. Richard Chandra helped with preparation of substrates and drafting of the manuscript. Jack Saddler helped with data interpretation and writing of the manuscript. Related research carried out during the degree but not included in the thesis was published as The potential of endoglucanases to rapidly and specifically enhance the rheological properties of micro/nanofibrillated cellulose, Gourlay, K, van der Zwan, T, Shourav, M, Saddler, J, 2018, in Cellulose 25: 977–986. Keith Gourlay, Musavvir Shourav and I conducted the experiments and drafted the manuscript. Jack Saddler helped plan the experiments and contributed to writing the manuscript. vi Table of Contents Abstract .......................................................................................................................................... iii Lay Summary .................................................................................................................................. iv Preface ............................................................................................................................................. v Table of Contents ........................................................................................................................... vi List of Tables ................................................................................................................................... x List of Figures ................................................................................................................................. xi List of Abbreviations, Acronyms and Symbols ............................................................................. xix Acknowledgements...................................................................................................................... xxii 1 Introduction ............................................................................................................................ 1 1.1 The recalcitrant structure of lignocellulosic biomass .............................................................. 3 1.1.1 Cellulose ................................................................................................................................ 4 1.1.2 Hemicellulose ....................................................................................................................... 5 1.1.3 Lignin .................................................................................................................................... 5 1.1.4 Ultrastructure ....................................................................................................................... 6 1.1.5 Influence of pretreatment on substrate structure ............................................................... 8 1.2 Importance of biomass slurry mixing for enzymatically catalyzed reactions ...................... 10 1.3 Rheology of lignocellulosic biomass slurries.......................................................................... 11 1.4 Mixing methods for high-solids biomass deconstruction ..................................................... 17 1.5 Two-stage hydrolysis ............................................................................................................... 18 1.6 Liquefaction of biomass slurries and the potential mechanisms involved ........................... 20 1.7 Lignocellulose deconstruction mechanisms and the enzymes involved .............................. 24 1.7.1 Cellobiohydrolases ............................................................................................................. 26 1.7.2 Endoglucanases .................................................................................................................. 27 1.7.3 Beta-glucosidases ................................................................................................................ 27 1.7.4 Hemicellulases .................................................................................................................... 27 1.7.5 Lytic polysaccharide monooxygenases ............................................................................. 28 1.8 Influence of cellulolytic enzymes on lignocellulosic substrate properties............................ 28 1.8.2 Endoglucanase .................................................................................................................... 30 vii 1.8.4 Beta-glucosidase ................................................................................................................. 31 1.8.5 Hemicellulase ..................................................................................................................... 31 1.8.6 Lytic polysaccharide monooxygenase ............................................................................... 32 1.9 Thesis overview and research approach ................................................................................. 33 2 Materials and Methods .......................................................................................................... 37 2.1 Preparation of lignocellulosic substrates ................................................................................ 37 2.2 Particle dimensions ................................................................................................................. 39 2.3 Crystallinity index ................................................................................................................... 39 2.4 Cellulose accessibility .............................................................................................................. 40 2.5 Substrate and pretreatment liquor composition .................................................................... 40 2.6 Fiber fractionation ................................................................................................................... 41 2.7 Conductometric titration ........................................................................................................ 41 2.8 Contact angle ........................................................................................................................... 42 2.9 Light and scanning electron microscopy ............................................................................... 42 2.10 X-ray photoelectron spectroscopy .......................................................................................... 42 2.11 Isothermal thermogravimetric analysis .................................................................................. 43 2.12 Water retention capacity ......................................................................................................... 43 2.13 Unidirectional shear yield stress ............................................................................................. 43 2.14 Oscillatory rheometry.............................................................................................................. 44 2.15 Enzymes and their purification .............................................................................................. 45 2.16 Protein concentration.............................................................................................................. 46 2.17 Enzyme activity assays ............................................................................................................. 47 2.18 SDS-PAGE ............................................................................................................................... 47 2.19 Isoelectric focusing .................................................................................................................. 48 2.20 Enzymatic hydrolysis............................................................................................................... 48 2.21 Statistical analysis .................................................................................................................... 49 Results and Discussion .................................................................................................................. 50 3 Assessment of the rheological challenge of high-solids enzyme-mediated hydrolysis and the influence of substrate characteristics ..................................................................... 50 3.1 Background......................................................................................................................... 50 viii 3.2 Preparation and characterization of substrates ................................................................ 53 3.3 The importance of enzymatic liquefaction in overcoming mass transfer limitations ... 54 3.4 The influence of mass transfer on enzymatic hydrolysis ................................................. 57 3.5 Substrate properties affecting biomass slurry rheology ................................................... 63 3.6 Examination of the influence of particle length on slurry rheology ............................... 69 3.7 Conclusions ........................................................................................................................ 74 4 The influence of substrate composition on slurry rheology and enzymatic liquefaction .................................................................................................................................................. 75 4.1 Background......................................................................................................................... 75 4.2 Preparation and characterization of aspen poplar substrates .......................................... 76 4.3 Modification of lignin through laccase-catalyzed grafting and its influence on rheology and enzymatic hydrolysis................................................................................................... 85 4.4 Examination of substrate–water interactions using isothermal thermogravimetric analysis ................................................................................................................................ 92 4.5 Oscillatory rheometry of aspen substrate variants ........................................................... 95 4.6 High-solids liquefaction of aspen substrate variants...................................................... 103 4.7 The degree of the solids effect in the hydrolysis of the aspen substrates ...................... 112 4.8 Conclusions ...................................................................................................................... 114 5 Characterizing the mechanisms of enzymatic liquefaction ............................................ 117 5.1 Background....................................................................................................................... 117 5.2 Tracking substrate properties over the course of enzymatic liquefaction .................... 118 5.2.1 Cellulose accessibility and crystallinity ........................................................................ 119 5.2.2 Particle fragmentation .................................................................................................. 121 5.2.3 Loss of water retention capacity ................................................................................... 127 5.2.4 Material dilution and its role at high solids loading ................................................... 129 5.3 Isolation of material dilution ........................................................................................... 131 5.4 Interparticle interactions ................................................................................................. 133 5.5 Conclusions ...................................................................................................................... 136 6 Enzyme roles and synergism toward enzymatic liquefaction ..................................... 139 6.1 Background....................................................................................................................... 139 ix 6.2 Liquefaction capacity comparison of a basic and an engineered Trichoderma reesei enzyme cocktail ................................................................................................................ 140 6.3 The role of hemicellulases in enzymatic liquefaction .................................................... 142 6.4 In-rheometer reaction method development ................................................................. 147 6.5 In-rheometer liquefaction using a cellulase cocktail ...................................................... 149 6.6 In-rheometer liquefaction using purified enzymes ........................................................ 151 6.6.1 Endoglucanase (HiCel45A) .......................................................................................... 156 6.6.2 Cellobiohydrolase (TrCel7A) ....................................................................................... 158 6.6.3 Glycoside hydrolase family 10 xylanase ....................................................................... 161 6.6.4 Glycoside hydrolase family 11 xylanase ....................................................................... 163 6.6.5 Summary of purified enzyme in-rheometer liquefaction ........................................... 164 6.8 High-solids enzymatic liquefaction with purified enzymes .......................................... 169 6.9 Conclusions ...................................................................................................................... 175 7 Conclusions and future work .............................................................................................. 177 7.1 Conclusions............................................................................................................................ 177 7.2 Future work ............................................................................................................................ 180 7.2.1 Development of biomass pretreatments that produce more favourable substrate slurry rheology ............................................................................................................................ 180 7.2.2 Screening for high-liquefaction-capacity enzymes ........................................................ 181 7.2.3 Optimization of high-solids bioconversion through process design ............................ 181 References.................................................................................................................................... 182 x List of Tables Table 1. Composition, water retention and morphological properties of the range of substrates used in this section, prepared using a variety of pulping and pretreatment methods................................. 53 Table 2. Composition of the pretreatment liquid fraction of steam-pretreated poplar (SPP200). ...... 60 Table 3. Composition, water retention capacity, and morphological properties of aspen substrates pretreated using acidic steam pretreatment (SP), neutral steam pretreatment (N-SP), and mechanical refining (RMP). .............................................................................................................................. 77 Table 4. Qualitative composition summary of aspen substrate variants. .......................................... 78 Table 5. X-ray photoelectron spectroscopy surface analysis of steam-pretreated aspen (SP-Asp), gallic acid-grafted steam-pretreated aspen (SP-Asp-LGal), and resorcinol-grafted steam-pretreated aspen (SP-Asp-LRes). ............................................................................................................................... 88 Table 6. Power law regression analysis of complex viscosity, storage modulus and loss modulus following logarithmic transformation over the linear viscoelastic region for aspen substrate variants at solids loadings (SL) of 15, 10, and 5 %. ............................................................................................ 99 Table 7. Average hydrolysis rates of aspen substrate variants during enzymatic liquefaction at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). .............................................. 104 Table 8. Enzymes utilized in this section, their isoelectric point (pI), molecular weight (MW), and method of purification. ................................................................................................................. 152 Table 9. Enzyme activities of purified preparations, tested in 50 mM sodium acetate buffer, pH 5. 155 xi List of Figures Figure 1. Representative example of unidirectional shear flow yield stress measurement using shear rate-controlled rheometry. The yield stress is taken as the maximum stress accumulated. ................ 44 Figure 2. The influence of solids loading on hydrolysis kinetics of steam-pretreated poplar (SPP200) with regard to hydrolysis extent (A) and hydrolysate glucose concentration (B). The first data point for each solids loading, indicated by surrounding orange box, indicates visual point of liquefaction and the first point at which hydrolysate could be sampled. The T. reesei enzyme cocktail (CTec3) was loaded at 30 mgprotein gglucan-1. ............................................................................................................. 55 Figure 3. Increasing time required for liquefaction (A) and increasing yield stress (B) at increasing steam-pretreated poplar (SPP200) solids loadings. (A′) Time-to-liquefaction on a log–log scale showing power-law relationship with solids loading. (C) Series of SPP200 slurries with increasing solids loadings (as labeled) demonstrating the decreasing level of free water in the slurry................. 56 Figure 4. Influence of the mixing method on high-solids enzymatic hydrolysis of hardwood dissolving pulp, examined with reactions in shaking flasks (200 rpm; dashed lines) and during horizontal rotation (10 rpm; solid lines) with 30 mgprotein gglucan-1 enzyme........................................... 58 Figure 5. Enzymatic digestion of steam-pretreated poplar (SPP200) at 20 % solids, 15 % solids, and 15 % solids plus reconstituted pretreatment liquid fraction (LF) with a T. reesei enzyme cocktail (CTec3) at 30 mgprotein mgglucan-1 showing hydrolysis extent (A) and monomeric carbohydrate concentration (B). ................................................................................................................................................. 61 Figure 6. Examination of the mixing-associated mass transfer boundary during the enzymatic hydrolysis of softwood dissolving pulp (SW-DP), hardwood dissolving pulp (HW-DP), and refined hardwood dissolving pulp (R-HW-DP) at increasing solids loadings following extended hydrolysis (7 days) at 20 mgCTec3 gcellulose-1, horizontally mixed at 10 rpm. (A) Hydrolysate glucose concentrations. (B) Hydrolysis extent expressed as percent of theoretical yield of glucose. The initial apparent linear relationship between solids loading and conversion extent prior to the mass transfer boundary is indicated. (C) Correlation of the solids loading (SL) at which the mass transfer boundary occurs and the hygroscopy of the substrate (represented by water retention capacity). ...................................... 62 Figure 7. Yield stress scaling with solids loading and power-law fits of a variety of woody substrates on a log–log plot. Yield stresses were determined using the controlled deformation method. ........... 64 Figure 8. Correlation of yield stress at 7.5 % solids with particle aspect ratio (A) and correlation of the solid loading (SL) at which the yield stress is 100 Pa with particle aspect ratio (B). ........................... 67 Figure 9. Correlation of substrate hygroscopy with yield stress scaling. The slope of slurry yield stress over solids loading obtained from a linear regression following logarithmic transformation of yield stress as plotted in Fig. 1 (termed the “τy scaling factor”) was plotted against the substrate’s water retention capacity (used here as a measure of hygroscopy) of (A) wood pulps and (B) steam-pretreated wood substrates. ............................................................................................................. 68 xii Figure 10. Light microscopy pictures of size-fractionated steam pretreated poplar (SPP200) showing the nature of fiber network formation of R-28 (A), R-48 (B), R-100 (C) and R-200 (D). Pictures captured using 0.5 % (m/m) solutions dried onto glass microscope slides. R-14 is not pictured due to the particles being too large to observe under the microscope. Scale bars indicate 500 μm. ............... 70 Figure 11. Particle length probability distributions of size-fractionated steam-pretreated poplar (SPP200), showing the probability density functions (A) and cumulative distribution functions (B). Length-weighted means are noted. The R-14 particles were too large to allow analysis with the optical fiber analyzer. ................................................................................................................................. 71 Figure 12. High-solids enzymatic hydrolysis of size-fractionated steam-pretreated poplar (SPP200) at 50 °C, 15 % (m/m) solids with 10 mgCTec3 gfiber-1. (A) Hydrolysate glucose concentration after 120 h of enzymatic hydrolysis. (B) Particle lengths over the course of enzymatic hydrolysis. Not determined for R-28 or R-14 due to difficulty in sampling these large particles representatively during enzymatic hydrolysis. ...................................................................................................................................... 72 Figure 13. Yield stress of size-fractionated steam-pretreated poplar (SPP) suspensions (A) and its relation to particle length (B). Slurries were prepared at 10 % (m/m) solids. .................................... 73 Figure 14. Picture of aspen substrate variants, as labeled. Substrates were vacuum-filtered to a moisture content of ~70 % by mass. ................................................................................................ 78 Figure 15. Volume-based particle size distributions of pretreated aspen substrate variants obtained through laser diffraction particle size analysis. (A) Probability density functions. (B) Cumulative distribution functions. .................................................................................................................... 79 Figure 16. Number-based particle size distributions of pretreated aspen substrate variants obtained through optical fiber analysis. (A) Probability distribution function of particle length. (B) Cumulative distribution function of particle length. ........................................................................................... 81 Figure 17. Slurry yield stress values of pretreated aspen substrate variants determined through unidirectional shear stress ramps at different solids loadings and power-law regression fits shown on linear (A) and log–log plots (B). The power law relationships of the substrates are listed in (B), calculated using the fractional consistency, Cm, in the form τy = aCmb. ............................................... 82 Figure 18. Cellulose hydrolysis of aspen substrate variants during enzymatic hydrolysis with 2.5 mgprotein gcellulose-1 T. reesei preparation (CTec3) at 2 % solids in 2-ml centrifuge tubes rotated end-to-end, showing hydrolysis extent (A) and glucose concentration (B). ................................................. 84 xiii Figure 19. Laccase-mediated grafting of phenolic compounds onto lignin. (A) Reaction scheme for laccase-mediated grafting of phenolic compounds (gallic acid, 3,4,5-trihydroxybenzoic acid; resorcinol, benzene-1,3-diol) onto lignin. The laccase structure shown is a representative laccase from Trametes versicolor (Protein Data Bank code 1KYA). (B) Enzymatic hydrolysis of untreated and laccase-grafted steam-pretreated aspen (SP-Asp) substrates at 2 % m/m for 24 h with increasing enzyme loading. (C) Control reactions (5 mgprotein gcellulose-1) of SP-Asp incubated with non-grafted resorcinol, gallic acid, or laccase individually following washing. (D) Hydrolysis following bovine serum albumin (BSA) blocking (1 h BSA block, 1 % solution by mass; 24 h hydrolysis at 5 mgprotein gcellulose-1). ......................................................................................................................................... 87 Figure 20. Water contact angles of acidic steam-pretreated aspen (SP-Asp), gallic acid-grafted steam-pretreated aspen (SP-Asp-LGal), and resorcinol-grafted steam-pretreated aspen (SP-Asp-LRes) determined through the sessile drop method. The box plots were derived from 10 measurements per sample. ........................................................................................................................................... 89 Figure 21. (A) Enzymatic digestion of untreated and laccase-grafted steam-pretreated aspen (SP-Asp) substrates at 10 % solids for 43 h with increasing enzyme loadings. (B) Yield stress plots of the untreated and laccase-grafted SP-Asp substrates on linear and log–log (inset; base two, error bars removed for clarity) scales, with fitted power-law curves. The power law relationships of yield stress to solids loading (expressed as a consistency fraction, Cm) are given................................................. 90 Figure 22. Isothermal thermogravimetric analysis (TGA) of steam-pretreated aspen (SP-Asp) drying. (A) Derivative thermogravimetric (DTG) curve (left axis; first derivative of the TGA curve) showing mass flow rate, and the solid fraction curve (right axis) showing the fraction of solids of the total mass. The arrow on the DTG curve indicates the aberration in the ‘constant’ rate zone. (B) A close-up of the ‘constant’ rate zone (black curve; left axis) of the DTG curve and its derivative curve (blue curve; right axis), DDTG, showing the ‘dip’ in the mass flow rate. The minimum of the DDTG curve was taken as the boundary of the higher rate and lower rate zones, and the associated mass fraction at this time point was taken as the boundary mass fraction. ................................................................. 93 Figure 23. Small angle oscillatory sweeps of aspen substrate variants at 15, 10, and 5 % solids (arranged in columns). Complex viscosity profiles (A, B, C), storage modulus profiles (D, E, F), and loss modulus profiles (G, H, I) are shown for each solids loading..................................................... 96 Figure 24. Loss tangent (tan δ; G″/G′) summary of small angle oscillatory sweeps of aspen substrate variants at 15 % (A), 10 % (B), and 5 % (C) solids. ......................................................................... 100 Figure 25. Yield stress scaling of aspen substrate variants with solids loading as determined by oscillatory rheometry on a log–log scale. Power law fits are shown, except for RMP-Asp and RMP-Asp-Delig, which did not appear to follow the power law relation. The reason for this deviation is discussed in the text. ..................................................................................................................... 102 Figure 26. Comparison of yield stresses determined through unidirectional controlled deformation (CD) and oscillatory rheometry (OR), shown for acidic steam-pretreated aspen (SP-Asp) and neutral steam-pretreated aspen (N-SP-Asp). Solids loading is shown on a base-two log scale. .................... 102 xiv Figure 27. Hydrolysis extent of aspen substrate variants during liquefaction at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). .................................................................... 104 Figure 28. Particle size reduction of aspen substrate variants during hydrolysis at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3) measured with optical number-based fiber analyzer. (A) Mean particle length progression over time. (B) Mean particle lengths normalized to the mean particle length of the non-hydrolyzed substrates. ................................................................. 106 Figure 29. Oscillatory rheological characterization of aspen substrate variants over the course of enzymatic hydrolysis at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). Complex viscosity (η*) (first column; A, D, G, J, M, P), storage modulus (G′) (second column; B, E, H, K, N, Q) and loss modulus (G′′) (third column; C, F, I, L, O, R) are shown for each substrate across the rows. ....................................................................................................................................... 109 Figure 30. Loss tangent (tan δ; G″/G′) summary for the small angle oscillatory sweeps of the aspen substrate variants after 0, 3, 6, and 9 h of enzymatic hydrolysis at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3)................................................................................................ 109 Figure 31. Example of yield stress determination from oscillatory stress sweeps, shown here for steam-pretreated aspen (SP-Asp). Stress sweeps were done at a frequency of 10 Hz at a measuring duration of 5 s. The arrow indicates the progression of enzymatic hydrolysis. The yield stress was taken as the intersection of the storage (filled symbols) and loss (empty symbols) moduli curves, averaged over three replicates. ....................................................................................................... 110 Figure 32. Yield stress reduction over the course of enzymatic hydrolysis of aspen substrate variants at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3) as determined through oscillatory stress sweeps, shown on a semi-log scale. ...................................................................... 112 Figure 33. Influence of solids loading on the extent of enzymatic hydrolysis (A) and the normalized extent of hydrolysis (B), normalized to the maximum yield at 2.5 % solids. Reactions were run for 48 h with 10 mgprotein gglucan-1 of a T. reesei cellulase cocktail (CTec3). Quadratic fits to the data are shown. ..................................................................................................................................................... 113 Figure 34. The extent of hydrolysis and yield stress over the course of enzymatic hydrolysis of (A) steam-pretreated poplar (SPP200) and (B) hardwood dissolving pulp (HW-DP) at 10 % solids with 20 mgprotein gglucan-1 of the enzyme preparation CTec3. The extent of hydrolysis was determined through HPAEC-PAD analysis of the hydrolysates and yield stress was determined using the controlled deformation method averaged over five replicates. ........................................................................ 118 Figure 35. Cellulose accessibility of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) over the course of enzymatic digestion expressed as maximum adsorption per gram of substrate over time (A and B) and per gram of cellulose as a function of glucan hydrolysis extent (A′ and B′), as determined through stilbene dye-binding (Direct Orange). .......................................... 119 xv Figure 36. Crystallinity index of steam-pretreated poplar (SPP200) over the course of enzymatic hydrolysis (A) and its relationship to cellulose conversion (B) as determined by X-ray diffraction. SPP200 was hydrolyzed at 10 mgprotein gcellulose-1 CTec3 at 2 % solids in 2-ml tubes and reactions were terminated by heat-inactivation. ................................................................................................... 121 Figure 37. Particle length probability distributions of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) over the course of hydrolysis shown as probability density functions (A, B) and cumulative distribution functions (A′, B′). (C) Comparison of the cumulative distributions of HW-DP and SPP200 at full liquefaction (τy<20 Pa; 5 h). ....................................... 122 Figure 38. Particle fragmentation over the course of hydrolysis of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) (A) and the result on sedimentation measurements (B), performed on 10 mg dry mass of substrate at each time point. Sedimentation was done overnight in water following staining with Direct Orange 15 dye of HW-DP to enhance contrast. ..................... 124 Figure 39. Particle fragmentation during enzymatic hydrolysis of steam-pretreated poplar (SPP200) at 17.5 % solids with different doses of enzyme (CTec3), as indicated. The visual point of liquefaction for each treatment is indicated by the orange frame surrounding the data point. Data before 16 h not shown for simplification. .............................................................................................................. 126 Figure 40. Particle width development during the liquefaction stage of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP). Dashed lines indicate 95% confidence interval as determined by the optical particle analyzer. ................................................................................... 127 Figure 41. Slurry yield stress loss and changes in water retention during the hydrolysis of steam-pretreated poplar (SPP200) (A) and hardwood dissolving pulp (HW-DP) (B) at 10 % solids and an enzyme loading of 30 mgenzyme gcellulose-1 CTec3. ................................................................................ 128 Figure 42. The relative contribution of material dilution and particle fragmentation to the liquefaction of steam pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) at a 10% substrate concentration and an enzyme loading of 20 mgprotein gcellulose-1 CTec3. (A) Yield stress reduction over time plotted on a semi-log scale, showing the exponential decay relationships of both substrates. (B) Yield stress plotted against cellulose hydrolysis (semi-log plot) showing dependence on material dilution. (C) Yield stress plotted against particle length (log–log plot) showing dependence on particle fragmentation. Coefficients of determination (R2) are indicated. .................................. 130 Figure 43. (A) Yield stress and cellulose hydrolysis of refiner mechanical pulp (RMP) at 7 % solids and an enzyme loading of 30 mgenzyme gglucan-1 CTec3. (B) Particle length distribution of RMP after 0, 1 and 24 h of enzymatic hydrolysis. The inset shows the correlation between yield stress and cellulose hydrolysis on a semi-log plot. (C) Yield stress of unhydrolyzed RMP over a range of solids loadings. ..................................................................................................................................................... 132 Figure 44. (A) Scanning electron micrographs of northern bleached softwood kraft (NBSK) (0, 1, 2, and 3) pulps that were unrefined (0), refined at 250 kWh t-1 (1), 500 kWh t-1 (2), and 750 kWh t-1 (3). (B) Particle size distribution and cumulative distribution (inset) functions of the NBSK pulps. (C) Yield stress of NBSK pulps at 7.5 % solids...................................................................................... 134 xvi Figure 45. (A) Yield stress reduction over the course of enzymatic hydrolysis of the differentially refined northern bleached softwood kradt (NBSK) pulps at 7.5 % solids. (B) Cellulose hydrolysis using an enzyme loading of 20 mgenzyme gcellulose-1 CTec3 at 7.5 % solids. (C) Particle length reduction during hydrolysis at 7.5 % solids. (D) Cellulose hydrolysis at 2 % solids and an enzyme loading of 10 mgenzyme gcellulose-1 CTec3. ................................................................................................................. 136 Figure 46. Hydrolysis of steam-pretreated aspen (SP-Asp) at 15 % solids with a basic T. reesei enzyme preparation (Celluclast 1.5L supplemented with Novozyme 188) and an advanced cellulase preparation (CTec3) at an enzyme loading of 20 mgprotein gglucan-1. (A) Hydrolysis extent over time. (B) Yield stress over time, with semi-log inset. (C) Yield stress plotted as a function of hydrolysis extent, fitted with a second degree polynomial. (D) Particle length over the course of enzymatic hydrolysis. Yield stresses were measured using the controlled deformation method. ....................................... 141 Figure 47. Hydrolysis of aspen substrate variants with a hemicellulase preparation (HTec3; 50 mgprotein gcellulose-1) at 10 % solids for 24 h. (A) Hydrolysis extents of glucan and xylan. (B) Fractional yield stress (fraction of untreated substrate yield stress). (C) Fractional mean particle length. .......................... 143 Figure 48. Storage (G′) and loss (G″) moduli as well as complex viscosity (η*) of aspen substrate variants before (empty symbols) and after (filled symbols) hydrolysis with a hemicellulase preparation (HTec3; 50 mgprotein gcellulose-1) at 10 % solids for 24 h. ...................................................................... 145 Figure 49. Loss tangent (tan δ; G″/G′) summary for aspen substrate variants before (empty symbols) and after (filled symbols) hydrolysis with a hemicellulase preparation (HTec3; 50 mgprotein gcellulose-1) for 24 h. ............................................................................................................................................. 146 Figure 50. In-rheometer reactions of microcrystalline cellulose (Avicel PH-101) at 20 % (m/m) with T. reesei cellulase (CTec3) at 20 mgprotein gcellulose-1 as well as controls with buffer and bovine serum albumin (BSA; 20 mgprotein gcellulose-1) at 50 °C. The arrow denotes the point at which buffer (50 mM sodium acetate, pH 4.8) or enzyme was added to the add-in-place control or add-in-place cellulase reactions, respectively. .................................................................................................................. 147 Figure 51. In-rheometer reactions of aspen substrate variants at 2.5 % (m/m) solids with an advanced enzyme cocktail (CTec3) at 20 mgprotein gcellulose-1 and a shear rate of 60 s-1. Blue trend lines show the logarithmic best fits to the replicates. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). (E) Refiner mechanical pulp aspen (RMP-Asp). (F) Delignified refiner mechanical pulp aspen (RMP-Asp-Delig). .................................................. 150 Figure 52. FPLC chromatograms showing purification of the enzymes used in this section. (A) TrCel7A: anion exchange followed by size-exclusion (inset) to obtain TrCel7A. The arrow indicates the peak containing TrCel7A that was used for size-exclusion. (B) HiCel45A: anion exchange. The initial two peaks are a 90 kDa protein (confirmed through SDS-PAGE) that could be removed from the preparation. The shaded area indicates the fraction collected for further use. (C) GH10Xyn: anion exchange. (D) GH11Xyn: Size exclusion followed by anion exchange (inset). ................................ 153 xvii Figure 53. SDS-PAGE of purified enzymes and the preparations from which they were purified, flanked on either side with protein markers with molecular weights as indicated. .......................... 154 Figure 54. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the endoglucanase HiCel45A at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). ...................................................... 157 Figure 55. In-rheometer reactions of delignified steam-pretreated aspen (SP-Asp-Delig) at 2.5 % solids with HiCel45A at reducing enzyme loadings. Logarithmic fits to duplicate reactions are shown for each enzyme loading. Original response curves not shown for clarity. ...................................... 158 Figure 56. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the cellobiohydrolase TrCel7A at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). ............................................... 160 Figure 57. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the xylanase GH10Xyn at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). ........................................................................ 162 Figure 58. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the xylanase GH11Xyn at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). ........................................................................ 164 Figure 59. In-rheometer liquefaction summaries for steam-pretreated aspen (SP-Asp) (A), delignified steam-pretreated aspen (SP-Asp-Delig) (B), and delignified neutral steam-pretreated aspen (N-SP-Asp-Delig) (C) showing the logarithmic fits of the averaged data sets for each in-rheometer reaction. ..................................................................................................................................................... 165 Figure 60. In-rheometer reactions of neutral steam-pretreated aspen (N-SP-Asp) at 2.5 % (m/m) with purified enzyme combinations. (A) TrCel7A/HiCel45A (both at 10 mgprotein gcellulose-1). (B) TrCel7A/GH11Xyn (both at 10 mgprotein gcellulose-1). (C) HiCel45A/GH11Xyn (both at 10 mgprotein gcellulose-1). (D) TrCel7A/HiCel45A/GH11Xyn (each at 6.67 mgprotein gcellulose-1). (E) TrCel7A/ HiCel45A /GH11Xyn/GH10Xyn (each at 5 mgprotein gcellulose-1). (F) Summary of logarithmic fits of the N-SP-Asp liquefaction reactions. ................................................................................................................... 168 xviii Figure 61. Purified enzyme reactions with steam-pretreated aspen (SP-Asp) at 10 % solids with 10 mgprotein gcellulose-1 for 4 h at 50 °C, at a reaction volume 50 ml in 100-ml wide-mouth screw-top bottles in duplicate, rotated horizontally at a rotation rate of 10 rpm. Oscillatory rheometry was used to determine complex viscosity (η*; A), storage (G′) and loss (G′′) moduli (B and C), tan delta (D), and yield stress (E). Mean particle lengths were determined using optical fiber analysis (F). Soluble carbohydrates, following acid-hydrolysis to depolymerize oligomers, were determined by HPAEC-PAD (F). HPAEC-PAD was also conducted prior to acid hydrolysis and the chromatograms are shown (H). Note that the baselines have been shifted up for each sample to allow clearer comparison. Fucose was used as an internal standard. ....................................................................................... 171 xix List of Abbreviations, Acronyms and Symbols γ shear strain γ* complex shear strain η viscosity η* complex viscosity λ wavelength μ micro σ shear stress σ* complex shear stress A ampere AIEC anion exchange chromatography Ara arabinan BSA bovine serum albumin BX birchwood xylan CBH cellobiohydrolase CBM carbohydrate-binding module c centi CMC carboxymethyl cellulose CrI crystallinity index Da dalton DNS dinitrosalicylic acid DDTG second derivative thermogravimetric (curve) DTG derivative thermogravimetric (curve) EG endoglucanase FPLC fast protein liquid chromatography g gram(s) G′ storage modulus G″ loss modulus Gal galactan xx GH glycoside hydrolase Glu glucan HMF hydroxymethylfurfural HPLC high-performance liquid chromatography HPAEC-PAD high-performance anion exchange chromatography with pulsed amperometric detection HW-DP hardwood dissolving pulp Hz hertz IEF isoelectric focusing k kilo(s) l liter(s) LPMO lytic polysaccharide monooxygenase LVR linear viscoelastic region M molar m mass, milli, or meter(s) Man mannan min minute(s) mol mole(s) MOPS 3-(N-morpholino)propanesulfonic acid MW molecular weight n nano N-SP-Asp neutrally steam-pretreated aspen N-SP-Asp-Delig neutrally steam-pretreated aspen, delignified kat katal NBSK northern bleached softwood kraft OPP organosolv-pretreated poplar Pa Pascal pI isoelectric point pNPC p-nitrophenyl β-D-cellobioside pNPG p-nitrophenyl β-D-glucopyranoside xxi RMP refiner mechanical pulp RMP-Asp refiner mechanical pulp of aspen RMP-Asp-Delig refiner mechanical pulp of aspen, delignified s second(s) S Siemens SDS-PAGE sodium dodecyl sulfate polyacrylamide gel electrophoresis SEC size exclusion chromatography SP-Asp steam-pretreated aspen SP-Asp-Delig steam-pretreated aspen, delignified SP-Asp-LGal steam-pretreated aspen, laccase-grafted gallic acid SP-Asp-LRes steam-pretreated aspen, laccase-grafted resorcinol SPLPP steam-pretreated lodgepole pine SPP steam-pretreated poplar SW-DP softwood dissolving pulp t ton(s) TGA thermogravimetric analysis TMP thermomechanical pulp TEOA triethanolamine v volume V volt(s) W watt(s) WRV water retention value Xyl xylan xxii Acknowledgements I am indebted for the support, guidance, and mentorship throughout my PhD program to my supervisor Jack Saddler, whose tireless work ethic never failed to inspire. I also sincerely thank my committee members Scott Renneckar, Paul McFarlane, and Jinguang Hu for their advice and feedback throughout my work. I have further received invaluable mentorship from Valdeir Arantes, Richard Chandra, and Maya Piddocke, for which I thank them immensely. A special mention goes to Brianna Bristow and Alex Sigg for offering up their valuable time in helping with experimental work, and Christophe Mobuchon for helping with access to and use of the oscillatory rheometer. My PhD work has been made all the better thanks to the many students, researchers, and staff I have had the pleasure of working with at the Forest Products Biotechnology/Bioenergy group. I will remember the laboratory sessions fueled by music and caffeine fondly. Last but by no means least, I thank my friends and loved ones, without whom my PhD studies would have been far less enjoyable. I am grateful to my sister and parents for their loving support, and to Anna, for continuously making my life brighter. 1 1 Introduction Recognition of the environmental consequences of the continued large-scale worldwide use of non-renewable fossil fuel reserves, particularly when extracted from unconventional sources such as deep-sea reserves and oil sands (Parajulee and Wania, 2014), has increased the exigency of sustainable sourcing of renewable fuels, energy, chemicals and materials (Hoffert et al., 2002; Pacala and Socolow, 2004). Solar, wind and other sustainable sources of electrical energy are envisioned to displace a large proportion of the global energy demands. However, the remaining need for liquid fuels for long-range transport and aviation in the foreseeable future, as well as the need for sustainable sources of chemicals and materials, has shifted the focus towards attaining a biobased economy as part of a multifaceted approach to addressing the increasing environmental footprint of human activities (Chu and Majumdar, 2012; Ragauskas et al., 2006). A number of production pathways are being examined for realizing biomass-based materials, chemicals, and liquid fuels that would go toward establishing a bioeconomy (Dapsens et al., 2012; Harmsen et al., 2014; Kobayashi and Fukuoka, 2013; Zhu et al., 2016), which principally fall under one of two approaches: thermochemical or biochemical. The former uses heat and chemical processes, often under harsh, energy-intensive conditions using high chemical concentrations. The latter leverages biotechnology to enable deconstruction and conversion of biomass through biocatalytic pathways, taking advantage of the specificity of biocatalysts and the milder reaction conditions under which they operate (Bornscheuer et al., 2012). The biochemical approach also has the benefit of having smaller economies of scale, which becomes important when sourcing biomass feedstocks and the costs of transportation associated with securing a sufficient supply (Stephen et al., 2010). Early biochemical ventures into a biobased economy in the 20th and leading into the 21st century were spurred on by bioethanol fuel blending mandates throughout the world. Crops rich in starch such as corn were used as substrates for fermentation into ethanol that could be blended with gasoline (Solomon et al., 2007). This practice continues today, with increasing focus on developing valuable co-products that enable a starch-based biorefinery (Wang et al., 2015). However, the dubious environmental benefit and energy balance of starch-based ethanol and concerns around use of fertile crop land for fuel instead of food have shifted the attention toward more sustainable biomass sources (Hill et al., 2006; Searchinger et al., 2008). Lignocellulosic materials, particularly in the form of residues or waste from existing industries such as agriculture and forestry, but also in the form of 2 bioenergy crops grown on marginal lands, presents an abundant sustainable and renewable supply for biorefining (Robertson et al., 2017). Partial deconstruction of plant cell walls into fibrous materials has resulted in the production of biomaterials such as aerogels, functionalized membranes, and electronics (Zhu et al., 2016). In a complementary fashion, complete depolymerisation of plant polysaccharides into soluble sugars provides a renewable sugar platform that can be converted through “building block” intermediates into a variety of biobased products such as plastics and commodity chemicals (Werpy and Petersen, 2004). Additionally, while lignin’s heterogeneity and high stability present a considerable challenge, it is the only renewable source of aromatic chemicals. It also has the potential to provide important value-added products that improve the economics of lignocellulosic biorefineries. Research into depolymerisation of lignin into homogenous product streams has been a field of ongoing interest (Xu et al., 2014). Currently, fermentable sugars for biobased products are primarily produced in North America from edible starch-bearing substrates. The starch is typically hydrolyzed at high substrate concentrations (more than 30 % solids by mass), using relatively low enzyme loadings (~1 genzyme kgstarch-1), to achieve high final glucose concentrations (Kelsall and Piggot, 2009). It would be similarly desirable to maintain a high ratio of biomass to solvent (water) during the enzymatic digestion of lignocellulosic biomass, referred to as “high consistency”, “high solids loadings”, or simply “high solids”. Doing so improves volumetric productivity and reduces the cost of downstream processing, driving down capital and production costs (Lye and Woodley, 1999; Modenbach and Nokes, 2013). It has been suggested that high biomass loadings are a prerequisite for bioconversion of lignocellulose to be commercially feasible (Larsen et al., 2008). However, following the same high-solids strategy as used for present-day starch hydrolysis has proven problematic. Lignocellulose is highly recalcitrant to enzymatic degradation, requiring 40–200 times more enzyme on a protein weight basis to break down cellulose as compared to starch (Pribowo, 2014). Furthermore, at high lignocellulose loadings—generally considered to be a mass fraction of insoluble solids where little-to-no free water is present in the slurry—biomass slurries become highly viscous and exhibit solid-like rheological behaviour. This makes effective mixing challenging and creates mass transfer problems that limit the efficacy of the enzymatic hydrolysis reaction. Consequently, cellulose hydrolysis yields decrease with increasing solids loadings, and at sufficiently high solids loadings, conversion yields drop precipitously when the mixing method becomes inadequate to promote mass transfer in the slurry (Hodge et al., 2008). As biomass conversion processes have entered a commercial production scale in recent years, dealing 3 with the issues imposed by high solids loadings has become a topic of considerable research interest (Brunecky et al., 2014; Jørgensen et al., 2007; Larsen et al., 2008; Ludwig et al., 2014). Biomass slurries are essentially wet solids (or structured fluids) that are challenging to mix efficiently at the start of high-solids bioconversion. However, during the early stages of the reaction the slurry viscosity decreases and flowability improves, facilitating better mixing for the remainder of the reaction (Nguyen et al., 2015). Studies have indicated that this viscosity reduction stage during which the slurry becomes increasingly liquid-like, frequently termed “liquefaction”, is achieved by substrate deconstruction mechanisms that are distinct from the hydrolysis of the bulk cellulose (Skovgaard et al., 2014). Although a similar viscosity-reducing liquefaction stage occurs in the hydrolysis of starch due to cleavage of starch chains by enzymes, for the case of the intricately structured lignocellulosic biomass, the initial deconstruction mechanisms that lead to viscosity reduction have yet to be fully resolved. A better understanding of the mechanisms behind this dissolution of lignocellulosic substrates is therefore required so that we are better able to develop strategies to achieve fast and efficient liquefaction of biomass. 1.1 The recalcitrant structure of lignocellulosic biomass As mentioned earlier, unlike the relatively simple, homogenous structure of starch that is easily liquefied with low enzyme doses, lignocellulose is a heterogeneous material with a highly complex architecture. It is composed of a framework of cellulose, hemicellulose and lignin that has been developed by nature to provide high rigidity under physical stresses, and to prevent biochemical degradation by microorganisms. The structural organisation of lignocellulosic biomass spans a large range of scales, from the nanoscopic level of cellulose chain crystallization, to the microscopic arrangement of cellulose microfibrils and their association with hemicellulose and lignin in the cell wall, to the macroscopic association of individual plant cells. The recalcitrance of lignocellulosic biomass has been extrapolated from various properties across these many levels of structural organisation (Chundawat et al., 2011a; Inouye et al., 2014; Mansfield et al., 1999). It is therefore important to examine the hierarchical cell wall structure in order to understand how enzymatic deconstruction of lignocellulose might lead to its dissolution and liquefaction. 4 1.1.1 Cellulose Making up around half of the mass of the plant cell wall, much of the cellulose is found as crystalline sheets of individual cellulose chains held together by lateral interchain hydrogen bonds. Multiples of these sheets stack together, stabilized by van der Waals interactions, to form tight bundles called microfibrils. These are several nanometers in diameter and, in the case of wood, are composed of around 24 cellulose chains (Fernandes et al., 2011). Microfibrils are particularly crystalline at their core, becoming less ordered from the centre out, with the most disordered regions occurring at the hydrated microfibril surface (Langan et al., 2014). Microfibrils are packed sufficiently tight that small molecules such as water cannot penetrate, let alone entire cellulase enzymes. Microfibrils additionally aggregate together to form larger bundles termed macrofibrils (Donaldson, 2007). Cellulose is the most abundant and most recalcitrant polysaccharide in lignocellulose and its effective depolymerisation is of principal importance in lignocellulose deconstruction. At the root of the general recalcitrance of lignocellulosic biomass toward cellulose hydrolysis is the highly stable, crystalline structure of cellulose itself. Due to the tight packing of cellulose chains, only a small portion of the chains is exposed and available for enzymatic attack. In order to catalyze the hydrolysis reaction, the enzymes must perform thermodynamic work to lift individual cellulose chains and disrupt the hydrogen bonding and the van der Waals interactions that stabilize the microfibril (Beckham et al., 2011). Despite this inherent recalcitrance, cellulose has been shown to contain amorphous (less ordered) regions that are more accessible and vulnerable to cellulolytic enzymes (Bertran and Dale, 1985; Ciolacu et al., 2011). While there has been some controversy surrounding the precise organization and distribution of these regions in the microfibril and the extent to which these regions can be considered distinct entities, the ‘amorphous’ regions are currently believed to be chain dislocations, arising due to strain-induced twisting of the microfibril (Habibi et al., 2010). The local disruption in chain packing is therefore thought to provide a more accessible region into which the enzymes can diffuse and attach to cellulose chains. 5 1.1.2 Hemicellulose Interspersed among the cellulose fibrils are the other main components of biomass, hemicellulose and lignin. Together, these polymers form an amorphous hydrated matrix that, although not being nearly as tightly packed as cellulose, forms a physical barrier around the cellulose fibrils while providing structural support to the fibrillar network. Hemicellulose (15–35 % of lignocellulosic biomass) is a relatively amorphous, branched polysaccharide that plays an important role in the hygroscopy of biomass by storing moisture (Célino et al., 2013). Hemicelluloses differ in their saccharide composition, types of linkages, degree of polymerisation, and side-chain composition, not only across species, but also across cell tissues in a plant (Fengel and Wegener, 1989). The hemicellulose typically found in hardwoods (angiosperms) primarily consists of xylan (β-1,4-linked β-D-xylose units) and glucomannan (β-1,4-linked β-D-glucose and β-D-mannose units), while softwoods (gymnosperms) are rich in galactoglucomannan (containing a backbone of β-1,4-linked β-D-mannose and β-D-glucose, with single α-D-galactose units attached as side-chains on the mannose or glucose units). Hemicellulose is found on the surface of cellulose fibrils as well as in interfibrillar spaces and fiber pores (Oksanen et al., 1997a). Hemicelluloses have been shown to have an inhibitory effect on cellulose hydrolysis, even at the low quantities that remain following pretreatments that remove hemicellulose (Hu et al., 2011). Hemicellulose contributes to recalcitrance by forming a physical barrier to cellulose, blocking cellulase enzymes from accessing the cellulose chains (Bura et al., 2009). In native primary cell walls, xylogucan in particular has been proposed to act as a tether between cellulose macrofibrils through forming a network in the spaces between the fibrils, limiting their ability to separate laterally (Park and Cosgrove, 2012). Other modeling work has suggested that hemicellulose plays a key role in stabilizing cellulose fibrils, thereby directly contributing to biomass recalcitrance (Silveira et al., 2013). 1.1.3 Lignin Lignin is an amorphous aromatic polymer of phenylpropanoid units that makes up 10–30 % of lignocellulose. It is formed through radical polymerisation of p-hydroxyphenyl (H), guiacyl (G), and syringyl (S) units, which differ in the amount of methoxyl substitutions on the aromatic ring, having none, one, or two, respectively (Ralph et al., 2004). Hardwood lignin primarily consists of S 6 and G lignin units and minor amounts of H, while softwood lignin is primarily composed of G lignin units and small amounts of H (Boerjan et al., 2003). The amount of methoxyl substitutions on the lignin monomers affects the degree and nature of crosslinking within the lignin matrix, with the less-substituted H and G lignin monomers capable of forming greater amounts of carbon–carbon bonds resulting in a more crosslinked lignin (Ferrer et al., 2008). Lignin can form a physical barrier to the cellulose, restricting access by cellulases in a manner similar to hemicellulose (Mooney et al., 1998). Lignin is further covalently linked to hemicellulose in lignin-carbohydrate complex (LCC) linkages, creating additional crosslinks in the cell wall matrix that excludes water and enzymes (Chundawat et al., 2011b). Lignin is additionally considerably hydrophobic relative to cellulose and hemicellulose. Whereas hemicellulose and amorphous cellulose contribute to the hygroscopic nature of biomass, lignin counteracts water uptake. Apart from physical obstruction, lignin is also known to sequester cellulases through non-productive adsorption (Nakagame et al., 2011a). Such interactions, occurring through hydrophobic, hydrogen bonding, and/or ionic interactions reduce the active cellulase concentration and can result in irreversible cellulase loss (Gao et al., 2014). 1.1.4 Ultrastructure The cellulose, hemicellulose and lignin in plant cell walls are assembled into several layers formed over the course of cell differentiation (Plomion et al., 2001). As a plant cell grows, a primary cell wall is deposited around the cell membrane, while being ‘glued’ together to other cells through pectin, a polysaccharide present at very low amounts in wood. Accordingly, pectin is usually grouped together with hemicellulose (Coetzee et al., 2011). The pectin at the intercellular matrix is reinforced with lignin together forming the middle lamella surrounding primary cell walls (Sjostrom, 1993). The primary cell wall is composed of several layers of randomly oriented cellulose macrofibrils, interspersed with lignin and hemicellulose. When the cell reaches its final size, a secondary cell wall is formed interior to the primary cell wall, composed of three distinct sublayers: S1, S2, and S3. The secondary cell wall is the thickest part of the cell and contributes greatly to its mechanical strength. The largest fraction of the mass is found in the S2 layer, which accounts for 75–85 % of the total cell wall thickness. In comparison, the primary cell wall accounts for just 5 to 10 % of the cell wall thickness (Daniel, 2009). 7 The cellulose macro/microfibrils in the secondary cell wall are oriented neatly at specific angles to the cell axis, with different angles for each of the S1, S2, and S3 layers. As well as the microfibril angle, the biopolymer composition of the secondary cell wall layers differs. Generally the lignin content of the S1 layer is higher than that of the S2 and S3 layers while the polysaccharide content of the S2 is greater than that in the S1 or S3 layers (Daniel, 2009). Given that the S2 layer contributes up to 85 % of the cell wall material, most of the cellulose of the cell wall is found in this up to 5-μm thick layer. In contrast, the S1 and S3 layers flanking the S2 layer are each generally only 0.1–0.2 μm thick (Booker and Sell, 1998). To access the majority of the cell wall cellulose found in the S2 layer, cellulases must migrate through or first deconstruct the S1 and/or S3 layers. Donaldson (1988) found that, during the digestion of delignified pine fibers with endoglucanase, the primary cell wall is most easily digestible while the S1 and S2 were much less digestible. Upon an extended treatment, the primary cell wall was fully degraded, while the S3 was degraded only in localised areas that extended to the adjacent S2 layer. The S1 layer did not show any degradation. Donaldson suggested that the hemicellulose distributed on and within the pores of the S1 and S3 layers limits accessibility to the S2 layer. This has since been corroborated by studies showing the beneficial effect of hemicellulose removal on cellulose hydrolysis by increasing accessibility (Kumar and Wyman, 2009; Öhgren et al., 2007). It should be noted that the localised hydrolyzed areas in the S3 layer observed by Donaldson may have been dislocations. Dislocations are transverse ‘weak points’ in plant cell walls with cellulose microfibril angles different from the surrounding microfibrils. They are thought to occur naturally due to compression and strain, as well as being inducible during processing (Nyholm et al., 2001). In the pulp and paper industry, dislocations have long been recognized for their negative effects on mechanical properties of both pulp and paper (Terziev et al., 2005). However, with regard to the deconstruction of lignocellulosic materials, dislocations provide vulnerable areas that are thought to be more susceptible to hydrolysis by acid and enzymes (Ander et al., 2008). Traditionally, based on their susceptibility to hydrolysis, dislocations were thought to be regions of amorphous cellulose. However, it has not been conclusively shown that cellulose crystallinity at dislocations differs significantly from that of the bulk cell wall (Hidayat et al., 2012). For example, Thygesen and coworkers (2007) found that microfibrils continue through dislocations. It has been proposed that the cell wall at dislocations is more ‘open’ and accessible (i.e. more porous), while still maintaining regular cellulose structure (Thygesen et al., 2011). These authors and others 8 (Filonova et al., 2007; Gourlay et al., 2015) have found that various glycoside hydrolases and carbohydrate-binding modules, crystalline-binding and amorphous-binding alike, preferentially localize at dislocations. This seemed to suggest that dislocations are regions of high accessible surface area enabling greater enzyme adsorption regardless of binding affinity. Apart from the discontinuities in the cell walls created by dislocations, plant cells contain regions in the cell wall where no secondary cell wall is deposited, creating openings 20–100 nm in diameter called pits that allow for fluid exchange between cells. When the plant cells are reacted with cellulases, pits allow the enzymes to migrate to the cell lumen. As a result, enzymes have access to both the primary wall and the S3 layer of the secondary wall, even if the cell is otherwise intact (Davison et al., 2013). Despite the close association of cellulose fibrils and interspersed matrix of hemicellulose and lignin, plant cell walls are naturally porous materials. In untreated lignocellulose, these ‘pores’ primarily are on the order of a few nanometers in diameter (Foston and Ragauskas, 2010). However, considering the size of cellulase enzymes, it is apparent that the native porosity is insufficient for access by cellulases. For example, cellobiohydrolase Cel7A (CBH I) from Trichoderma reesei, one of the most studied and industrially applied cellulase enzymes, has a catalytic domain of 5×6×4 nm and a total length of 18 nm including the linker and CBM (Divne et al., 1998). Adding the hydration shell of the enzyme, very few if any of the pores of the untreated substrate are accessible by cellulases. 1.1.5 Influence of pretreatment on substrate structure Due to the native inaccessibility to cellulose and the general recalcitrance of lignocellulose as a whole, pretreatment of biomass—through biological, physical, and/or chemical means—is required to increase its digestibility by cellulolytic enzyme systems (Chandra et al., 2007). Regardless of the specific pretreatment method used, the central objective behind pretreatment of biomass is to increase accessibility for cellulases (Zhao et al., 2012). Cellulose accessibility to cellulase enzymes has been proposed as the principal indicator of substrate digestibility, dictating the minimum enzyme loading for effective hydrolysis (Arantes and Saddler, 2011). Physicochemical treatments that combine chemical and physical pretreatment means have garnered considerable interest toward processing of biomass for bioconversion. These methods have been extensively researched in recent decades and have been successfully scaled up to an industrial 9 scale (Larsen et al., 2008). One such physicochemical method, steam pretreatment, also called steam explosion, exposes biomass to high-pressure steam at 160–260 °C, which, catalysed by organic acids formed from the biomass or by added acid catalysts, primarily enables hydrolysis of hemicellulose as well as degradation of lignin and hemicellulose–lignin linkages (Ramos, 2003). Following a several-minute incubation to allow hemicellulose hydrolysis, the pressure is abruptly released, causing strong shear forces as the biomass is ejected from the reactor. As a result of steam pretreatment, much of the hemicellulose in the substrate is broken down and transferred to the liquid fraction in the form of soluble monomeric and oligomeric saccharides, exposing cellulose surfaces that were covered by the hemicellulose matrix (Kabel et al., 2007). Adjoining cells are separated by the shear forces during decompression and individual cells are fragmented into smaller particles, consequently increasing the substrate surface area. Cleavage of β-ether linkages in lignin resulting in depolymerisation and cleavage of lignin–carbohydrate complex bonds also occurs, as well as minor chemical modification (Overend and Chornet, 1987). The high temperature additionally causes lignin to melt and undergo depolymerisation and repolymerization reactions (Li et al., 2007). This can result in the redistribution of the lignin, partly as agglomerates onto the internal and external cell wall surfaces, and can be observed as lignin droplets on fiber surfaces. Relocation of lignin in this manner, while not removing it from the substrate, has been shown to expose cellulose fibrils (Donohoe et al., 2008), as well as increasing pore size and overall surface area (Meng et al., 2013). Pretreatment methods that subject lignocellulose to a high-temperature aqueous environment in general, also called thermochemical pretreatments (which include steam, hydrothermal and ammonia fiber expansion pretreatment), have been shown to be driven through common processes of lignin–hemicellulose phase separation and cellulose dehydration (Langan et al., 2014). Due to the dehydration of the cellulose during the pretreatment, cellulose fibril organisation is not significantly altered, although crystallinity is slightly increased. However, substrate porosity/cellulose accessibility is significantly increased due to removal/redistribution of hemicellulose and lignin (Ibbett et al., 2013; Kristensen et al., 2008). Since pretreatment can significantly alter substrate structure, it can be expected that pretreatment influences not only enzymatic digestibility but also slurry rheology and liquefaction. Therefore, depending on the severity and nature of the structural modifications induced by the 10 pretreatment, liquefaction behaviour will likely differ significantly between substrates with different treatment histories. 1.2 Importance of biomass slurry mixing for enzymatically catalyzed reactions In order for an enzymatically catalyzed reaction to occur, reactants must be brought together with the enzyme. Effective mixing therefore is of critical importance to the reaction rate. In the case of cellulose hydrolysis, this is complicated by the fact that the reaction is occurring between an insoluble cellulose substrate in an aqueous medium. This medium also serves as the reactant, in which cellulase enzymes are required to first diffuse to and adsorb onto accessible reaction sites on the cellulose substrate before catalysis can occur. As substrate concentration is increased and free water diminishes, bringing the enzyme and its target together becomes more challenging. Limitations in mass transfer incurred by the concentrated slurry have been proposed as a major factor in what has been termed the ‘solids effect’, the observed reduction in conversion yield with increasing substrate loading (Jørgensen et al., 2007). Mass transfer limitations not only reduce the ability of the cellulases to diffuse to the reaction sites, but also limit the diffusion of soluble hydrolysis products away from the reaction sites. This has been shown to exert inhibition on enzyme activity (Kadić and Lidén, 2017; Roberts et al., 2011; Wojtusik et al., 2016). Thus, the method and extent of mixing in high-solids biomass conversion reactions has been shown to have a significant impact on the reaction rate (Ingesson et al., 2001; Palmqvist et al., 2011). This is especially true for the early stages of the hydrolysis reaction, as good initial mixing to effectively distribute enzyme across the substrate has a particularly significant effect on the final hydroysis yield (Roche et al., 2009b). Examining fluid dynamics over the entire course of enzymatic hydrolysis reactions, Wojtusik et al. (2016) showed that, in a stirred tank bioreactor with pretreated corn stover, low mass transfer rates persist at stirring rates below 300 rpm. Mass transfer was shown to be the primary determinant of the observed reaction rate under these conditions. At stirring rates above 300 rpm, the mass transfer limitation was seen to be mitigated and the overall conversion process became limited by the efficacy of the enzymes. While more vigorous mixing can overcome mass transfer limitations and enable higher conversion yields, the high viscosities encountered at high solids loadings result in large energy 11 demands for effective mixing of the biomass slurry (Jørgensen et al., 2007). For example, Fan and coworkers (2003) found that a 4 % increase in solids loading (from ~3 % to 7 %) of paper sludge resulted in five-fold increased power consumption for mixing the hydrolysis reaction until completion. Another group working with corn stover found that the power consumption for mixing during enzymatic hydrolysis increased by an order of magnitude when going from 15 % to 30 % solids, from 79.5 MJ t-1 slurry to 1009.2 MJ t-1 slurry (Zhang et al., 2010). Meanwhile, the 15 % solids reaction produced 854.9 MJ t-1 slurry worth of ethanol, while the 30 % solids reaction produced 1723.2 MJ t-1 slurry worth of ethanol. This showed the large power demand relative to the energy content of the ethanol produced at high solids loadings. At such high power consumption demands, mixing can become a significant portion of the total process cost. Therefore, gaining a better understanding of the rheology of biomass suspensions could inform the development of practical solutions for reducing slurry viscosity and to lessen mass transfer limitations that hinder economical conversion of biomass at high solids loadings. 1.3 Rheology of lignocellulosic biomass slurries Understanding the shear rheology of fiber suspensions, that is, understanding their flow, has been critical to the design and optimization of pulp mixing equipment for pulp and paper operations (Bennington, 2004). Thus, it will similarly be important for control of enzyme-catalyzed reactions during biorefining. Several efforts to use rheological modelling of biomass through computational fluid dynamics to inform reactor design for pretreatment (Hou et al., 2016) and enzymatic hydrolysis (Carvajal et al., 2012) have been reported. In general, rheological behaviour of particle suspensions (also called structured fluids) is a function of temperature and particle concentration, as well a variety of factors related to the particles, such as size, shape, strength of interactions and extent of aggregation (Nguyen et al., 2015). Biomass fiber suspensions are a special case due to the high fiber aspect ratios (e.g. ranging from 40–100 in native woody biomass), causing significant contact to occur between fibers in suspension, which strongly influences slurry rheology (Derakhshandeh et al., 2011). In highly dilute aqueous fiber suspensions, minimal interactions occur between fibers, and the suspension behaves in the Newtonian manner of the suspending liquid (water). However, at higher concentrations, the wood fibers begin forming coherent networks that have mechanical strength due to friction at contact points, resisting flow of the suspension. Apart from frictional forces, other contributions to network mechanical strength can come from hooking of curved or 12 fibrillated fibres, as well as surface tension when the slurry contains considerable amounts of air, as is the case at high solids loadings (Bennington, 2004). The presence of air in voids in the slurry causes the slurry to become a three-phase system of water, fiber and air. At the high concentrations relevant to lignocellulose conversion, the fiber slurry is distinctly non-Newtonian, exhibiting shear-thinning (pseudoplastic) and thixotropic behaviour. With increasing substrate concentration, the suspension becomes increasingly shear-thinning (Nguyen et al., 2013) and begins to resemble a slurry that behaves more like a soft solid than a liquid suspension (Knutsen and Liberatore, 2009), making it a challenging material to process industrially. Considering its impact on fiber network formation, one of the most important characteristics of pulps related to suspension rheology is the length of the fibers. Longer fibers have a higher probability of interacting with other fibers, increasing the amount of contact points and thus increasing the mechanical strength of the fiber network. However, pulp fiber length distributions generally are not uniform, particularly following pretreatments that involve reductions in fiber size. Therefore, to characterize the average length of a fiber population, length-weighted means are generally preferred over arithmetic means, given that longer fibers disproportionally affect suspension rheology (Bennington, 2004). To further analyze the role of fiber length in determining suspension rheology, a parameter termed the “crowding number” has previously been described, which emphasizes the role of fiber interaction in suspension rheology. The crowding number, N, defines the number of fibers in a spherical volume swept by a fiber (i.e. the number of fibers that it could interact with in suspension based on the length of the fiber). Accordingly, at N = 1, collisions start to occur between fibers during flow, while at N ≈ 60, fiber suspensions have about three contacts per fiber (Kerekes and Schell, 1992). This is a critical concentration at which the fibers become restrained by three-point contact that locks the fibers into a network with normal forces acting at the contact points (Derakhshandeh et al., 2011). At high fiber concentrations, the crowding number quickly reaches values well above this critical three-contact value. Taking the example of a poplar pulp, having a mean fiber length of 1 mm and a coarseness of 1 mg m-1, according to the equation of Kerekes and Schell (1992) the crowding number reaches N = 1000 at 20 % solids. Clearly, at the high solids loadings required for economical bioconversion, fiber interactions occur to the extent that the fibers are extensively restrained into a network, forming a solid-like slurry. However, calculating the crowding number assumes the 13 interaction of smooth rods, which, especially in the case of pretreated fibers that become fractured and fibrillated, is too simplistic a model and fails to capture surface interactions. More generally, in the modelling of (polymer) particle suspension rheology, different concentration regimes have been characterized by the extent of interparticle interactions that occur, each with distinct rheological behaviour, namely the dilute, semi-dilute, and concentrated regimes. For high-solids biomass processing, the concentrated regime, defined as the consistency at which the crowding number is greater than the fiber aspect ratio, is the most relevant. However, it is also the most difficult to study and model (Samaniuk et al., 2011). More detailed rheological modelling of high-solids biomass slurries faces various difficulties and therefore has proved challenging, although relative values are generally obtainable (Knutsen and Liberatore, 2009). These modelling issues arise due to the mechanical strength imparted by the network of high-aspect-ratio fibers and the solid-like properties observed at higher consistencies. Fiber suspensions or slurries are observed to have viscoelastic behaviour (having both viscous and elastic characteristics), in that they require a minimum applied stress before the solution starts to flow. Once flowing, the fibers will migrate away from the measuring geometry, making measuring of rheological properties difficult. Fibers additionally tend to aggregate in suspension, even at low consistencies, forming structures called flocs (Schmid et al., 2000). As a result, fiber suspensions are heterogeneous, having regions of strong associations between the fibers within flocs and lower-strength associations in the regions between flocs. Thus, fiber suspensions are heterogeneous both in density and in strength, further complicating their rheological behaviour. In order to initiate motion in a pulp fiber suspension, a force needs to be applied that exceeds the mechanical strength of the fiber network. Due to the heterogeneity in the fiber network, suspension flow initiates in the lower-strength regions between flocs (Swerin et al., 1992). The applied stress at which the suspension starts to flow in the regions between flocs has been termed the yield stress, while higher stresses are required for disruption of the flocs (Bennington, 2004). Given that the yield stress relates to a minimum force required to enable mixing, it is generally regarded as one of the most important rheological properties of fiber slurries impacting pulp and paper processes (Derakhshandeh et al., 2010). It should be noted that the existence of a yield stress is contentious and may not be a true physical property (Barnes, 1999). Rather, yield stress is a useful concept that can be empirically determined on timescales relevant to reaction mixing. Thus, it therefore holds considerable practical value for industrial processes. It is this definition of yield stress that is used in the thesis work reported here. 14 Although extensive rheological characterization of fiber slurries remains difficult, yield stress measurements can be done relatively easily while avoiding the common issues associated with rheological characterization of concentrated fiber slurries (Knutsen and Liberatore, 2009). Not surprisingly, yield stress measurements have also been the primary relative measurement used to characterize and compare the rheology of biomass slurries with respect to bioconversion (Knutsen and Liberatore, 2009; Roche et al., 2009a). Since yield stress is proportional to the fiber network strength, it is heavily dependent on the consistency of the fiber suspension, generally being found to relate to solids loading in a power law (Nguyen et al., 2015). As the suspension consistency is increased, fiber network strength increases considerably, requiring higher stress inputs for the suspension to yield. At high consistencies therefore, yield stress is an important suspension characteristic influencing process design and operation. Measuring yield stress and other rheological parameters that characterize the flow of fluid materials is the domain of shear rheometry. In the context of this thesis and the measurement of biomass slurry flow, shear rheometry can be further divided into unidirectional and oscillatory shear rheometry. Unidirectional shear rheometry, as the name implies, measures the strain of a material under shear flow in one direction. The yield stress of a material can be determined from unidirectional flow in a number of ways, such as through model-fitting (e.g. to the Herschel–Bulkley model; an extension of the Ostwald–de Waele relationship including a yield stress term (Herschel and Bulkley, 1926)) to shear rate versus shear stress data, or a stress growth test (also called controlled deformation) using a constant low-shear-rate deformation (Cheng, 1986). The latter method was used in the initial work reported in the thesis. In contrast, oscillatory rheometry involves induction of a sinusoidal shear deformation in the material and measurement of the resulting stress response (strain). One of the advantages of oscillatory rheometry is that it allows for dynamic measurement of viscoelastic materials to obtain parameters that quantify both the ‘viscous’ and ‘elastic’ characteristics, which in turn can be related to the processability of the materials (Weitz et al., 2007). Another advantage is that oscillatory shear rheometry limits the phenomenon of sample fracture (dissociation of a portion of the sample from the rest of the sample) that is common and problematic in unidirectional shear flow (Mas and Magnin, 1997). Oscillatory rheometry allows measurement of yield stress through oscillation amplitude sweeps, whereby the yield stress is determined by examining the region where the material deviates from linear viscoelasticity (Dinkgreve et al., 2016). 15 The applied stress (σ) during sinusoidal shear deformation and resulting strain (γ) wave forms can be expressed as σ = σ0 cos(ωt) γ = γ0 cos(ωt – δ) (1) (2) where σ0 is the stress amplitude, γ0 is the strain amplitude, ω is the angular frequency (2πf, where f is the ordinary frequency), t is time, and δ is the phase lag (loss angle) (Marin, 1993). For an ideal solid, δ = 0 °, while for a purely viscous (Newtonian) fluid, δ = 90 °, with viscoelastic materials having an intermediate phase lag. Using the relationship cos(x) + j⋅sin(x) = ejx (3) where j = √−1, the real (ℝ) parts of the complex functions of stress and strain (complex stress, σ*; and complex strain, γ*) can be expressed as σ = ℝ(σ*) = ℝ(σ0 ejωt) γ = ℝ(γ*) = ℝ(γ0 ej(ωt – δ)) (4) (5) The complex shear modulus can then be defined as G* = complex stresscomplex strain = σ*γ* = G′(ω) + j⋅G″(ω) (6) This modulus can be determined experimentally using small angle oscillatory sweeps. The real part of the complex shear modulus is called the storage modulus (G′(ω); G′), which quantifies the in-phase stress to strain ratio and represents the elastic portion. The imaginary part of the function is called the loss modulus (G″(ω); G″), and quantifies the out-of-phase stress to strain ratio, representing the viscous portion of viscoelastic materials. A complex viscosity, η*(ω), can furthermore be defined as η*(ω) = complex stresscomplex rate of strain = σ*γ̇*(ω) = '*(ω))ω = η′(ω) - j η″ (7) 16 where η′ = G″ω (8) and η″ = G'ω (9) The functions 8 and 9 describe the dynamic viscosity (η′) and out-of-phase viscosity (η″), making up the real and imaginary parts of the complex viscosity, respectively. The fraction of the loss and storage moduli can be defined, where tan δ = G″G' (10) This function is termed the loss tangent, or tan δ, and provides a ratio of the viscous to elastic portions of the rheological behaviour. If tan δ > 1, the material exhibits primarily viscous behaviour; if tan δ < 1, the behaviour is primarily solid-like; and the point at which tan δ = 1 is termed the gel point or crossover point. Overall, the storage and loss moduli were used in the thesis work as individual indicators of the elastic and viscous aspects of biomass slurry rheological behaviour, while the complex viscosity (or rather its scaling with frequency) was used as an indicator of the degree of shear thinning and tan δ as an overall descriptor of viscoelasticity. Various measuring geometries exist for shear rheometry, such as cone-and-plate, parallel plate, and concentric cylinder. However, these traditional geometries do not perform well with structured fluids. In the case of high-aspect-ratio biomass particle suspensions, traditional geometries suffer from disruption of the sample during insertion of the geometry (James et al., 1987) as well as wall slip phenomena at the surface of the measuring devices (Barnes, 1995). Vane geometries, consisting of equally sized flat blades attached to a central shaft, were developed to address these issues with structured fluids (Barnes and Carnali, 1990; Dzuy and Boger, 1983; Dzuy and Boger, 1985) and have been found to be suitable for measuring wood pulp suspensions (Mosse et al., 2012). Sample disturbance, in the form of compression of the fiber network in the case of biomass slurries, is minimized because of the smaller footprint of the vane geometry (in comparison to e.g. concentric 17 cylinder geometry) (Barnes and Nguyen, 2001). Wall slip phenomena meanwhile are eliminated due to the fact that material in the cylinder circumscribed by the vane blades moves together with the vane, therefore interacting with other layers of the material outside the cylinder rather than interacting with the surface of the measuring device (Keentok, 1982). Thus, vane geometries were used for the rheological measurements reported in this thesis. 1.4 Mixing methods for high-solids biomass deconstruction Through effective mixing, the rheological issues related to the ‘solids effect’ can, at least partially, be overcome to enable production of concentrated product streams (Zhang et al., 2009). Impeller-based mixing methods, which are commonly used for industrial mixing of liquids in a turbulent regime, are difficult to apply to high-solids fiber slurries. Due to the high mechanical strength of the fiber network, the suspension yields only in the vicinity of the impeller. Consequently, a slip plane forms, creating a cavern within the suspension (Bhole et al., 2009). Beyond the boundary of the cavern, the imparted stress is less than the yield stress and no flow occurs. As a result, it becomes difficult to promote flow throughout the vessel. Therefore, positive-displacement pumps and mixers tend to be used instead at high suspension consistencies in the pulp and paper industry (Bennington, 2004). Various alternative mixing methods better suited for high-solids processing have been investigated for conversion of a variety of pretreated substrates. Impeller variations in vertical stirred tank reactors have shown considerable success, such as peg mixer impellers (Zhang et al., 2009), a tried-and-true technology from the pulp and paper industry; plate-and-frame impellers (Wang et al., 2012b); and helical impellers (Ludwig et al., 2014; Zhang et al., 2010). Nevertheless, horizontal mixing systems are increasingly being adopted for high-solids biomass processing. Horizontal reactors minimize particle settling and ‘dead spots’ by using the force of gravity to promote flow of the entire mixture (Modenbach and Nokes, 2013) and are widely used to handle high-viscosity mixtures such as in the food and construction industries. Horizontal mixers have low energy consumption compared to stirred tank reactors and are easily scalable to industrial volumes (Dasari et al., 2009). Various horizontal mixer configurations have been investigated and employed from lab scale (Du et al., 2014; Jørgensen et al., 2007) to pilot plant scale (Hsu et al., 1996; Larsen et al., 2008) for biomass conversion at high solids loadings, showing capability to promote adequate mixing for concentrated fiber slurries with low energy requirements. Horizontal mixing configurations therefore are likely to be adopted for 18 high-solids bioconversion efforts, especially during the initial viscosity-reduction stage of the reaction. 1.5 Two-stage hydrolysis The industrial production of sugar from starch-bearing substrates such as corn through enzymatic hydrolysis currently makes use of two stages of hydrolysis, operating under different conditions optimized for the prevailing reaction requirements and mixture rheology (Taylor et al., 2010). The first, liquefaction, involves thermostable α-amylase enzymes acting at high temperatures to reduce the viscosity of the starch slurry until the slurry is sufficiently pumpable and can be transferred to a stirred tank reactor for impeller mixing. Glucoamylase enzymes are then added to hydrolyse the bulk of the starch during the saccharification stage, operated at a lower temperature to allow for simultaneous fermentation (Kelsall and Piggot, 2009). Although the underlying mechanisms may differ considerably, the rheology of lignocellulosic slurries also dramatically changes over the course of hydrolysis. Initially, high-solids lignocellulose slurries are solid-like mixtures that are best suited to mixing methods designed for dealing with solids or solid–liquid mixtures, such as horizontal mixing configurations. Then, as the hydrolysis reaction proceeds, the mixture becomes increasingly liquid-like, at which point stirred tank reactors become the most effective mixing method. In light of this, it is not surprising that two-stage hydrolysis has also been introduced to lignocellulose bioconversion. Comprehensive technoeconomic analyses of lignocellulose bioconversion, such as from the National Renewable Energy Laboratory (NREL) in the United States, have incorporated two-stage hydrolysis (Davis et al., 2013; Humbird et al., 2011). Here, high-solids slurries are first modeled to be reacted in continuous high-solids reactors upstream of batch stirred reactors, where the slurry is pumped to after viscosity is reduced sufficiently (i.e. when liquefaction is complete). Similar systems as those proposed in the technoeconomic analysis have since been implemented at NREL’s Integrated Biorefinery Research Facility (National Renewable Energy Laboratory, 2015). Liu et al. (2015) tested two-stage hydrolysis with corn stover, using an initial short liquefaction step in a helical ribbon-stirred bioreactor before the liquefied material was transferred for saccharification in larger bioreactors. Their analysis indicated that 60 % of the mixing energy consumption was saved by operating in a two-stage setup. Given the high (>150 °C) temperatures 19 usually employed in pretreatment and the need for active or passive cooling down to the usual temperature of around 50 °C for enzymatic hydrolysis, some studies have examined a high-temperature prehydrolysis step, using hyperthermostable enzymes to perform partial liquefaction at the intermediate temperatures between pretreatment and enzymatic hydrolysis. Brunecky et al. (2014) used cellulolytic enzymes from extremophilic bacteria to prehydrolyse pretreated corn stover, improving hydrolysis rates and yields (10–15 %) in subsequent enzymatic hydrolysis. Similarly, Hämäläinen et al. (2016) used hyperthermostable endoglucanase, xylanase, and mannanase to prehydrolyse steam-pretreated spruce at 15 % solids. They reported increases in subsequent enzymatic hydrolysis yield with a commercial cellulase mixture of up to 50–70 % following prehydrolysis with all three enzymes. These enhanced yields were attributed to reduced slurry viscosity and improved mass transfer. Starting in 2003, the Danish company Inbicon operated several pilot-scale bioconversion plants using their Integrated Biomass Utilization System (IBUS) process, operating a 100 ton day-1 demonstration plant utilizing the same technology (Larsen et al., 2008). In the IBUS process, lignocellulose (wheat straw) was first liquefied at >20 % solids in a “free fall mixing system” (a horizontal paddle mixer) until it became a pumpable liquid, at which point it was pumped to stirred tank reactors for simultaneous saccharification and fermentation. Similarly, the 270,000 t y-1 BetaRenewables commercial-scale cellulosic ethanol plant that started production in 2012 in Crescentino, Italy, featured an enzymatic “viscosity reduction” step as part of its process prior to a simultaneous saccharification and co-fermentation of both the cellulose- and hemicellulose-derived sugars. It appears that two-stage hydrolysis has become a prominent process feature of lignocellulosic bioconversion, having been adapted from pilot and demonstration plants to the world’s first commercial-scale cellulosic ethanol plants. However, despite involving a much more complex deconstruction process in comparison to the hydrolysis of starch, current lignocellulosic hydrolysis processes still operate as a single reaction involving a single enzyme cocktail. In order to reap the benefits of two-stage hydrolysis, it is likely that lignocellulosic deconstruction should be treated as a multifaceted process. This would be similar to the separation of α-amylase-mediated viscosity reduction and glucoamylase-mediated saccharification in starch hydrolysis, where the specific enzymes in ratios relevant to the current stage of lignocellulose deconstruction are added successively (Szijártó et al., 2011b). Therefore, in line with the separation of hydrolysis into two stages in two different reactors, two different enzyme cocktails could conceivably be applied. One a liquefaction 20 cocktail to rapidly reduce viscosity in the high-solids reactor, the other a saccharification cocktail for efficient liberation of as much of the cellulosic and hemicellulosic sugars as possible. However, what is actually occurring during the initial stages of enzymatic hydrolysis of lignocellulose that causes a reduction of slurry viscosity is not well defined. For example, the extent to which different substrate factors influence liquefaction and which enzymes are responsible for liquefying different lignocellulosic substrates are just some of the factors at play. Such information will be required in order to guide the formulation of more effective enzyme cocktails. 1.6 Liquefaction of biomass slurries and the potential mechanisms involved It has been widely reported that, as enzymatic deconstruction of biomass substrates proceeds, slurry viscosity (or yield stress) reduces, particularly at the early stages of the reaction (Jørgensen et al., 2007; Modenbach and Nokes, 2013; Nguyen et al., 2015; Szijártó et al., 2011a). This viscosity reduction stage, during which the slurry rheology shifts from solid-like to liquid-like behaviour, has been termed “liquefaction”. It is thought to be analogous to the initial enzymatic liquefaction step in the production of sugar from starch slurries. However, this analogy does not extend much beyond a resemblance of a viscosity reduction stage. While liquefaction of starch materials simply involves the reduction of the degree of polymerisation of starch molecules by endo-acting α-amylase enzymes, the complex ultrastructural organisation of cellulose intertwined with hemicellulose and lignin does not lend to a simple reduction of degree of cellulose polymerisation to result in a reduction of viscosity. Instead, the viscosity reduction phenomenon has been proposed by some authors to be due to various changes related to fiber morphology and physicochemical properties during enzymatic hydrolysis. These include reductions in interfiber interactions, reduction of fiber length and reduction of water retention capacity (Skovgaard et al., 2014). Alternatively, it has been suggested by other authors that liquefaction is simply due to material dilution as hydrolyzed biomass components transfer from the solid to the liquid phase (Roche et al., 2009a). However, this is contradicted by studies showing that (at low solids loadings) suspension viscosity depletes after a minor amount (less than 10 %) of cellulose has been converted to soluble species (Skovgaard et al., 2014; Wiman et al., 2011). Therefore, viscosity reduction during enzymatic hydrolysis of biomass cannot be explained by material dilution alone. 21 Multiple authors have reported a reduction of fiber (particle) length in the early stages of enzymatic hydrolysis, showing a leveling-off of the mean length well before much of the cellulose has been hydrolyzed (Arantes et al., 2014; Clarke et al., 2011; Del Rio et al., 2012). This fiber fragmentation presumably occurs at fiber dislocations, which present weak points that enable rapid enzymatic fiber cutting (Clarke et al., 2011). More recently, Thygesen and coworkers (2014) modeled fiber fragmentation as a combination of enzymatic weakening of plant cell walls through hydrolysis of glucosidic bonds and mechanical forces from reaction mixing. This was thought to provide the force to rupture the weakened cell wall, resulting in a pattern of fragmentation consistent with cleavage at regularly spaced dislocations along the length of fibers. It appears likely that there is an initial rapid stage of fiber fragmentation that correlates with the observed reduction of slurry viscosity during the initial stages of enzymatic hydrolysis. For example, Skovgaard and colleagues (2014) found that fiber fragmentation of pretreated wheat straw during enzymatic hydrolysis was proportional to a reduction in viscosity, with both viscosity and fiber length simultaneously leveling off early in the enzymatic hydrolysis reaction. These authors further attributed fiber fragmentation to a different enzymatic mode of action than hydrolysis of the bulk cellulose, given that no correlation was found between the rate and extent of fiber fragmentation and overall conversion. Further to this notion of different enzymatic modes, there has been some debate in the literature on the effect of fiber/particle size on enzymatic digestibility. Some authors have found that reduction of particle size does help to improve substrate digestibility (Dasari and Berson, 2007; Yeh et al., 2010), while others have found that it has no influence (Ju et al., 2013; Kadić et al., 2014; Li et al., 2015; Del Rio et al., 2012). The answer to this controversy may lie in the method by which the differently sized particles were obtained, since it is difficult to alter one property (e.g. size) of a substrate without affecting other properties of that biomass substrate. For example, in one of the studies that showed a positive effect of particle size reduction on digestibility, milling of microcrystalline cellulose to reduce particle size also reduced crystallinity (Yeh et al., 2010). In contrast, when substrates were size-fractionated into distinct populations (without undergoing mechanical size reduction treatment), no influence of particle size on digestibility was found (Li et al., 2015; Del Rio et al., 2012). It has also been shown that digestibility did not increase following extended agitation of steam-pretreated spruce suspensions in a stirred-tank reactor to reduce particle size prior to enzymatic hydrolysis (Kadić et al., 2014). Using this method, the spruce fibers were fragmented through physical (shear) forces in a similar manner as during a mixed enzymatic 22 hydrolysis reaction, but without aid from enzymes in weakening the cell walls at dislocations. It therefore appears that purely reducing particle length does not aid enzymatic hydrolysis of the bulk cellulose, likely due to the insignificant amount of surface area gained when fragmenting particles of high aspect ratio. Instead, it has been suggested that internal surface area (porosity) has a much larger influence on enzymatic digestibility than does external surface area, only the latter of which is significantly affected by particle length reduction (Li et al., 2015). Another point to consider in the matter of the influence of particle size is the solids loading at which the study is performed. While most studies have used low solids loadings (2 % m/m or less), Dasari and Berson (2007) performed hydrolysis at higher solids loadings (10–13 %) and found that cellulose hydrolysis increased with smaller particle sizes, as well as drastically reducing slurry rheology. Thus, it is possible that, rather than directly influencing enzymatic digestibility, smaller particles can help to reduce slurry rheology, thereby improving mixing and facilitating a higher rate of enzymatic hydrolysis. By fractionating fully bleached wood pulps into distinct size populations, Lapierre and coworkers (2006; 2009) found that longer fibers correlate to higher suspension viscosity, as measured through a capillary viscometer method. Similar findings have been made using rotational rheometers that have looked at slurries of size-fractioned sawdust particles (Dasari and Berson, 2007) and corn stover particles (Viamajala et al., 2009). These findings support the notion that longer fibers result in higher slurry viscosity, or conversely, that shorter fibers—for example following fragmentation by enzymes—lead to lower slurry viscosity. However, Dibble and colleagues (2011) found that mechanical size reduction of corn stover particles did not reduce yield stress nor increase enzymatic digestibility over a range of 1 mm to 100 μm, while size-reduction as a result of dilute acid pretreatment over a similar size range did noticeably reduce slurry yield stress. This discrepancy between the effects on yield stress from different size reduction methods was thought to be a result of changes in surface properties following pretreatment. This was posited to result in changes to interparticle friction and surface interactions, while it was suggested that the mechanical size reduction method had an insignificant effect on these fiber surface properties. As a result, bulk material properties such as surface roughness, zeta potential and adhesion were suggested to have a greater influence on high-solids biomass slurry rheology than fiber length. However, these suggestions require further investigation since little focus has been placed on the factors influencing biomass slurry rheology at high solids. 23 The influence of surface interaction properties have been indirectly addressed through the addition of rheology modifiers to biomass slurries. Samaniuk and coworkers (2012) surveyed a variety of additives for their efficacy as rheological modifiers, with water-soluble polymers such as carboxymethyl cellulose having the greatest effect. The addition of water-soluble polymers resulted in an up to 80 % reduction in yield stress with an addition of 2 % by mass. These finding strongly reflect the influence of interparticle friction to slurry viscosity, which can be reduced by the addition of water-soluble polymers. Such additives been shown to reduce fiber–fiber interactions, thereby reducing the strength of the fiber network (Zauscher and Klingenberg, 2001). However, the addition of rheology modifiers for industrial bioconversion will incur additional material costs, and depending on the balance of cost and benefit, viscosity reduction may be better suited to enzymes that simultaneously cause the desired biomass deconstruction. A dominant property of lignocellulosic biomass that makes its processing at high solids consistencies challenging is its hygroscopic nature. By being highly absorbent, free water that could lubricate fiber–fiber interactions is effectively reduced with increasing solids loadings. This makes effective dispersal of enzyme across the substrate challenging and causes high slurry viscosity. The water absorption/retention capacity of lignocellulosic substrates has been suggested as another important factor contributing to the rheological properties of lignocellulose (Viamajala et al., 2009). Changes in the water retention capacity of lignocellulosic materials as a result of enzymatic action may play a role in biomass liquefaction. However, it remains to be determined to what degree this influences enzymatic liquefaction, as previous studies into the impact of purified cellulases and hemicellulases on water retention capacity of recycled kraft pulps showed little effect (Oksanen et al., 2000). It is important to note that studies into the rheology of lignocellulosic slurries have been performed with a wide range of particle/fiber sources, be they untreated or pretreated with various thermal/chemical/physical methods, and at a broad range of solids consistencies. It is likely that at different solids consistencies, different factors—fiber length, interparticle friction, water retention, or material dilution—will have different degrees of influence on suspension/slurry rheology and how liquefaction occurs. At low fiber concentrations (dilute or semi-dilute regimes), it is likely that fiber length significantly impacts rheology through influencing fiber network formation, while interparticle friction will be less significant. Conversely, at high solids loadings (concentrated regime), when little-to-no free water is present in the slurry, interparticle friction and water retention capacity can be expected to dominate rheological properties. 24 Thus, it is apparent that the rheology of lignocellulosic biomass suspensions/slurries is a complicated matter, and the role that enzymes play in reducing viscosity to liquefy biomass remains unclear. Thus, as described in the main body of the thesis, further investigations into the modification to the biomass structure occurring during enzymatic hydrolysis that lead to viscosity reduction, and which enzymes are responsible, should provide key insight into how to effectively perform bioconversion at high solids loadings. 1.7 Lignocellulose deconstruction mechanisms and the enzymes involved Much of the photosynthetically fixed carbon in terrestrial plants is dedicated to the synthesis of lignocellulose, and accordingly many organisms on Earth across all domains of life have developed the enzymatic machinery to allow deconstruction of lignocellulose (specifically the polysaccharides contained therein) for its use as a source of carbon and energy, from animals such as gribbles (marine isopods) to various species of archaea, bacteria, and fungi (Berlemont, 2017; Cragg et al., 2015; Graham et al., 2011; Kern et al., 2013). Filamentous fungi in particular have been found to be key decomposers of lignocellulose in nature and play an important role in the global carbon cycle. Their notable efficiency in degrading lignocellulose has been ascribed to their mycelial growth habit, which allows for transport of nutrients into the substrate that are otherwise scarce in lignocellulosic carbon sources such as wood (Sánchez, 2009). Biological depolymerisation of carbohydrates such as cellulose and hemicellulose is primarily achieved through glycoside hydrolases, a class of enzymes that uses a hydrolytic mechanism to break glycosidic linkages, with assistance from other non-hydrolytic carbohydrate-active enzymes such as carbohydrate esterases and polysaccharide lyases, as well as specific enzymatic oxidative mechanisms catalyzed by lytic polysaccharide monooxygenases (LPMOs) (Frandsen et al., 2016). Reflecting the diversity and pervasiveness of carbohydrates in nature, there are a vast number of families of these different carbohydrate-active enzymes that have been grouped together according to their amino acid sequence similarities. These enzyme groups have been catalogued in the Carbohydrate-Active enZymes (CAZy) database (Lombard et al., 2014). Lignin on the other hand is primarily degraded in nature by white-rot fungi that employ non-specific oxidative enzymatic mechanisms catalyzed by peroxidases and laccases (Pollegioni et al., 2015). Cellulolytic enzyme systems come in a variety of formats, from small (~10 kDa) individual enzymes to massive multiprotein complexes sometimes containing more than a hundred enzymes 25 termed cellulosomes that are usually found tethered to select anaerobic bacteria (Artzi et al., 2017) (although also having been reported in anaerobic fungi (Haitjema et al., 2017)), as well as intermediate strategies of untethered multimodular proteins containing several different catalytic domains (Brunecky et al., 2013). While the latter multi-protein/modular systems are certainly worthy of in-depth discussion, the work described in this thesis exclusively used non-complexed free enzyme systems from aerobic fungi. Thus, the following discussion was limited to this subset. The glycoside hydrolases of aerobic filamentous fungi have found the most industrial use given the propensity of these fungi to produce high protein titers. They are also the most well studied cellulolytic enzymes (Payne et al., 2015; Zhang and Lynd, 2004). The paradigmatic enzyme system of aerobic fungi is that of secreted non-complexed free enzymes, found either as single modules or in a bimodular conformation of a catalytic domain (CD) and a carbohydrate-binding module (CBM) separated by a flexible peptide linker. The linker is an intrinsically disordered, typically glycosylated protein segment that allows for some degree of independent movement of the adjoined domains. Evidence has been accumulated through molecular dynamics modelling (Payne et al., 2013) and structure–function studies (Badino et al., 2017b; Hansson et al., 2017) indicating that the linker may play an important role in substrate binding as well as influencing the stability of the catalytic domain. If present as part of bimodular enzymes, CBMs recognize and bind polysaccharide ligands and are recognized to serve a primary function of increasing enzyme concentration at the insoluble substrate surface, also called the proximity effect, as well as having a targeting effect, directing the enzyme toward the specific polysaccharide ligand(s) to which the CBM binds (Boraston et al., 2004; Guillén et al., 2010). The cellulolytic and hemicellulolytic enzymes of the mesophilic soft-rot ascomycete fungus Trichoderma reesei (an anamorph of Hypocrea jecorina) comprise the most well characterized enzyme system capable of lignocellulosic biomass deconstruction. The genome of T. reesei has been sequenced (Martinez et al., 2008). Like other aerobic soft-rot fungi, T. reesei secretes a variety of non-complexed cellulases and hemicellulases from the hyphae, breaking down cellulose and hemicellulose while leaving most of the lignin intact (Martínez et al., 2005). Enzymes produced by industrial T. reesei strains, enhanced through mutagenesis, have dominated the range of commercially available cellulase preparations used in the food, detergent and textile industries (Nieves et al., 1998). Similarly, T. reesei enzymes have been prevalent in the cellulase preparations geared toward biomass conversion, including use in the world’s first commercial scale cellulosic ethanol plants that have come online in collaboration with the leading enzyme producers Novozymes, DSM and DuPont. 26 The main classes of fungal non-complexed cellulolytic enzymes will be discussed next, with particular emphasis on T. reesei, which include: cellobiohydrolases, endoglucanases, beta-glucosidases, hemicellulases, and lytic polysaccharide monooxygenases. Synergism among these enzyme classes is key in enabling effective deconstruction of the complex lignocellulosic matrix (Van Dyk and Pletschke, 2012; Kostylev and Wilson, 2012). These synergistic interactions are complex and numerous, and are dependent on factors related to the substrate, including composition (Hu et al., 2013), physicochemical properties (Väljamäe et al., 1999) and morphology (Ganner et al., 2012), as well as factors related to the enzymes such as mode of action (Kostylev and Wilson, 2014) and substructure specificity (Badino et al., 2017a). The intricacy of these interactions points to the complexity of lignocellulose and the mechanisms that allows its enzymatic deconstruction. Thus, understanding the function of these enzymes and their interactions is important in deciphering the mechanism of action in enzymatic liquefaction of lignocellulosic materials. Following the summary of the enzymes classes in the next section, their influence on substrate properties is discussed. 1.7.1 Cellobiohydrolases Cellobiohydrolases are glycosyl hydrolases that processively catalyze hydrolytic cleavage of cellulose chains into cellobiose units, generally initiating processive runs from free chain ends. These enzymes are the central catalysts behind fungal biomass degradation, and accordingly are often the main enzyme secreted by many fungi, particularly those from glycoside hydrolase family 7 (Martinez et al., 2008). In the case of T. reesei, the cellobiohydrolase Cel7A (originally termed CBHI) generally comprises more than half of the total secreted protein, and together with T. reesei’s second of two cellobiohydrolases, Cel6A (CBHII), can account for up to 80 % of the T. reesei secretome (Herpoël-Gimbert et al., 2008; Nidetzky and Claeyssens, 1994). Both Cel7A and Cel6A feature tunnel-shaped active sites of about 2 nm and 5 nm in length, respectively, with multiple subsites for binding of glycosyl units and a catalytic site within the tunnel near the exit site (Divne et al., 1998; Rouvinen et al., 1990). Cel7A has historically been considered to be exclusively exo-acting, but some studies have indicated the capacity for endo-mode initiation, which has likewise been found for Cel6A (Kurašin and Väljamäe, 2011; Silveira and Skaf, 2018; Ståhlberg et al., 1993). Glycoside hydrolases generally use one of two mechanisms that differ in the fate of the stereochemistry at the anomeric center: retaining or inverting hydrolysis (Wilson et al., 1995), respectively resulting in the stereochemistry being retained or inverted. Cel7A employs a retaining mechanism, while an inverting mechanism is catalyzed by Cel6A. Both T. reesei 27 cellobiohydrolases feature a GH1 CBM with flat, aromatic-residue-rich binding surfaces, reflecting these enzymes’ importance in deconstructing crystalline cellulose (Hoffrén et al., 1995). 1.7.2 Endoglucanases Endoglucanases are endo-acting glycosyl hydrolases that catalyze the hydrolysis of the β-1,4-glucosidic bonds within cellulose chains. Endoglucanases are the second primary enzyme in the arsenal of fungal cellulose degradation and exhibit synergy with cellobiohydrolases by creating new cellulose chain ends on which cellobiohydrolases can initiate processive cleavage (Kostylev and Wilson, 2012). T. reesei is known to produce a number of endoglucanases (EGI/Cel7B, EGII/Cel5A, EGIII/Cel12A, EGIV/Cel61A, EGV/Cel45A) (Saloheimo et al., 1997), although EGII/Cel5A is proposed to account for the majority of endoglucanase activity in the T. reesei secretome (Suominen et al., 1993). 1.7.3 Beta-glucosidases Beta-glucosidases catalyze hydrolysis of cellobiose to glucose, completing the conversion of cellulose into glucose. T. reesei produces extracellular, cell-wall-bound and intracellular beta-glucosidase, but the amount of extracellular beta-glucosidase is insufficient and rate-limiting for commercial applications (Barnett et al., 1991). Exogenous beta-glucosidase, e.g. from Aspergillus spp., is therefore commonly included in T. reesei cellulase preparations. 1.7.4 Hemicellulases Since hemicelluloses are a diverse group of polysaccharides that come in a wide variety of monomer constituents, degrees of branching, degrees of substitutions, etc., an array of hemicellulase enzymes are produced by many microorganisms (Shallom and Shoham, 2003). The Trichoderma reesei genome however possesses relatively few (sixteen) hemicellulase genes, and indeed has been found to have one of the most limited sets of hemicellulases among fungi studied (Martinez et al., 2008). T. reesei enzyme preparations nevertheless seem adequately capable of hydrolysing residual hemicellulose in lignocellulose substrates that have been pretreated with methods that remove and/or relocate hemicellulose, although less severely treated substrates or substrates with hemicellulose that is sufficiently mismatched with T. reesei’s hemicellulase portfolio may require supplementation of 28 exogenous hemicellulase to make up for the brevity of diversity in T. reesei hemicellulases, which are primarily geared toward xylan hydrolysis (Häkkinen et al., 2012). 1.7.5 Lytic polysaccharide monooxygenases Lytic polysaccharide monooxygenases (LPMOs) are a more recently discovered class of enzymes that catalyze direct oxidative cleavage of cellulose chains, distinct from the canonical hydrolytic and hydroxyl radicalization (Fenton) mechanisms of biomass-degrading fungi (Phillips et al., 2011). Originally classified as members of glycosyl hydrolase and cellulose binding module families prior to discovery of their catalytic activity, LPMOs have now been classified under Auxiliary Activities families, and proteins of these families have been identified and characterized in a variety of fungi (Hemsworth et al., 2014), including a member of family AA9 in Trichoderma reesei (Peciulyte et al., 2014). LPMOs have been shown to have specificity toward highly ordered, crystalline cellulose regions (Eibinger et al., 2014). By cleaving and oxidizing chains in crystalline regions, LPMOs create additional chain ends as well as reducing the work required for decrystallization, making hydrolysis of these crystalline regions more favourable for cellobiohydrolases (Vermaas et al., 2015). Strong synergistic interactions of LPMOs with the canonical glycosyl hydrolases toward deconstruction of cellulosic substrates have therefore been shown, with only relatively small doses (2 mgprotein gcellulose-1) required to obtain the conversion boosting effect regardless of the solids loadings used (Hu et al., 2015). 1.8 Influence of cellulolytic enzymes on lignocellulosic substrate properties The use of enzymes from T. reesei as well as from other microorganisms has been of interest to the pulp and paper industry, an industry that has traditionally been burdened by energy-intensive and chemically intensive processing steps, which may be improved through the application of enzymes (Jegannathan and Nielsen, 2013). A considerable amount of research has therefore been conducted in this field on the potential of enzymes and their effect on fiber and pulp slurry properties (Bajpai, 1999; Torres et al., 2012). Although extensive hydrolysis is detrimental to the mechanical properties of pulp and paper, limited action of cellulases on pulp fibers can be beneficial in reducing energy and chemical use as well as improving pulp and paper properties (Mansfield et al., 1996). 29 Considering that considerable slurry viscosity reduction can occur in the early stages of enzymatic hydrolysis, during which limited hydrolysis yet significant fiber modification can occur, the pulp and paper literature can be examined to gain insight into the enzymatic liquefaction of woody biomass. 1.8.1 Cellobiohydrolase Although being principally important for cellulose hydrolysis, cellobiohydrolases have generally not been found to have a significant effect on pulp properties at low extents of hydrolysis. T. reesei Cel7A (CBHI) was found to have no effect on drainability or beatability of hardwood kraft pulp (Kamaya, 1996). A later study using Thermoascus arantiacus cellobiohydrolase acting on hardwood pulps showed that overall handsheet properties were not affected, indicating that fiber–fiber surface interactions were not significantly altered, while on the other hand the strength of individual fibers was reduced (Suchy et al., 2009). This was attributed to localized action of the cellobiohydrolases at structurally irregular regions (e.g. dislocations and fractures) on the fibers, leading to their reduced tensile strength. These authors further reported that at higher enzyme loadings (up to 0.9 mg g-1 pulp) cracks started to become evident on the fiber surfaces, formed by hydrolysis at the structural irregularities on the fiber surface. Studies investigating the effects of various cellulases on fiber suspension rheology have shown little viscosity-reducing effects from cellobiohydrolases. Early studies into the effect of monocomponent T. reesei cellulases (EGI/Cel7B and EGII/Cel5A; CBHI/Cel7A and CBHII/Cel6A) on the properties of softwood fiber suspensions at low (<2 %) cellulose conversion by Pere and coworkers (1995) showed that viscosity was dramatically reduced by both endoglucanases, particularly by EGII/Cel5A, even at this low total cellulose hydrolysis, while both T. reesei CBHs showed little effect. Similarly, in an investigation of the influence of T. reesei enzymes on softwood kraft pulp properties at similar extents of conversion, Oksanen and coworkers (1997b) found that neither of the T. reesei CBHs had an influence on pulp property development during refining. In contrast, both EGI and EGII improved pulp beatability, with EGII being most effective, although endoglucanase treatment also reduced pulp strength, which was attributed to fiber fragmentation. Since cellobiohydrolases are the key players in hydrolysis of crystalline cellulose by noncomplexed cellulase systems, and since they have little influence on the viscosity of pulps following limited hydrolysis, it can be inferred that the enzymatically catalyzed events leading to the 30 rapid initial reduction in viscosity are occurring outside of the bulk crystalline cellulose. These events may include surface modification of particles, such as of removal loose chains not strongly associated with the bulk cellulose (Hildén et al., 2005). Endoglucanases were found to be most efficient in removing such loosely associated cellulose fibrils. 1.8.2 Endoglucanase As mentioned in the previous section, in studies in the pulp and paper literature, endoglucanases have been found, in contrast to cellobiohydrolases, to significantly reduce pulp suspension viscosity (Pere et al., 1995). Similarly, while cellobiohydrolases were found to have no influence on pulp beatability or drainability, endoglucanases have been shown to be the main enzyme affecting these pulp properties (Kamaya, 1996; Oksanen et al., 2000). Treatment of pulp fibers with endoglucanases from Trichoderma reesei and Humicola sp. has also been shown to effectively alter various pulp surface characteristics (Hildén et al., 2005). Furthermore, studies into cellulase treatment of cotton fibers toward production of fabrics have shown that the modification of relevant properties (such as yarn hairiness and pilling tendency) was exclusively due to endoglucanase activity, rather than cellobiohydrolase activity (Pere et al., 2001). With respect to bioconversion, studies examining the role of purified cellulases in modifying fibers toward biomass deconstruction have similarly found endoglucanases to have a central role. Endoglucanases, particularly EGII/Cel5A, have been shown to be primarily responsible for viscosity reduction of wheat straw (Szijártó et al., 2011b; Szijártó et al., 2011a), and also have been the main enzyme implicated in fiber fragmentation at dislocations (Skovgaard et al., 2014). Endoglucanases are further known to smooth cellulosic fiber surfaces by removing protruding cellulose fibrils (Lee et al., 2000). By smoothing off fibrillated cellulose, endoglucanases could potentially reduce the fiber surface coefficient of friction, thereby reducing interparticle friction (Samaniuk et al., 2011). Research into cellulose–water interactions has shown endoglucanases to have a significant influence on water sorption, increasing cell wall-bound water and causing fiber swelling, presumably by loosening up the cellulose structure and increasing porosity following mid-chain cleavage (Felby et al., 2008). Considering the importance of free water for dispersal of enzymes and for the rheology of slurries at high solids loadings, increased water sorption due to endoglucanase activity will cause lignocellulose to take up more free water (if present), potentially increasing slurry viscosity. However, 31 this effect may become overshadowed by other simultaneously occurring fiber modifications that alter slurry viscosity. 1.8.4 Beta-glucosidase While beta-glucosidases are important for the reduction of product inhibition exerted by cellobiose on cellulases, they are unlikely to be important at the low conversion extents associated with fiber rheology modification, where low concentrations of cellobiose are expected. However, at higher solids, where significant hydrolysis can occur before adequate viscosity reduction takes place, beta-glucosidases could be important in alleviating product inhibition during liquefaction. 1.8.5 Hemicellulase Hemicellulases have been used in pulp & paper to assist pulp bleaching, generally at low enzyme loadings to keep hydrolysis at a minimum to preserve pulp yield and retain advantageous properties of hemicellulose in pulp (Bajpai, 1999). At these low extents of hemicellulose hydrolysis, little extraneous effect has been found on pulp properties (Oksanen et al., 1997b; Oksanen et al., 2000). However, with respect to deconstruction of lignocellulose for bioconversion, hemicellulases have been shown to serve an important synergistic role for cellulose conversion (Hu et al., 2011). Depending on the amount of hemicellulose remaining following pretreatment, hemicellulases could therefore also be important for liquefaction, assisting endoglucanases in their central role during viscosity reduction. One study, examining the enzymatic liquefaction of hydrothermally pretreated wheat straw, showed that two different xylanases from glycoside hydrolase families 10 and 11 acting on their own had negligible effect on suspension viscosity (Szijártó et al., 2011b). Another study from the same authors using a thermostable family 11 xylanase similarly showed negligible effect on viscosity (Szijártó et al., 2011a). In contrast, more recent work showed that a family 11 xylanase from Thermoascus aurantiacus could play an important role while acting in concert with a cellulase cocktail in the liquefaction of a similar hydrothermally pretreated wheat straw substrate, increasing the extent of liquefaction and resulting in smaller fibers following hydrolysis (Skovgaard et al., 2014). It is important to note however that the latter study’s pretreated wheat straw substrate still had 10.8 % xylan by mass, compared to 3.6 % in the studies that showed no viscosity-reducing effect from xylanases. Since this earlier work only treated the substrate with the xylanases on their own, xylanases 32 and hemicellulases in general may primarily serve a supplementary/synergistic role during liquefaction, being especially beneficial when high amounts of hemicellulose remain in the pretreated substrate. Considering the high water holding capacity (or hygroscopy) of hemicellulose (Chandra et al., 2015), its presence can be expected to have a significant influence on the amount of free water in the slurry and therefore also influencing slurry rheology. Large amounts of hemicellulose in the substrate may therefore not only be detrimental to cellulose hydrolysis by reducing enzymatic accessibility, but also by decreasing free water in the system, thereby increasing viscosity and reducing mixing efficacy. However, it remains to be seen to what extent this phenomenon plays into liquefaction, especially when much of the hemicellulose is removed following acidic pretreatments. 1.8.6 Lytic polysaccharide monooxygenase LPMOs could be expected to play a role in enzymatic liquefaction due to having, similar to endoglucanases, an endo-type mode of action. Having high specificity toward crystalline regions may complement the viscosity-reducing action of endoglucanases, and the introduction of surface charges following oxidation additionally may have an influence in altering fiber adhesion and interparticle friction at high solids loadings. However, to date, no studies have been reported in the literature on the influence of purified LPMOs on the viscosity of lignocellulose. While Karnaouri et al. (2017) did examine synergism of a purified LPMO and EG from Myceliophthora thermophila, the dynamic viscosity reduction profiles were not significantly different compared to the EG alone. However, any potential synergism was likely not detectable due to the highly excessive enzyme loadings employed of 100 mgprotein gsubstrate-1 per enzyme, which, while no cellulose content of the pretreated wheat straw was reported, would translate into more than 160 mgenzyme gcellulose-1, assuming a typical cellulose fraction of 0.6 following hydrothermal pretreatment. Given the slow rate of action of LPMOs (turnover numbers have been reported to be on the order of minutes; Eibinger et al., 2017) and the corresponding low amount of charge imparted per unit cellulose surface area (as measured by conductometric titration; Hu, 2013), their role might only be supplementary through synergistic interactions with other cellulolytic enzymes. 33 1.9 Thesis overview and research approach As summarized in the previous sections, lignocellulosic biomass is an abundant and renewable resource that can serve as a feedstock for the production of bioproducts in a biorefinery. However, the high solids loadings required for an economically feasible process causes significant challenges due to the inherent fibrous and hygroscopic nature of lignocellulosic materials. Understanding the structure and characteristics of lignocellulosic materials (Section 1.1) is therefore not only integral to its successful pretreatment and depolymerisation, but will also be key in overcoming the rheological challenge of high-solids bioconversion (Section 1.2 to 1.3). As recognition of this rheological challenge has increased (Nguyen et al., 2015), progress has been made in engineering approaches toward reactor design as well as two-stage modes of hydrolysis (Section 1.4 to 1.5). However, relatively little is known about the influence that substrate characteristics will have on slurry rheology as well as of the various pretreatment methods that are being assessed. While it is known that slurry rheology changes during the enzymatic hydrolysis of lignocellulosic biomass in a process termed liquefaction, the physicochemical mechanisms involved are far less clear (Section 1.6). For example, conflicting results have been reported regarding the role of individual enzymes toward liquefaction, likely as a result of differences in the nature of the substrates (Section 1.7 and 1.8). Slurry rheology has a crucial role in determining the efficacy of high-solids enzymatic hydrolysis through its impact on mass transfer, mixing energy requirements, and the overall processability of lignocellulosic substrates. Therefore, a better understanding of the substrate characteristics that affect slurry rheology and how enzymes affect slurry rheology during enzymatic liquefaction will be beneficial in developing pretreatment processes, enzyme cocktails, and process operation modes that allow efficient and cost-effective bioconversion of lignocellulosic biomass. Toward the need for a better understanding of slurry rheology and its relation to high-solids enzymatic hydrolysis, the work described in this thesis was divided into four Results and Discussion chapters (Sections 3, 4, 5, and 6), as detailed below. Section 3 of this work first set out to better understand the challenge behind conducting high-solids bioconversion and to identify the principal substrate factors that limit efficient enzymatic hydrolysis at high solids loadings. The central hypothesis behind this work was that poor enzymatic liquefaction (and therefore challenging rheology throughout the reaction) is a primary determinant of the efficiency of high-solids enzymatic hydrolysis. This was tested through hydrolysis at increasing solids loadings to examine the time required for complete liquefaction, which was expected to 34 increase nonlinearly with solids loading due to worsening mass transfer conditions and increasingly challenging rheological properties. A second central hypothesis in this section was that the extent of the rheological challenge, and thus how well a given substrate scales to high solids loadings, is dependent on the substrate’s treatment history and resulting physicochemical properties. Particularly, it was expected that substrate–water interactions and fiber network formation, as influenced by water retention capacity and particle morphology, respectively, would be the key properties that influence slurry rheology. To test this hypothesis and to try to better understand the relationship between substrate properties and slurry rheology, yield stress profiles of a range of ten woody substrates with diverse treatment histories were determined and correlated to their physicochemical properties. Size-fractionation of substrate particles was furthermore used to specifically examine the influence of particle length on slurry rheology, a property which has been suggested in the literature to be most influential in determining slurry rheology. While the rheological characterization of the diverse range of substrates in Section 3 provided a broad overlook of the rheology of lignocellulosic materials, Section 4 sought to develop a systematic assessment of the influence of substrate composition in determining slurry rheology and liquefaction efficiency. This was approached through differential pretreatment of an aspen poplar (Populus tremuloides) feedstock using acidic steam pretreatment, neutral steam pretreatment, mechanical pretreatment, laccase-mediated grafting, and delignification. This was done with the aim of providing a set of pretreated substrates that all originated from the same biomass feedstock but differed in their relative cellulose, hemicellulose, and lignin contents. Given the hydrophilic nature of cellulose and hemicellulose, in contrast to the hydrophobic nature of lignin, it was hypothesized that the hydrophilic:hydrophobic polymer ratios would exert strong control on substrate hygroscopy and therefore have a direct influence on the amount of free water in the slurry and its rheology. Accordingly, it was posited that, from a rheological point of view, it might be beneficial to retain lignin in the substrate to reduce substrate hygroscopy and thereby improve slurry rheology, particularly if hydrophobic lignin covers the substrate surface. Extensive rheological characterization using oscillatory rheometry was conducted to test these hypotheses and to examine the influence of the compositional differences between the aspen substrate variants. It was then questioned whether the rheological behaviour of these substrates could be tied to their high-solids liquefaction and hydrolysis kinetics. This was firstly investigated by tracking liquefaction using off-line rheometry over the course of enzymatic hydrolysis at 15 % solids. Secondly, it was examined how well hydrolysis of the aspen substrate variants could scale to high solids loadings, where it was hypothesized that the 35 more challenging the rheological properties of a substrate, the more pronounced its ‘solids effect’ (i.e., the reduction in hydrolysis yields with increasing solids loadings). Despite the importance of efficient enzymatic liquefaction in catalyzing high-solids bioconversion, the exact mechanisms through which enzyme action reduces slurry viscosity/yield stress, and the degree to which the different mechanisms that have been proposed contribute to this effect, remains unclear. Therefore, the work described in Section 5 aimed to answer: what are the mechanisms driving enzymatic liquefaction, to what extent do the different mechanisms contribute, and is the relative influence of these mechanisms dependent on the rheological regime/solids loading? To answer these questions, this work first assessed the overall enzyme-mediated changes made to the substrate structure during enzymatic hydrolysis of a steam-pretreated poplar substrate and a model cellulosic substrate to examine whether a distinct liquefaction stage could be identified. Then, a variety of substrates were specifically prepared to allow for a restricted focus on the individual mechanisms that have been proposed to account for enzymatic liquefaction, which included material dilution, particle fragmentation, alteration of interparticle interactions, and reduction in water retention capacity. Through measuring the changing rheology of the various substrates during enzymatic hydrolysis, the relative influence of the liquefaction mechanisms was interrogated with the hope of enabling a better mechanistic definition of enzymatic liquefaction. Improving enzymatic liquefaction will require a deeper understanding of the roles of individual enzymes in order to optimize enzyme cocktails toward enabling rapid viscosity/yield stress reduction. To this end, the work described in Section 6 examined the role of individual or combinations of enzymes toward enzymatic liquefaction in relation to complete enzyme cocktails, using real-time viscometry during in-rheometer hydrolysis reactions as well as using offline oscillatory rheometry measurements of high-solids reactions. While previous work has indicated that endoglucanases may be the main enzyme responsible for causing enzymatic liquefaction, we hypothesized that this is dependent on the nature and composition of the substrate, as well as the solids loading at which the reaction is taking place. To allow an assessment of the substrate-dependency of liquefaction, the aspen substrate variants prepared in Section 5 were used during hydrolysis with endoglucanases, cellobiohydrolases, xylanases, and their combinations. Overall, the main objectives of the thesis were to provide insight into the rheological challenges posed by high solids loadings and to assess how effective hydrolysis in these conditions is influenced by the nature of the lignocellulosic substrate and its corresponding slurry rheology. 36 Furthermore, we hoped to gain a better understanding of how enzymatic liquefaction takes place and how it can be promoted in order to facilitate efficient bioconversion at high solids loadings. 37 2 Materials and Methods 2.1 Preparation of lignocellulosic substrates Chipped hybrid poplar (Populus trichocarpa × Populus deltoides) was steam-pretreated at 180, 190, and 200 °C for 5 min catalyzed by 3 % SO2 (by mass) to obtain the steam-pretreated poplar (SPP) substrates SPP180, SPP190, and SPP200, respectively. The chosen pretreatment conditions were identified in previous work in our group to provide a well-digestible substrate that retains high sugar recovery (Ewanick et al., 2007). Steam pretreatment was performed at a solids loading of 200 g (dry matter basis) in a two-litre reactor. Following decompression into a collection vessel, multiple rounds of steam pretreatment were conducted before all pretreated substrate was collected. The resulting pulp was washed extensively with tap water to remove the influence of solubilized components that could interfere with enzymatic catalysis and vacuum-filtered to a moisture content of ~70 %. A ~50 ml sample of the filtrate was saved for analysis of the pretreatment liquor. Lodgepole pine (Pinus contorta) chips were treated in a similar manner at 200 °C to obtain the steam-pretreated lodgepole pine (SPLPP) substrate. Organosolv-pretreated poplar (OPP) was obtained by treatment of hybrid poplar chips with aqueous ethanol (60 % v/v), containing H2SO4 (1.1 %) as catalyst, in a custom-built rotating digester made by Aurora Products Ltd. (Savona, BC, Canada) at 170 °C for 60 min. The hybrid poplar chips were cooked in two-liter vessels, 200 g (dry weight) at a time. The hardwood dissolving pulp (HW-DP) is a mixed hardwood pulp obtained from Fortress Paper Ltd. (North Vancouver, BC). The softwood dissolving pulp (SW-DP), made from western hemlock (Tsuga heterophylla), was provided by Neucel Specialty Cellulose (Port Alice, BC). Both dissolving pulps were provided as sheets, which were rewetted and resuspended using a lab-scale disintegrator. Some of the hardwood dissolving pulp was additionally PFI-milled to obtain a refined hardwood dissolving pulp (R-HW-DP) with mild fibrillation. The pulp was fed at 10 % solids into a PFI mill run for 10 000 revolutions, according to TAPPI method T248. Refiner mechanical pulp (RMP) and thermomechanical pulp (TMP) were provided by FPInnovations (Vancouver, BC). Aspen poplar (Populus tremuloides) chips with a moisture content of ~7 % were obtained from Alberta-Pacific Forest Industries Inc. (Boyle, Alberta). Steam pretreatment was performed on 200 g (dry matter) of chips at a time in a two-liter reaction vessel with 3 % (by mass) SO2 as a catalyst. 38 SO2 was vented into plastic bags containing the weighed amount of chips, closed, and then weighed to confirm the SO2 loading following overnight incubation and release of excess non-absorbed SO2. Steam pretreatment was performed at 200 °C with a residence time of 5 min before decompression into a collection vessel, wherein multiple rounds of pretreated substrate were collected and mixed. The resulting pulp was washed extensively with tap water to remove the influence of solubilized components that could interfere with enzymatic catalysis and vacuum-filtered to a moisture content of ~70 %, providing the SP-Asp substrate. A small amount of the original pretreatment liquor additionally was saved for analysis. Neutralized steam pretreatment of aspen poplar chips was done by soaking aspen poplar chips (200 g dry matter) in sodium bicarbonate (8 % by mass) dissolved in 200 ml water ahead of steam pretreatment to neutralize organic acids liberated from the biomass during pretreatment. The chips were steamed at 210 °C for 5 min until decompression into a collection vessel. Neutralization was confirmed through measurement of the pH of the pretreatment liquid fraction (pH 7.1 compared to pH 2.4 following acid-catalyzed steam-pretreatment). Due to a lack of acid catalyst during the neutralized steam pretreatment, little particle fragmentation occurred following decompression. Accordingly, to bring the particle size distribution closer to that of SP-Asp, the neutrally pretreated substrate was ground using a single pass through a twin-gear juicer (Super Angel, Tustin, CA, USA). The substrate was then extensively washed with tap water and vacuum-filtered to a moisture content of ~70 %, resulting in the N-SP-Asp substrate. Grafting of phenolic compounds (gallic acid, 3,4,5-trihydroxybenzoic acid; and resorcinol, benzene-1,3-diol; Sigma-Aldrich) onto SP-Asp was done using a Myceliophthora thermophila laccase preparation (Novosample 51003; Novozymes North America Inc, Franklinton, NC; (Berka et al., 1997)) at 45 °C for 2 h to modify the chemical properties of the SP-Asp lignin. Gallic acid and resorcinol were added at 1 mmol per gram of substrate dry matter at a total reaction volume of 1.5 l in a 3-liter Erlenmeyer flask, hand-stirred every 30 minutes. 130 μl of laccase preparation was used per gram of substrate. Following two hours of reaction time, the grafted substrates were extensively washed with tap water and vacuum-filtered. SP-Asp grafted with gallic acid and resorcinol resulted in the SP-Asp-LGal and SP-Asp-LRes substrates, respectively. Control reactions were run under the same conditions, omitting the phenolic compounds for a laccase-only control, or omitting the laccase for phenolic compound-only controls with gallic acid and resorcinol each. 39 A refiner mechanical pulp (RMP) variant was made from aspen poplar wood chips by feeding chips to a laboratory disc refiner (Sprout-Waldron) with D2A507 plates (Chandra et al., 2016). The wood chips were refined in three steps with the disc clearance set at a decreasing order from 0.5 mm, to 0.2 mm, and then to 0.1 mm. Delignification of SP-Asp, N-SP-Asp and RMP-Asp was done through an acid chlorite bleaching method using 0.44 M NaClO2 (sodium chlorite) in the presence of 0.167 M acetic acid based on the PAPTAC Useful Method G.10U. Reactions were performed at a volume of 1.5 L in three-liter lightly-stoppered Erlenmeyer flasks containing 150 g substrate dry matter for 24 h in the dark. N-SP-Asp was taken through two rounds of chlorite bleaching to obtain its delignified variant. The pulps were extensively washed following bleaching until a neutral pH was reached through successive rounds of suspension in tap water and vacuum-filtering on a Büchner funnel. 2.2 Particle dimensions Number-based fiber dimensions were measured optically using a HiRes Fiber Quality Analyzer (OpTest Equipment Inc., Hawkesbury, ON) that uses a sheath flow cell to hydrodynamically orient fibers into a thin plane before passing through a charge-coupled device image sensor where fibers are measured by circular polarized light. The reported particle lengths are the length-weighted mean lengths and represent a dilute sample of 20,000 fibers measured at 20–40 events per second. Volume-based fiber dimensions were determined using a laser diffraction particle size analyzer (Mastersizer 2000 with Hydro 2000G wet sample dispersion unit; Malvern, Westborough, MA). Samples of each pulp were sonicated while stirred in the dispersion unit until thoroughly suspended, as determined by the diminishing change in laser obscuration and mean particle sizes. Reported values and distributions represent an average of two technical replicates. A refractive index of 1.56 was used for measurement of the lignocellulosic materials. Reported mean particle diameters are the surface-weighted mean diameter (Sauter mean diameter; D[3,2]). 2.3 Crystallinity index Crystallinity index (CrI) was measured through wide-angle X-ray diffraction by using a Bruker D8-Advance powder X-ray diffractometer in the Bragg–Brentano configuration with Cu Kα radiation (λ = 1.5406 Å) at scattering angles from 5–80 °. Samples were air-dried into flat discs and 40 mounted onto silicon zero diffraction plates. Bruker TOPAS software (version 4.2) was used to model the percentage crystallinity according to the cellulose 1β model (Nishiyama et al., 2002). 2.4 Cellulose accessibility The accessibility of cellulose was determined through the stilbene dye-binding protocol described by Chandra and Saddler (2012). Briefly, the stilbene-derived dye Direct Orange 15 (Pontamine Fast Orange 6RN, lot no. 814071; Pylam Products Co. Inc., Garden City, NY) was first suspended at 10 mg ml-1 and ultrafiltered in a pressure cell containing a membrane with a 100 kDa nominal molecular weight limit (Amicon, Millipore) in order to eliminate the <100 kDa dye fraction that binds poorly to cellulose. Following ultrafiltration and resuspension, the concentration of >100 kDa dye was found to be 7.5 mg ml-1 through oven-drying on pre-weighed aluminum dishes. In preparation for dye-binding, 10 mg dry weight of substrate to be analyzed was added to 2-ml screw-top centrifuge tubes and suspended in a 30 mM phosphate-buffered saline (70 mM NaCl, pH 6) solution. Increasing amounts of dye (0.19, 0.38, 0.56, 0.75, and 1.13 mg) were then added to a total volume of 1 ml to obtain an adsorption isotherm curve after incubation for 6 h at 70 °C in a rotating incubator. Following adsorption, the tubes were centrifuged and the supernatant was collected to be measured for absorbance at a wavelength of 445 nm in a spectrophotometer (Cary 50 UV-Vis, Varian). The amount of dye in the supernatant was calculated according to the Beer–Lambert law with an attenuation coefficient of 40.3 l g-1 cm-1, as determined with a standard curve. The amount of dye adsorbed to the substrate was calculated by the difference between the amount of dye in the supernatant and the total amount of dye added. The adsorption data were then fitted to the Freundlich adsorption model (+, = 𝐾𝑐0/2 , where x is the mass of dye, m is the mass of substrate, c is the equilibrium concentration of dye in the solution, and K and n are constants) such that the maximum adsorption value (Amax) could be determined from a log–log plot of c and the mass of bound dye. 2.5 Substrate and pretreatment liquor composition Biomass substrate compositions were determined based on the National Renewable Energy Laboratory standard laboratory analytical protocol (Sluiter et al., 2012). Monomeric carbohydrates were measured via high performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) on an ion chromatography system equipped with a gold-electrode detector 41 (ICS-3000, Dionex, Sunnyvale, CA) using a CarboPac PA-1 column in combination with a CarboPac PA-1 guard column at an isocratic flow of ultrapure water at 1 ml min-1, using L-fucose as an internal standard. A post-column flow of 0.2 M NaOH at 0.5 ml min-1 was mixed in ahead of the detection chamber. Concentrations of acetic acid, furfural and hydroxymethylfurfural in the pretreatment liquor were determined through measuring absorbance at 280 nm (AD-20 absorbance detector, Dionex) following cation exchange on an Aminex HPX-87H column (Bio-Rad, Hercules, CA) with an isocratic flow of 0.6 ml min-1 5 mM H2SO4. Quantification of soluble phenolic compounds was done with a microplate-based Folin−Ciocalteu method (Ainsworth and Gillespie, 2007) and expressed as vanillin equivalents on a mass basis. 2.6 Fiber fractionation Fractionation of biomass fibers into distinct fiber populations was done by running a pulp sample through a Bauer-McNett classifier (Model 203; Bauer, Brantford, ON) with sequential stirred containers equipped with 14, 24, 48, 100, and 200 mesh screens containing 1180, 710, 300, 150, and 75 μm diameter openings, respectively. Water flow through the screens was maintained for up to 30 min to allow separation of fibers, after which the containers were drained and the fibers filtered out through retention on a fine cloth. 2.7 Conductometric titration Conductrometric titration was used to determine weak acid (carboxylic) groups on biomass substrates based on SCAN-CM 65. In brief, 0.15 g (dry mass) substrate was suspended in 15 ml 0.1 M HCl for 1 h for protonization. Excess acid was then removed with repeated washing on a filter paper-lined Büchner funnel with deionized water (250 ml total). The substrate was scraped off and suspended in 50 ml 1 mM NaCl and titrated with 50 mM NaOH 20 μl at a time while measuring the conductivity of the solution. The weak acid group content was then determined from the titration curve from the region between the intersections of the decreasing and increasing phases with the steady phase. 42 2.8 Contact angle Flat sheets of pretreated substrate were prepared using a laboratory handsheet press (Mavis Engineering Ltd., England). Suspensions of ~2 g of substrate in 50 ml ultrapure water were first vacuum filtered onto filter paper in a Büchner funnel. The vacuum-filtered substrates were then transferred to the handsheet press and pressed at 50 psi for 5 min, followed by another 2 min at 50 psi after tightening the wing nuts of the press. The sheets were allowed to dry in a climate-controlled room maintained at 23 °C and a relative humidity of 50 %. Water contact angles were determined using the sessile drop method with an optical contact angle meter (CAM 101; KSV Instruments Ltd., Finland) with a frame rate of 60 Hz. The first frame at which the droplet stabilized on the surface was used for image analysis in the KSV CAM software (v. 3.99). A minimum of 10 measurements were made per sheet. 2.9 Light and scanning electron microscopy Light microscopy of biomass fibers was done with a JENAMED 2 microscope (Carl Zeiss, Germany; 2.5× objective). Fiber suspensions of 0.5 % (mass) solids were loaded onto glass slides with a plastic cover slip. Digital pictures were taken with an INFINITY 3 microscopy camera (Lumenera Scientific, Ottawa, ON). A Hitachi S-3000N scanning electron microscope (SEM) was used at 10 kV to obtain scanning electron micrographs of air-dried, gold-coated fiber samples. 2.10 X-ray photoelectron spectroscopy For substrate surface analysis by X-ray photoelectron spectroscopy (XPS), thin substrate sheets were prepared through vacuum-filtration of dilute substrate suspensions on a Büchner funnel. The XPS measurements were carried out using a Leybold Max 200 X-ray photoelectron spectrometer (Cologne, Germany) with a monochromated Al Ka X-ray source. The detector position was at an angle of 90° relative to the sample surface. A Gaussian curve-fitting program was used to deconvolute the carbon (C1s) peak at 285 eV. The chemical shifts relative to class I carbon (C-C, C-H and C=C) used in the deconvolution were 1.7 eV for C-O (class II carbon), 3.1 eV for C＝O or O-C-O (class III carbon), and 4.3 eV for O-C=O (class IV carbon) groups (Laine et al., 1994; Liu et al., 2013). 43 2.11 Isothermal thermogravimetric analysis Biomass substrates were suspended in deionized water at a solids loading between 2 % and 3 % (by dry mass) prior to thermogravimetric analysis (TGA). Samples of the suspended substrate with a total weight between 50 and 100 mg were transferred to tared aluminum TGA sample pans loaded on a thermogravimetic analyzer (Q500; TA Instruments, Canada). The drying process was started with a heating ramp of 150 °C min-1 up to 60 °C. Isothermal drying was maintained until no further change in mass was detected, indicating that the sample had fully dried. 2.12 Water retention capacity Water retention capacity (or water retention value; WRV) was used as a measure of substrate hygroscopy. Test pads were formed in 15-ml centrifuge tubes capped with 325-mesh screens, and the WRV was then determined according to TAPPI Universal Method 256. 2.13 Unidirectional shear yield stress Unidirectional shear yield stress of biomass slurries was measured with a stress growth test (also called controlled deformation) (Cheng, 1986) in a HAAKE Viscotester 550 rotational viscometer (Thermo Fisher Scientific, Karlsruhe, Germany) measuring the shear stress as a function of time during deformation at a constant shear rate of 0.0125 s-1 (Fig. 1). This low shear rate allows a gradual build-up of stress on the slurry until a peak stress is reached at which the slurry yields and flow is initiated. Measurements were made at 23 °C in a cup (26-mm radius, 82-mm height) using a four-bladed vane geometry (9-mm radius, 28-mm length) lowered approximately halfway into the slurry. 44 Figure 1. Representative example of unidirectional shear flow yield stress measurement using shear rate-controlled rheometry. The yield stress is taken as the maximum stress accumulated. 2.14 Oscillatory rheometry Oscillatory rheometry was performed with an MCR 502 rheometer (Anton-Paar GmbH, Austria) using a four-bladed vane geometry (24.4 mm diameter, with each vane having a height of 19 mm) in a cylindrical cup (28.5 mm diameter, 67 mm height). The cup was filled with 40 ml of substrate slurry and the measuring geometry was lowered approximately halfway into the slurry. Following insertion into the slurry, the geometry was raised by 1 mm to relieve normal forces incurred by compression of the slurry particles. For each sample replicate, a frequency sweep and a stress sweep were conducted in sequence, for a minimum of three replicates. Between replicates, the geometry was raised out of the slurry and the slurry was transferred into and mixed in a beaker with a spatula, before being returned to the cup. Frequency sweeps were performed on a logarithmic ramp with 30 measurement points from 100 Hz to 1 Hz, with each point measured for a duration of 10 s. A stress amplitude of 20 Pa was generally used, except for samples where 20 Pa was outside of the linear viscoelastic region (LVR). In these cases, a stress sweep was first conducted to determine the LVR such that a stress amplitude could be chosen that fell within it. Stress sweeps were conducted at a frequency of 10 Hz on a logarithmic ramp, generally from 0.1–100 Pa (depending on the slurry’s LVR) to a value just above the yield stress, as determined by an initial stress sweep. 50 measurement points were taken with a duration of 5 s. The storage modulus (G′), loss modulus (G″), and complex viscosity (η*) were recorded as determined by the RheoPlus software (version 3.61, Anton-Paar). 0501001502002500 60 120 180Stress (Pa)Time (s)Yield stress (𝜏4) Increasing stress Initiation of flow 45 Oscillatory yield stress was determined from the crossover point of the storage and loss moduli curves in the stress sweep, taken as an average of the replicates ± the standard error. 2.15 Enzymes and their purification Protein purifications were done on a fast protein liquid chromatography (FPLC) system (ÄKTAprime plus, GE Healthcare). TrCel7A was purified from the Trichoderma reesei cellulase preparation Celluclast 1.5L (Novozymes; Davis, CA). The crude cellulase preparation was first desalted on a cross-linked dextran bead column (5 ml of two-fold diluted preparation; HiPrep 26/10 Desalting Column, GE Healthcare) into 20 mM triethanolamine (TEOA) buffer pH 7 at 10 ml min-1. The desalted preparation was then injected into a quaternary ammonium cross-linked agarose anion exchange column (Q Sepharose High Performance, GE Healthcare) in a linear gradient from buffer A (20 mM TEOA pH 7 with 0.1 M NaCl) to buffer B (20 mM TEOA pH 7 with 0.3 M NaCl) at 3 ml min-1. This refinement of a method earlier established in our laboratory (Hu, 2013) greatly reduces the elution time and enables cleaner separation of the TrCel7A peak. The TrCel7A-containing peak was further purified on a size-exclusion column (HiLoad 16/600 Superdex 75, GE Healthcare) with 50 mM sodium acetate buffer pH 5 at a flow rate of 0.5 ml min-1. Between chromatography steps and upon completion of purification, collected fractions were concentrated by ultrafiltration in a centrifuge at 4000×g with centrifugal filter units having a 10 kDa nominal molecular weight limit (Amicon Ultra-15, Millipore). A crude preparation of Humicola insolens Cel45A (HiCel45A) cloned and expressed in Aspergillus oryzae was provided by Novozymes (Davis, CA). The preparation was first desalted (HiPrep 26/10 Desalting Column, GE Healthcare) into 20 mM TEOA buffer pH 7 (buffer A), followed by anion exchange chromatography on a quaternary ammonium cross-linked agarose bead column (Q Sepharose High Performance, GE Healthcare) in a linear gradient from buffer A to buffer B (20 mM TEOA pH 7 with 1 M NaCl). The fractions corresponding to the peak containing HiCel45A were then concentrated by ultrafiltration, as described above, while also exchanging into 50 mM sodium acetate buffer pH 5. The glycoside hydrolase family 10 xylanase (GH10Xyn) and family 11 xylanase (GH11Xyn) were purified from T. reesei xylanase preparations (Cellic HTec, Novozymes and Multifect Xylanase, Genencor, respectively). GH10Xyn was purified through desalting and subsequent anion exchange 46 chromatography as described above for HiCel45A. GH11Xyn was purified first by size-exclusion chromatography (HiLoad 16/600 Superdex 75, GE Healthcare) with 20 mM TEOA buffer pH 7, followed by the same anion exchange protocol. For both xylanases, the relevant fractions were collected, concentrated, and buffer exchanged into 50 mM sodium acetate buffer, as described above. The purity of the enzymes following FPLC was confirmed by SDS-PAGE, as well as tandem mass spectrometry as described previously (Pribowo et al., 2012). The commercial enzyme preparations Cellic CTec3, Cellic HTec3, Celluclast 1.5L and Novozym 188 were furthermore used directly without purification as kindly provided by Novozymes. 2.16 Protein concentration The concentration of purified TrCel7A (CBHI) was determined through absorbance at 280 nm measured in a spectrophotometer in a quartz cuvette with 1 cm path length, using a millimolar attenuation coefficient of 84.4 mM-1 cm-1 (Velleste et al., 2010). Concentrations of other purified proteins was determined using a microplate-based bicinchoninic acid assay according to the kit instructions (Pierce BCA Protein Assay Kit; Thermo Fisher Scientific), Protein content of commercial enzyme preparations was determined via a sodium borohydride-coupled ninhydrin-based method (Mok et al., 2015). One hundred microliters of a protein sample was first incubated with 50 μl of NaBH4 for 60 min at a ratio of 1:3 NaBH4 to total sugar (by mass) in a 0.5-ml screw-cap microcentrifuge tube with bovine serum albumin as a protein standard unless otherwise specified. This was followed by the addition of 300 μl of 9 M HCl (final concentration of 6 M HCl) and subsequent heating in a dry heating bath at 130 °C for 2 h. After cooling the reactions to room temperature, 100 μl of the hydrolysate was transferred to a 1.5-ml microcentrifuge tube and neutralized with 100 μl of 5 M NaOH. Upon neutralization, 200 μl of 2 % ninhydrin reagent was added and heated at 100 °C for 10 min. Samples were then cooled to room temperature prior to the addition of 500 μl of 50 % v/v ethanol. Subsequently, 200 μl of the colored solution was transferred to a 96-well microplate and the absorbance was read at 560 nm. All samples were performed in triplicate and experiments were repeated at least twice. 47 2.17 Enzyme activity assays Cellobiohydrolase and β-glucosidase activities were measured in microplate assays using 2.5 mM p-nitrophenyl-β-D-cellobioside (pNPC) and p-nitrophenyl-β-D-glucopyranoside (pNPG) as substrates, respectively, in 100 μl reactions with 50 mM sodium acetate buffer pH 5 at 50 °C. The pNPC assay reactions additionally contained 5 mM gluconolactone in order to inhibit β-glucosidase activity. Enzymes were diluted as necessary and incubated with the substrate on a microplate shaker at 400 rpm. Stop solution (100 μl, 1 M glycine/0.8 M NaOH) was added at 10, 20, and 30 min time points to five replicates each and the color that developed as a result of p-nitrophenol liberation was measured at 405 nm on a microplate spectrophotometer. The amount of liberated p-nitrophenol was calculated against a standard curve of p-nitrophenol dilutions. Endoglucanase and xylanase activities were measured using 0.7 % (by mass) solutions of carboxymethyl cellulose (90 kDa average molecular weight, 0.7 carboxymethyl groups per anhydroglucose unit; Sigma) and birchwood xylan (Sigma) in 100 μl reactions with 50 mM sodium acetate buffer pH 5 on microplates at 50 °C. Appropriately diluted enzyme samples were incubated with substrate for 10, 20, and 30 min (five replicates each) and stopped by addition of a dinitrosalicylic acid (DNS) reagent solution, prepared as previously described (Adney and Baker, 2008). The microplates covered with low-evaporation lids taped at the seams were incubated at 105 °C for 30 minutes to allow reaction of DNS with liberated saccharides, allowed to cool to room temperature, and then the colour produced was measured at 540 nm on a microplate spectrophotometer. A standard curve was prepared with serial dilutions of glucose and xylose treated in the same manner with dinitrosalicylic acid reagent, from which the activity of the enzymes was extrapolated using the measured absorbances. 2.18 SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was performed using 12% acrylamide bis-tris gels (Criterion XT, Bio-Rad) with 3-(N-morpholino)propanesulfonic acid (MOPS pH 6.9; XT, Bio-Rad) running buffer in an electrophoresis cell (Criterion, Bio-Rad) at 60 V for 60 min. Protein samples were incubated at 95 °C for 5 min following addition of sample buffer containing SDS and reducing agent containing tris(2-carboxyethyl)phosphine to break disulfide bonds (XT, Bio-Rad). Stained molecular weight standards were run for reference (Precision Plus 48 Protein Dual Color, Bio-Rad). Following electrophoresis and prior to imaging, gels were stained for at least 1 h with Coomassie brilliant blue R-250 (Bio-Rad), followed by washing with deionized water and at least three rounds of destaining for 30 min with a destaining solution (50 % deionized water, 40 % methanol, 10 % acetic acid, by volume). 2.19 Isoelectric focusing Isoelectric focusing (IEF) was done using pH 3–10 IEF gels (Criterion IEF, Bio-Rad) run at 15 mA in three stages: 1) 150 V, 60 min; 2) 250 V, 60 min; and 3) 500 V, 30 min. Protein samples were prepared with 5% glycerol. The IEF gels were run in an electrophoresis cell with 7 mM phosphoric acid anode buffer and 20 mM lysine/20 mM arginine cathode buffer (Bio-Rad). Following electrophoresis, the gels were fixed with 12 % v/v trichloroacetic acid for 30 min, washed four times with deionized water, and then stained as described above for SDS-PAGE. 2.20 Enzymatic hydrolysis Enzymatic hydrolysis was generally conducted with 50 mM sodium acetate buffer at pH 5, unless otherwise indicated. Small-scale enzymatic hydrolysis was generally conducted in 2-ml O-ring screw-cap centrifuge tubes with a 1-ml reaction volume, rotated in a hybridization incubator at 50 °C. Reactions were stopped by heat-inactivation through incubation at 95 °C for 10 min in a heating block. Medium scale enzymatic hydrolysis was conducted in 40-ml crimp-top serum bottles with a 20-ml reaction volume, similarly rotated in a hybridization incubator. Larger scale enzymatic hydrolysis was conducted in 100-ml screw-cap bottles rotated (STR4, Stuart, Staffordshire, UK) at 10 rpm within an incubator. The medium and larger scale reactions were stopped through heat-inactivation in a water bath at 95 °C for 30 min. For in-rheometer reactions, 20 ml of slurry was loaded into a cylindrical cup in the MCR 502 rheometer (Anton-Paar GmbH, Austria), as described above for the oscillatory rheometry. Temperature control was achieved using a C-PTD 200 Peltier device (Anton-Paar GmbH, Austria) in combination with counter-cooling achieved with an external circulator with water set to 35 °C, together maintaining a temperature of 50 °C. Prior to addition of enzyme, the slurry was warmed up to 50 °C under constant stirring at a shear rate of 60 s-1 for 5 min. The measuring geometry was then raised out of the slurry and the enzyme was added and thoroughly mixed into the slurry with a 49 spatula. The geometry was then immediately lowered back into the slurry and shear initiated. Reactions were run at a constant shear rate of 60 s-1 for one hour, measuring viscosity data points every 10 s. When necessary, a cover made of laboratory film stretched around cardboard with a narrow cutout for the measurement geometry was used to minimize evaporation. A 1-ml sample taken from the slurry upon completion of the reaction was incubated at 95 °C for 5 min to heat-inactive the enzymes and stored at -20 °C until further analysis. Carbohydrates in the hydrolysates were measured using HPAEC-PAD as described above in Section 2.5. When necessary (e.g. following hydrolysis with purified enzymes where large amounts of oligomers were present), oligomers were depolymerised through acid hydrolysis with sulfuric acid (4 % by mass) at 121 °C into monomers prior to HPAEC-PAD (Sluiter et al., 2008). Glucose was additionally measured using a YSI 2700 Select Biochemistry Analyzer (YSI Life Sciences Inc., Yellow Springs, OH) equipped with an immobilized glucose oxidase membrane. With regard to the solids loading at which enzymatic hydrolysis was conducted, in the thesis a ‘low’ solids loading was defined qualitatively as a solids loading at which free interstitial water in the suspension was abundant. It was defined quantitatively as a solids loading at which the yield stress was ≤ 20 Pa. A ‘high’ solids loading was defined qualitatively as a solids loading at which little-to-no free interstitial water remained, leaving an essentially moist solid. The yield stress value at which this occurred was generally > 100 Pa. It is important to note that a ‘high solids’ condition cannot be attributed to a specific solids loading. Rather, it is dependent on a given substrate’s rheological characteristics, as is discussed in more detail in the main body of the thesis. 2.21 Statistical analysis Data was generally presented as the mean ± standard error. For box plots, center lines show the medians; crosses indicate the mean; box limits indicate the 25th and 75th percentiles as determined by R software; and whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles. Multiple linear regression analysis was used to test the correlation between selected parameters using the Data Analysis Add-in in the Excel software. The reported coefficient of determination (R2) describes the proportion of variance in the dependent variable explained by the variance in the independent variables (covariates). 50 Results and Discussion 3 Assessment of the rheological challenge of high-solids enzyme-mediated hydrolysis and the influence of substrate characteristics 3.1 Background High solids loadings are desirable for the bioconversion of lignocellulosic biomass because of the potential for higher volumetric productivity and reduced capital and operating costs (Lye and Woodley, 1999; Modenbach and Nokes, 2013). However, due to several interdependent factors related to the nature of the substrate, mass and heat transfer phenomena, and enzyme kinetics, concentrated enzymatic hydrolysis reactions suffer from reduced reaction efficiencies. In particular, the hygroscopic and fibrous nature of lignocellulosic substrates leads to very high viscosities and low free (non-biomass-associated) water at high solids loadings. This makes its processing and reaction with enzyme catalysts a difficult challenge. The benefits of highly concentrated enzymatic hydrolysis has motivated ongoing work focused on using higher solids loadings in the starch bioconversion industry (Ramirez-Cadavid et al., 2013). High-yield hydrolysis and fermentation of starch at loadings as high as 37 % (m/m) has been reported (Thomas and Ingledew, 1992), as well as loadings of up to 40 % using a continuous liquefaction system (Taylor et al., 2010). While starch is considerably less recalcitrant and heterogeneous and much more enzymatically digestible than lignocellulose, issues around slurry viscosity and mixability similarly arise during the mashing of starch at these high solids loadings (Ingledew et al., 1999). Native starch is generally found in the form of structured granules with alternating amorphous and crystalline regions. It is degraded relatively slowly by enzymes as only the surface of the granules is available to enzymatic attack (Buléon et al., 1998). However, when the granules are heated to temperatures above 90 °C, their structure starts to swell and unravel in a process termed ‘gelatinization’. This increases enzyme accessibility to the starch, increasing hydrolysis rates (Wang and Copeland, 2013). Thus, starch bioconversion processes usually include a gelatinization step, where the starch granules are cooked at 90 °C or higher prior to addition of enzyme. However, swelling and unraveling the starch granules in this manner increases the viscosity of the slurry as much as 20-fold, making it difficult to pump or stir the slurry (Robertson et al., 2006). 51 A liquefaction step therefore is usually implemented, where thermostable a-amylase enzymes are added to cleave starch chains. This reduces the degree of polymerization, reducing the interaction of solubilized chains, and consequently reducing slurry viscosity (Huang et al., 2014; Salemis and Rinaudo, 1984). The use of gelatinization as a way to improve the accessibility of starch toward enzymes is not unlike the use of pretreatment to open up the structure of lignocellulose to enhance the enzymatic hydrolysis of the cellulose component. However, cellulose is not soluble in water, even at higher temperatures, and it is present in a complex matrix of hemicellulose and lignin. Therefore, in order to increase the accessibility of cellulose to enzymes, pretreatments generally try to also enhance defibration/defibrillation of the material into individual fibers and delaminated fibrils, as well as modification, relocation, or removal of lignin (Chandra et al., 2007). However, although pretreatment enables increased enzyme accessibility, the fibers and fibrils separated during pretreatment typically form interconnected networks that resist slurry flow and cause high viscosities (Derakhshandeh et al., 2011). At the same time the increase in substrate porosity increases the hygroscopy of biomass and reduces the amount of free water available at a given solids loading (Weiss et al., 2017). Pretreatment therefore directly impacts the extent to which the fibrous nature and hygroscopy of lignocellulosic biomass influence slurry rheology and how well a given pretreated substrate can be mixed and reacted at high solids loadings. A variety of different pretreatment methods have been developed for lignocellulosic biomass, primarily involving different combinations of chemical, physical, and/or thermal treatments (as covered in Section 1.1.5). As mentioned earlier, the primary goal of pretreatment is to increase enzymatic digestibility, and, accordingly, this is generally the only parameter tested in order to gauge the efficacy of a given pretreatment method. However, enzymatic digestibility is usually tested at low solids loadings and characterization of rheology following pretreatment is rare. Consequently, rheology and high-solids reaction kinetics have not been studied sufficiently. For example, the most highly cited review article in recent years on pretreatment methods for improving enzymatic hydrolysis of lignocellulose does not mention the challenge of high solids loadings in a section dedicated to the factors limiting enzymatic hydrolysis (Alvira et al., 2010). Although another highly cited review article on pretreatment does include a section on the key features by which to assess the efficacy of a pretreatment method, it fails to mention high-solids hydrolysis as a factor (Agbor et al., 2011). It is therefore apparent that little focus has been placed on how pretreatment affects the processibility of substrates at high solids loadings, despite the increased awareness of the need to 52 perform enzymatic hydrolysis at high solids loadings (Koppram et al., 2014; Modenbach and Nokes, 2013), and despite the fact that slurry rheology can have a large impact on determining economic feasibility of bioconversion at high solids loadings (Viamajala et al., 2010). A multitude of different possible substrate characteristics can have an influence in determining slurry rheology and therefore suitability of a substrate to high-solids processing. These include the extent of defibration, defibrillation, the degree of fiber fragmentation, the resulting particle morphologies, the relocation of lignin, and the removal of hemicellulose. Several indications of this substrate-dependency of slurry rheology can be found in the literature in studies that have examined scaling of hydrolysis efficiency with solids loading, with different substrates showing vastly different scaling trends (Kristensen et al., 2009). However, the underlying reasons for these differences have not yet been clearly identified. Of the studies that have examined the rheology of pretreated lignocellulosic biomass slurries, most have been conducted with herbaceous biomass or corn stover. Few have examined woody biomass, which due to its highly fibrous nature, is likely to be more problematic (Wiman et al., 2011). By comparing the enzymatic hydrolysis of steam-pretreated giant reed and spruce in stirred tank bioreactors, Kadić et al. (2014) discovered vast differences in processibility between these two materials. Spruce slurries exhibited much higher viscosities and were much more sensitive to mass transfer limitations compared to giant reed slurries at equivalent solids loadings. Thus, given the ongoing pursuit and potential of woody biomass as a lignocellulosic feedstock (Sannigrahi et al., 2012), especially in Canada (Mabee et al., 2006), further studies into the rheology of woody biomass slurries and its connection to processability at industrially relevant conditions are warranted. In this section of the thesis, the first objective was to assess those substrate properties that most influenced the effectiveness of high-solids enzymatic hydrolysis. A range of woody biomass substrates with distinct characteristics were prepared using a variety of pretreatments based on traditional pulp and paper methods as well as bioconversion-oriented methods, which included combinations of mechanical, thermal, and/or chemical approaches. By selecting subsets from this array of substrates, the influence of the solids loading in determining mass transfer limitations and the mass transfer boundary (Hodge et al., 2008) was examined and tied back to the properties of the substrates. One objective was to determine how a substrate’s physicochemical characteristics affected scaling of yield stress with slurry solids loading. Given the importance of the fibrous nature (and particle dimensions) of lignocellulosic biomass in determining slurry rheology (Cui and Grace, 2007; 53 Kerekes, 2006), the last part of this section of the thesis work closely examined the influence of particle length on slurry rheology behavior and hydrolysis kinetics using a size-fractionated steam-pretreated poplar substrate. 3.2 Preparation and characterization of substrates In order to examine the influence of substrate properties on slurry rheology, a variety of substrates with different compositions and properties were prepared from woody biomass. They varied widely in their cellulose, hemicellulose and lignin content, water retention capacity, and particle dimensions (Table 1). The substrates included traditional mechanical pulps (refiner mechanical pulp, RMP; thermomechanical pulp, TMP), nearly pure cellulose pulps (softwood dissolving pulp, SW-DP; hardwood dissolving pulp, HW-DP; PFI mill-refined hardwood dissolving pulp, R-HW-DP), an organosolv-pretreated poplar pulp (OPP), and various steam-pretreated pulps (steam-pretreated poplar, SPP180, SPP190, SPP200, pretreated at 180, 190, and 200 °C, respectively; and steam-pretreated lodgepole pine, SPLPP). Table 1. Composition, water retention and morphological properties of the range of substrates used in this section, prepared using a variety of pulping and pretreatment methods. Substrate Composition (% dry matter)a WRVb (g g-1) Particle lengthc ( μm) Aspect ratiod Glu Lignin Xyl Man Ara Gal RMP 42 32 13 2.3 3.7 4.0 2.02 548 22.5 TMP 47 23 12 2.2 3.5 3.3 2.18 769 34.5 OPP 78 19 4.5 2.2 0.0 0.0 2.27 522 23.1 SW-DP 87 0.0 1.5 1.7 0.1 0.2 1.26 1883 75.3 HW-DP 93 0.0 5.0 0.8 0.0 0.0 1.76 551 36.3 R-HW-DP 93 0.0 5.0 0.8 0.0 0.0 2.51 884 34.4 SPP180 60 30 6.6 1.3 0.3 0.8 1.59 1093 45.4 SPP190 57 32 6.0 1.9 0.1 0.1 2.09 622 26.8 SPP200 59 34 2.2 1.4 0.0 0.0 2.02 505 22.2 SPLPP 52 45 0.0 1.1 0.2 1.8 2.03 405 13.7 aAbbreviations: glucan, xylan, mannan, arabinan, galactan; bwater retention value; cnumber-based length-weighted mean; dcalculated through division of the number-based length-weighted mean by the mean width 54 Since the low bulk density and high hygroscopy of lignocellulosic substrates (and the resulting entrapment of water) presents a major challenge in the handling of biomass at high solids loadings, a method to quantify such interactions of water with the substrates with water was needed. The water retention value (WRV) test, a traditional pulp and paper method involving saturation of biomass fibers in water followed by centrifugation of excess water to determine substrate-associated water (TAPPI, 2011), has been used as a measurement for biomass absorbency/hygroscopy (Xiao and Meshitsuka, 2001) and was used in the current work for this purpose. For comparison of particle dimensions, apart from mean particle lengths, the mean aspect ratios were determined (Table 1). These were obtained through division of the mean lengths and mean widths measured with an optical analyzer (Fiber Quality Analyzer). Together, these measurements were used as representative parameters for the hygroscopy and fibrous nature of biomass. 3.3 The importance of enzymatic liquefaction in overcoming mass transfer limitations The challenge of high-solids enzymatic hydrolysis of lignocellulose and the factors influencing it were first examined using a steam-pretreated poplar substrate (SPP200). The challenge of high solids loadings primarily manifests as a reduction in conversion yield with increasing solids loading. This phenomenon has been termed the “solids effect” (Kristensen et al., 2009). Various causal mechanisms have been suggested for this effect, including mass transfer limitations (Lavenson et al., 2012). The influence of this effect was confirmed for the hydrolysis of SPP200 with a T. reesei enzyme preparation (Fig. 2A). However, the reduction of hydrolysis yield was not severe enough to reach negative returns in hydrolysate glucose concentrations with increasing solids loading over the tested range (Fig. 2B). 55 Figure 2. The influence of solids loading on hydrolysis kinetics of steam-pretreated poplar (SPP200) with regard to hydrolysis extent (A) and hydrolysate glucose concentration (B). The first data point for each solids loading, indicated by surrounding orange box, indicates visual point of liquefaction and the first point at which hydrolysate could be sampled. The T. reesei enzyme cocktail (CTec3) was loaded at 30 mgprotein gglucan-1. Apart from reductions in hydrolysis yields, the point at which the SPP200 slurries were visibly liquefied (corresponding to the first time the hydrolysate could be sampled and therefore the first data point of each curve) was increasingly delayed with increasing solids loading (Fig. 2). This time-to-liquefaction was plotted and a power-law relationship with solids loading was apparent (Fig. 3A). This was similar to the power-law relationship that has been observed for biomass slurry yield stress scaling with solids loading (Nguyen et al., 2015). The yield stress power-law relationship was also confirmed with SPP200 (Fig. 3B), modeled according to the equation τy = aCmb , where Cm is the consistency (solids loadings) expressed as a fraction, and where a and b are constants for a specific material, sensitive to the material’s properties (Bennington et al., 1990). To illustrate the increasingly challenging slurry conditions in which to conduct enzymatic hydrolysis with increasing solids loadings, a series of slurries were prepared at different solids loadings (Fig. 3C). No free water was apparent at a solids loading as low as ~8 %, with the slurry becoming essentially a wet granular material at this solids loading (Fig. 3C). Ostensibly, given that water needs to serve as both a dispersal medium and reactant for enzymatic hydrolysis, performing bioconversion under these conditions of low free water is a considerable challenge. 607080901000 30 60 90Hydrolysis extent (%)Time (h)A50751001251500 30 60 90Glucose concentration (g l-1 )Time (h)B12.5 % 15.0 % 17.5 % 20.0 % 22.5 % 22.5 % 20.0 % 17.5 % 15.0 % 12.5 % Solids loading Solids loading 56 Figure 3. Increasing time required for liquefaction (A) and increasing yield stress (B) at increasing steam-pretreated poplar (SPP200) solids loadings. (A′) Time-to-liquefaction on a log–log scale showing power-law relationship with solids loading. (C) Series of SPP200 slurries with increasing solids loadings (as labeled) demonstrating the decreasing level of free water in the slurry. The observation that the time required for liquefaction increases in a power-law fashion with solids loadings has important implications with regard to bioconversion reactions carried out at an industrial scale. The time required to obtain the targeted yield in a catalytic process, or the time-to-target, is an important factor in determining the economics of an industrial process such as bioconversion (Brunecky et al., 2014; Himmel et al., 2017). Delayed liquefaction results in an extended period of high slurry viscosity/yield stress, requiring increased mixing power demand and worsening mass transfer limitations. Furthermore, simultaneous saccharification and fermentation (SSF), where hydrolysis and fermentation are conducted simultaneously, minimizing end-product 02040608010 12.5 15 17.5 20 22.5Time-to-liquefaction (h)Solids loading (%)A11010010001 10Yield stress (Pa)Solids loading (%)B2.5 % 5 % 6.25 % 7.5 % 8.25 % 10 % 12.5 % C 55010 100A′ τy = 1.2 × 106 𝐶𝑚2.9 57 inhibition, would be limited in its applicability and efficacy by poor liquefaction. This is because efficient mixing is important for the productivity of the fermenting microorganism (Hoyer et al., 2009). Overall, the remarkably nonlinear scaling of the time required for liquefaction confirmed the hypothesis that the lack of efficient liquefaction is central to the challenge of conducting bioconversion at high solids loadings. 3.4 The influence of mass transfer on enzymatic hydrolysis Efficient mass transfer is known to be important for enzymatic hydrolysis reactions at an industrial scale (Viamajala et al., 2010) and has been found to affect both general depolymerization of bulk cellulose (saccharification), and reduction of slurry viscosity (liquefaction) (Lavenson et al., 2012). The experiments detailed in the next section tried to identify the driving factors behind mass transfer limitations at high solids hydrolysis. The influence of reaction mixing mode was first investigated. Biotechnological laboratory experiments tend to be performed in shake flasks because of their simplicity, despite the fact that shake flasks often do not adequately represent industrial conditions. Translating findings at lab-scale to industrial-scale operations can therefore be challenging (Freyer et al., 2004). For example, shake flasks have previously been shown to promote poor mixing at high biomass loadings and result in low enzymatic hydrolysis yields in comparison to horizontally mixed systems that are often used at an industrial scale (Roche et al., 2009b). As summarized earlier, horizontal mixing systems (so called because of the orientation of the mixing axis) have been shown to handle high-solids reactions well, have low energy consumption, scale up to industrial volumes, and have been adopted in the pioneering commercial biorefining plants (Jørgensen et al., 2007). As expected, during the enzymatic hydrolysis of the model cellulosic substrate HW-DP, horizontally mixed reactions performed better than shaking flasks, despite only being rotated at a rate of 10 rpm compared to the 200 rpm rate required to promote movement in the slurry for the shaking flasks (Fig. 4). It also appeared that liquefaction occurred later in the shake flasks, as indicated by the first data point (that being the first time that a liquid sample could be taken for analysis). This was especially apparent at 20 % solids, where liquefaction did not occur until approximately 100 h into the reaction, at which point the hydrolysis extent was only 55 %, compared to 67 % for the horizontally rotated reactions. Similar behaviour was observed with the SPP200 substrate using one-time-point reactions to confirm the 58 influence of mixing modes (data not shown). Thus, horizontal mixing was used for all further reactions described in the thesis. Figure 4. Influence of the mixing method on high-solids enzymatic hydrolysis of hardwood dissolving pulp, examined with reactions in shaking flasks (200 rpm; dashed lines) and during horizontal rotation (10 rpm; solid lines) with 30 mgprotein gglucan-1 enzyme. The ability of horizontal mixers to promote increased hydrolysis efficiency and more rapid liquefaction at high solids loadings is influenced by the nature of the flow properties of concentrated lignocellulosic materials. With an increase in solids loading, lignocellulosic materials become increasingly granular in nature, whereby the flow properties become more influenced by direct particle–particle interactions (Brennen, 2005). At a sufficiently high solids loading, when there is little-to-no free water in the medium, an essentially wet solid remains, therefore initially requiring more of a solid–solid mode of mixing rather than solid–liquid mixing. For this approach, horizontal mixers are better suited, since they enable ‘folding’ of the material through a free-fall mode of mixing, achieving disruption of the interconnected fibrous mass. Considering the conditions required for the material to be carried up inside the reactor followed by deposition due to gravity, it can be anticipated that the higher the crowding number and yield stress of the lignocellulosic material, the more amenable it will be to horizontal mixing. This was evident in the observed greater relative difference in hydrolysis and liquefaction efficiency between horizontal mixing and shake flasks at a solids loading of 20 %, as compared to the difference at a solids loading of 15 % (Fig. 4). At a 20 % solids loading, stress transfer within the slurry in shake flasks was particularly poor. This resulted in the 2550751000 50 100 150 200Hydrolysis extent (%)Time (h)Horizontal 15%Shaking 15%Horizontal 20%Shaking 20% 59 slurry moving as one continuous mass until the material had liquefied sufficiently to allow stress transfer through orbital mixing. These results underline the fact that, to achieve efficient mass transfer during high-solids enzymatic hydrolysis, the granular flow properties that predominate in the early stages of the reaction can be improved through mixing methods that are geared toward solid–solid mixing such as horizontal mixing. Apart from an insoluble solids fraction, thermochemical pretreatments such as steam pretreatment also produce a liquid fraction that is enriched in hemicellulose-derived sugars. While the liquid fraction can be treated separately in order to avoid inhibition by these soluble components and to focus on enzyme–substrate interactions, its inclusion in hydrolysis reactions is essential as part of a ‘whole slurry’ approach for maximizing product yields (Cheng et al., 2015). Following detoxification treatments that reduce the inhibitory effects of the soluble components on the enzymes and microorganisms (Jönsson et al., 2013), the hemicellulosic sugar-rich liquid fraction could be included with the solid fraction, effectively reducing the insoluble solids content while maintaining a high soluble sugar content. Doing so could reduce slurry viscosity and lessen mass transfer limitations without sacrificing volumetric productivity. Using compositional analysis of the liquid fraction of the steam-pretreated substrate SPP200 (Table 2), a total soluble carbohydrate content of 78 g l-1 was determined. Given that the insoluble solids content following pretreatment was found to be about 65 % by weight (35 % liquid fraction), a large amount of carbohydrates was evidently diverted to the liquid fraction, which could be retained using a whole slurry approach. In order to avoid the influence of soluble inhibitory compounds (such as phenolics, acetic acid, furfural, and hydroxymethylfurfural; Table 2) and allow a focus on the solids effect, the liquid fraction was reconstituted using monomeric carbohydrates according to the total carbohydrate composition of the liquid fraction. Note that this assumes that the soluble oligomeric carbohydrates present would be fully hydrolyzed by the enzyme cocktail used in the process to be available for the microorganism used in the bioconversion process. For the xylo-oligomers typically associated with hardwood substrates, this appears to be a reasonable assumption, as evidenced by previous work (Hu et al., 2016). Hydrolysis of SPP200 was conducted at 20 % solids, 15 % solids, and at 15 % solids including the reconstituted liquid fraction (15 % + LF) (Fig. 5). The amount of reconstituted liquid fraction added corresponded to the theoretical soluble carbohydrate yield lost due to the 5 % difference in insoluble solids loading. Thus, the total theoretical yield of soluble carbohydrates was equivalent between the 20 % solids reaction and the 15 % + LF treatment. 60 Table 2. Composition of the pretreatment liquid fraction of steam-pretreated poplar (SPP200). Soluble carbohydrates (g l-1) Other (g l-1) Carbohydrate Glu Xyl Man Ara Gal Phenolics Acetic acid Furfural HMFa Monomeric 9.7 38 5.4 0.8 2.6 10.5 13.5 1.2 1.1 Totalb 14 51 8.7 1.1 3.1 ahydroxymethylfurfural; bfollowing acid hydrolysis to depolymerize oligomeric carbohydrates Comparing the extent of hydrolysis, the differences between the 15 and 20 % solids reactions seemed to reflect the solids effect, with liquefaction of the 20 % solids reaction occurring at about 41 h compared to 22 h for the 15 % solids reaction (Fig. 5A). This was also observed earlier (Fig. 3). The initial spiking of soluble monomeric carbohydrates from the reconstituted liquid fraction reduced the hydrolysis rate and extent of the 15 % + LF reaction, likely due to product inhibition of the enzymes (Hsieh et al., 2014). Nonetheless, full liquefaction was achieved only slightly later than the reactions at 15 % solids alone. At the same time, a much higher concentration of monomeric sugars was achieved than either the 15 % (1.4-fold higher) or 20 % solids (1.15-fold higher) reactions (Fig. 5B). While product inhibition had a measurable effect, these results showed the clear influence that mass transfer limitations as a result of poor liquefaction have at high solids loadings. Through partial displacement of insoluble solids with the soluble fraction equivalent, the time required for enzymatic liquefaction was greatly reduced and therefore hydrolysis yields increased. These results provided further support for liquefaction (and its effect on slurry flow conditions) being the critical factor that determines high-solids hydrolysis kinetics. The findings also illustrate a potential method to at least partly mitigate this challenge through inclusion of the pretreatment liquid fraction, especially when SSF is used to eliminate product inhibition. 61 Figure 5. Enzymatic digestion of steam-pretreated poplar (SPP200) at 20 % solids, 15 % solids, and 15 % solids plus reconstituted pretreatment liquid fraction (LF) with a T. reesei enzyme cocktail (CTec3) at 30 mgprotein mgglucan-1 showing hydrolysis extent (A) and monomeric carbohydrate concentration (B). Given the apparent influence of mass transfer in high solids hydrolysis kinetics, we next tried to better understand how the hygroscopy of different substrates might influence substrate–water interactions and mass transfer limitations. Previously, Hodge et al. (2008) had observed an apparent mass transfer boundary with pretreated corn stover, a solids loading beyond which the enzymatic hydrolysis was mass transfer-limited and sharp reductions in hydrolysis yields were observed. To assess if this proposed mass transfer boundary occurs with other substrates and if substrate characteristics influence at which solids loading the boundary occurs, three different dissolving pulps were used (SW-DP, HW-DP, and R-HW-DP). These were chosen because of their nearly pure cellulose content, which should minimise the additional variables of lignin and hemicellulose in determining substrate–water interactions. All three substrates also had distinctly different water retention capacities (1.26, 1.76, 2.51, respectively; Table 1), allowing for a comparison of the influence of their differences in hygroscopy on slurry dynamics. Similar to the observations of Hodge et al. (2008), following near-linear increases in the glucose concentration with increasing solids loading, a mass transfer-limited region was reached where negative returns occurred with increased solids loading (Fig. 6A). This was also reflected in the extent of hydrolysis (Fig. 6B) where, following an initial apparent linear reduction with increased solids loading (shown with the shaded linear fits), a more rapid reduction occurred. This was most noticeable for the R-HW-DP substrate. Examining the solids loading at which the relationship of 506070809010012 24 36 48Hydrolysis extent (%)Time (h)A15%15% + LF20%025507510012515012 24 36 48Monomeric carbohydrates (g l-1 )Time (h)B 62 hydrolysis extent with solids loading started to deviate from linear behaviour, there seemed to be strong correlation between the onset of the mass transfer boundary and the hygroscopy of the substrate (Fig. 6C), at least within the parameters of this controlled experimental setup. Figure 6. Examination of the mixing-associated mass transfer boundary during the enzymatic hydrolysis of softwood dissolving pulp (SW-DP), hardwood dissolving pulp (HW-DP), and refined hardwood dissolving pulp (R-HW-DP) at increasing solids loadings following extended hydrolysis (7 days) at 20 mgCTec3 gcellulose-1, horizontally mixed at 10 rpm. (A) Hydrolysate glucose concentrations. (B) Hydrolysis extent expressed as percent of theoretical yield of glucose. The initial apparent linear relationship between solids loading and conversion extent prior to the mass transfer boundary is indicated. (C) Correlation of the solids loading (SL) at which the mass transfer boundary occurs and the hygroscopy of the substrate (represented by water retention capacity). The mixing-associated mass transfer boundary therefore appears to be determined by a substrate’s hygroscopy: the more water the substrate is able to absorb and entrap, the less free water is available between the biomass particles, and the more limited mass transfer becomes. It can be posited then that at a certain point, the amount of free water becomes sufficiently limiting that hydrolysis yields drop precipitously. The SW-DP substrate, having the lowest water retention capacity, had the least pronounced drop in conversion extent at the mass transfer boundary, but also had the lowest glucose yields, perhaps precisely because of being less accessible for the enzyme due to poor substrate–water interactions and low water availability (Selig et al., 2012). However, SW-DP was able to eventually outperform HW-DP at 30 % solids (Fig. 6A and 6B), perhaps due to reaching its mass transfer boundary at a higher solids loading than HW-DP. Comparing HW-DP and R-HW-DP, 0501001502002500 10 20 30Glucose concentration (g l-1 )Solids loading (%)AR-HW-DPHW-DPSW-DP4060801000 10 20 30Hydrolysis extent (%)Solids loading (%)BR-HW-DPHW-DPSW-DP10152025301 1.5 2 2.5SL at mass transfer boundary (%)Water retention capacity (g g-1)C 63 the latter being a mildly refined version of the former, the increased accessibility and water retention capacity following refining is clearly reflected in the improved glucose yields/conversion extents, as well as their measured WRV. Because of the 1.4-fold increase in WRV however, R-HW-DP more quickly reaches its mass transfer boundary, occurring at ~15 % as opposed to ~20 % for HW-DP. While refining aids hydrolysis through improving accessibility to enzymes (Jones et al., 2014), the increased substrate hygroscopy afforded by the treatment appears to make high solids hydrolysis more challenging through reduced mass transfer. These results demonstrated that the hygroscopic nature of lignocellulosic materials was a key determinant of high-solids hydrolysis kinetics and that this property was highly sensitive to the substrate’s treatment history. Substrates with low hygroscopy therefore seem to be favorable from a rheological point of view. However, water retention capacity also reflects a substrate’s accessibility to enzymes and has been shown to correlate to enzymatic digestibility (Jones et al., 2014; Luo and Zhu, 2011). Substrate hygroscopy consequently has an important role in determining slurry rheology, while at the same time being intertwined with enzymatic digestibility. This conjunction of determining both rheological character and enzymatic digestibility (in an inversely proportional manner in terms of processability) will likely preclude hygroscopy from being a target for the tuning of lignocellulosic substrates toward mitigating rheological issues. An intermediate compromise will be required; while a highly hygroscopic substrate may be highly digestible at low solids loadings, its processing at higher solids loadings will become difficult and the benefits of its accessible, hygroscopic nature will be negated and possibly overshadowed by the resulting rheological challenges. Regarding the relationship between a substrate’s hygroscopy and its mass transfer boundary, it is interesting to note that a similar linear correlation was found between the water retention capacity of these dissolving pulp substrates and their scaling of yield stress with solids loading in later experiments (Fig. 8A), as is discussed below during the closer examination of the relationship between substrate characteristics and slurry rheology. 3.5 Substrate properties affecting biomass slurry rheology Slurry rheology is of great importance to the processability of biomass substrates at industrial scale (Knutsen and Liberatore, 2009). Characterizing the rheology of slurries allows prediction of mass transfer limitations (Wang, 2013), and therefore enables indication of how well a given substrate 64 can be processed at high solids loadings. However, as discussed earlier, rheological studies of biomass slurries with respect to application in enzymatic bioconversion have been primarily restricted to herbaceous biomass and corn stover; few have examined woody biomass. Moreover, little is known about the influence of different pretreatments and resulting substrate properties on slurry rheology. Having examined the influence of mass transfer during enzymatic hydrolysis in the work reported above, the next objective therefore was to examine the rheology of substrates with different treatment histories and properties, focusing on woody biomass. aPower-law regression fit of yield stress plotted against the consistency, Cm, expressed as a fraction, in the form of τy = 𝑎𝐶,8 as described by Bennington et al. (1990). Substrate Power-law correlationa RMP τy = 4.2 × 106 𝐶,9.9 r2 = 0.960 TMP τy = 1.4 × 107 𝐶,9.; r2 = 0.938 OPP τy = 1.7 × 106 𝐶,9.< r2 = 0.913 SW-DP τy = 1.4 × 105 𝐶,=.< r2 = 0.986 HW-DP τy = 1.2 × 106 𝐶,=.> r2 = 0.998 R-HW-DP τy = 3.1 × 106 𝐶,9.= r2 = 0.988 SPP180 τy = 3.0 × 107 𝐶,?.9 r2 = 0.987 SPP190 τy = 4.4 × 107 𝐶,?.? r2 = 0.994 SPP200 τy = 1.5 × 108 𝐶,@.9 r2 = 0.918 SPLPP τy = 4.1 × 108 𝐶,;.; r2 = 0.975 Figure 7. Yield stress scaling with solids loading and power-law fits of a variety of woody substrates on a log–log plot. Yield stresses were determined using the controlled deformation method. To address the shortcomings in the literature with regard to the influence of treatment history on biomass slurry rheology, rheometry was performed on the range of woody substrates described earlier (Table 1). Focus was placed on their yield stress, given the industrial significance of this parameter (Derakhshandeh et al., 2010). Through yield stress measurements of these substrates slurried at a range of solids loadings, it became clear that substrates with different species origins and treatment histories have remarkably different rheological profiles (Fig. 7). It should be noted that it 16 1010010002 4 8Yield stress (Pa)Solids loading (%)103 102 101 65 was not possible to study solids loadings higher than those studied here due to the torque limits of the rotational viscometer used, but the range captured is nonetheless meaningful in showing the onset of yield stress, which is a key determinant of the rheological challenge of biomass processing. As might be expected with regard to the influence of particle length on network formation in suspension (Powell, 1991; Schmid et al., 2000; Switzer and Klingenberg, 2003), the substrate with the longest particle lengths (SW-DP) registered yield stresses at the lowest solids loadings, already reaching a yield stress of around 105 Pa at 2.5 % solids. An equivalent yield stress was not reached until around 10 % solids for the substrate with the shortest particle lengths (SPLPP), which did not register a measurable yield stress until 7.5 % solids. Further distinction of the other substrates’ yield stress profiles according to particle length seems to however be muddled by the influence of other substrate factors, which are difficult to tease out individually. This would require in-depth analysis with well-controlled substrate treatment that could specifically isolate their influence on slurry rheology. Such efforts are reported in Section 3.6. Curiously, the SPP180 and SPP190 substrates have nearly identical yield stress profiles, despite having distinct substrate properties (Table 1). The reasons for this are unclear, but indicate the complexity of factors determining slurry rheology. The SPP200 substrate on the other hand, being the most severely pretreated of the three SPP substrates, showed greatly reduced yield stress, registering an approximately four-fold lower yield stress at 5 % solids than SPP180 and SPP190. Compared to the other substrates, it is also clear that steam-pretreatment is beneficial with regard to reducing yield stress, with all steam-pretreated substrates registering lower yield stress values than all other tested substrates. This is consistent with a study that examined the differences between a thermochemically pretreated corn stover substrate and a mechanically pretreated substrate that showed considerably lower yield stresses for the former (Dibble et al., 2011). The RMP, TMP, OPP, HW-DP, and R-HW-DP substrates were relatively clustered together in comparison to their differences with the steam-pretreated substrates. The TMP substrate deviated slightly through faster yield stress scaling, while the SW-DP substrate deviated considerably in its behaviour from the other traditional pulps, perhaps because of its high aspect ratio, as noted above. The comparable yield stress values of RMP, TMP, OPP, HW-DP, and R-HW-DP, despite their considerable differences in substrate composition, WRV, and particle dimensions (Table 1), again shows the complexity of the substrate properties influencing rheological behaviour. 66 For further examination of general rheological differences among the substrates, the yield stress profiles were fitted to the two-parameter power law defined earlier (τy = a𝐶,8 ) and the corresponding correlations determined (Fig. 7), where a and b are parameters that are sensitive to the substrate type and treatment history. The power law exponent b describes the proportionality of yield stress with solids loading, with an approximate third power proportionality noted to be the consensus for wood pulp suspensions (Kerekes, 2006). Values around this mark were obtained in the current study for the traditional pulps (e.g. RMP, TMP, OPP, dissolving pulps) and align with those cited for comparable pulps in the literature. Bennington et al. (1990) for example observed a value for b of 3.56 for the thermomechanical pulp in their study, in comparison to a value of 3.6 observed for the thermomechanical pulp used here. It appears however that for steam-pretreated substrates, the proportionality of yield stress to solids loading increases sharply, rising from a value of b = 4.3 for the least severely pretreated SPP180 up to a value of b = 6.6 for the most severely steam-pretreated substrate SPLPP. This is comparable to the b value of 5–7 reported for dilute acid-pretreated spruce (Wiman et al., 2011). It can be posited that due to particle fragmentation during steam pretreatment, equivalent fiber network formation of these substrates requires higher solids loadings (as shown by a shift to the right in the yield stress profiles in Fig. 6), but once the fiber network takes shape, yield stress rises sharply. This might be due to increased interparticle interactions arising from physical disruptions such as defibrillation caused by the rapid decompression at the end of the steam pretreatment (Chornet and Overend, 1991). Values for the power law exponent b have also been determined for Miscanthus × giganteus, a grass hybrid grown as an energy crop, with values reported between 10 to 12 (Botto et al., 2014). These values are significantly higher than those reported for woody substrates, as well as corn stover, where values range between 4 to 6 (Lavenson et al., 2011). The high b parameter values for Miscanthus were attributed by the authors to the strong mechanical properties of the fibres. Additionally, the Miscanthus biomass was only mechanically ground and no thermochemical pretreatment was performed, perhaps explaining its much higher power law exponent. Botto et al. (2014) were not able to detect a yield stress until relatively high solid loadings (11 %), which reflects the behaviour of SPLPP determined here, with a yield stress not being detectable until 7.5 % solids and having the highest power law exponent of the woody substrates studied. 67 Figure 8. Correlation of yield stress at 7.5 % solids with particle aspect ratio (A) and correlation of the solid loading (SL) at which the yield stress is 100 Pa with particle aspect ratio (B). It has been noted for wood pulps that fiber length has a strong positive influence on the a parameter (Dalpke and Kerekes, 2004), although no such relationship was found here. The steam-pretreated substrates had the highest a values while having some of the shortest mean fiber lengths (Table 1). Fiber aspect ratio, despite its anticipated importance in determining slurry rheology due to its influence on fiber network formation, furthermore seemed to only weakly predict slurry yield stress when compared at equivalent solids loadings (Fig. 8A). Although a lack of correlation can likely at least partly be attributed to the underlying complexity of the particle size distribution not being well-represented by a population mean (Wiman et al., 2011), it also points to the importance of other factors in determining the rheological behaviour of lignocellulosic slurries beyond particle aspect ratio. Notably, there appeared to be a moderate correlation between the aspect ratio and the solids loading at which the yield stress was 100 Pa (chosen because of being the lowest yield stress value that lies within the experimental yield stress curves of all substrates) (Fig. 8B). Such a relationship might be expected, given the importance of fiber length in determining particle interactions and formation of fiber networks (Schmid et al., 2000). Thus, the longer the particles, the higher the crowding number at a given solids loading, and the earlier an apparent yield stress is expected to be detectable. Given that the hygroscopic nature of biomass is one of the underlying factors in the rheological challenge of high solids loadings, the yield stress profile data was next examined with regard to how a given substrate’s hygroscopy influences slurry rheology. It was hypothesized here that hygroscopy, being the tendency for a substrate to take on water, might affect the scaling of yield stress SPLPPSPP200SPP190SPP180OPPTMPRMPHW-DPR-HW-DPSW-DPR² = 0.41210100100010 100τ yat 7.5% solids (Pa)Aspect ratioAR² = 0.57711010 100SL at τy = 100 Pa (%)Aspect ratioB 68 with solids loading. Thus, a more hygroscopic substrate might more rapidly approach a high-solids rheology regime and see greater increases of yield stress per unit increase of solids loading. By analyzing substrate hygroscopy through a measure of water retention capacity as outlined earlier in Section 3.2, the hypothesized relationship between hygroscopy and yield stress scaling was evident, albeit independently among two different substrate classes: wood pulps (Fig. 9A) and steam-pretreated substrates (Fig. 9B). This was likely due to the significant changes occurring during the high-temperature steam pretreatment, such as depolymerisation and repolymerisation reactions and the resulting rearrangement of lignin (Li et al., 2007) and physical alteration. These changes significantly alter the substrate–water interactions, such that the water retention test is not able to provide an accurate comparison of hygroscopy across regular wood pulps and steam-pretreated substrates, but does among substrates of the same type. All considered, the correlations found here between hygroscopy and yield stress scaling, as well as the correlations discovered earlier between hygroscopy and the apparent mass transfer boundary, provide evidence for hygroscopy being an important substrate property affecting slurry rheology. A recent study likewise showed with wheat straw that increased water absorption causes increased slurry viscosity (Battista et al., 2018). Figure 9. Correlation of substrate hygroscopy with yield stress scaling. The slope of slurry yield stress over solids loading obtained from a linear regression following logarithmic transformation of yield stress as plotted in Fig. 1 (termed the “τy scaling factor”) was plotted against the substrate’s water retention capacity (used here as a measure of hygroscopy) of (A) wood pulps and (B) steam-pretreated wood substrates. OPPR-HW-DPSW-DPHW-DPTMPRMPR² = 0.9440.200.250.301 1.5 2 2.5 3τ yscaling factorWater retention capacityASPP200SPP190SPP180SPLPPR² = 0.8040.250.300.351.5 1.7 1.9 2.1 2.3τ yscaling factorWater retention capacityB 69 Beyond the direct implications of the variation in yield stress profiles shown earlier with regard to how easily the substrates can be mixed, these results further illustrate the ambiguity of the “high solids” concept. While some substrates do not register a measurable yield stress until higher solids loadings are reached (e.g. SPLPP with a yield stress of 16 Pa at 7.5 % solids), others reach considerable yield stresses at much lower solids loadings (e.g. SW-DP with a yield stress of 107 Pa at 2.5 % solids). Thus, the point at which a high-solids regime is reached for a given substrate appears to depend on its morphological and physicochemical features affecting bulk density, hygroscopy, and fiber network formation. “High solids”, especially with respect to rheological regimes, therefore needs to be considered a relative term specific to each substrate and does not refer to a specific solids loading that is universal to all substrates. It is this rheological conceptualization of the term “high solids” that is used throughout this thesis. 3.6 Examination of the influence of particle length on slurry rheology While theory (Powell, 1991; Schmid et al., 2000; Switzer and Klingenberg, 2003) and experimental work (Lapierre et al., 2006; Lapierre et al., 2009) has suggested that particle length (or aspect ratio) is central in determining slurry rheology behaviour, the results in the previous section were more ambiguous. While the substrates with the shortest and longest mean particle lengths had the lowest and highest apparent yield stresses respectively, the relationship between aspect ratio and yield stress for the substrates between these extremes was not clear-cut. Perhaps this result is not surprising, given that it has previously been shown that the method by which particles are fragmented affects whether yield stress is reduced (Dibble et al., 2011). These authors found that mechanical size reduction of corn stover did not reduce yield stress when performed over a range similar to the particle size reductions achieved during thermochemical pretreatment (from 1 mm to 0.1 mm), instead suggesting that other changes to the substrate, namely substrate surface changes affecting interparticle interactions, were responsible for yield stress reductions following thermochemical pretreatment. However, the mechanical knife milling treatment used by Dibble et al. could potentially have roughened the surface of the particles, increasing the yield stress, which was balanced out by the concurrent reduction in yield stress due to reduced particle lengths. Furthermore, the experimental studies that have shown an increase in viscosity with increasing particle length (Lapierre et al., 2006; Lapierre et al., 2009) are misleading, given that these studies measured kinematic viscosity, also called intrinsic viscosity. Kinematic viscosity is the resistance of flow against the force of gravity in the absence of an external force, and its measurement requires dissolution of the pulp at a solids loading 70 of 0.5 % (w/v) in cupriethylenediamine. Hence, kinematic viscosity is not directly comparable to the dynamic viscosity that is of interest in reaction mixing. Due to the dissolution of the pulp in solvent and a lack of dynamic movement during the kinematic measurement, any influence of fiber surface characteristics is lost and therefore not representative of dynamic viscosity or yield stress values measured at high solids loadings. Similarly, rheological parameters have been shown to correlate with particle length using pure cellulose preparations (Tatsumi et al., 2002), but such pure celluloses likewise do not reflect the complexity of lignocellulose particle slurries. Figure 10. Light microscopy pictures of size-fractionated steam pretreated poplar (SPP200) showing the nature of fiber network formation of R-28 (A), R-48 (B), R-100 (C) and R-200 (D). Pictures captured using 0.5 % (m/m) solutions dried onto glass microscope slides. R-14 is not pictured due to the particles being too large to observe under the microscope. Scale bars indicate 500 μm. In order to be able to properly test the influence of fiber length on slurry rheology and hydrolysis kinetics while avoiding modification of interparticle interactions, aqueous particle fractionation using a BauerMcNett classifier was performed on the steam-pretreated poplar substrate SPP200. This technique allows separation of particles based on their length during agitated flow in water through compartments with dividers of decreasing mesh size, resulting in particle populations (Fig. 10) with distinct particle size distributions (Fig. 11) named according to the mesh size by which they were retained: R-14, R-28, R-48, R-100, and R-200. A B D C 71 Figure 11. Particle length probability distributions of size-fractionated steam-pretreated poplar (SPP200), showing the probability density functions (A) and cumulative distribution functions (B). Length-weighted means are noted. The R-14 particles were too large to allow analysis with the optical fiber analyzer. First, to examine the influence of particle lengths on high-solids hydrolysis, the SPP200 fractions were subjected to enzymatic hydrolysis at 15 % solids (Fig. 12). Hydrolysis yields increased with decreasing particle length, suggesting that reduced particle length aided high-solids hydrolysis (Fig. 12A). Control reactions at a low solids loading (1 %) meanwhile showed identical digestibility for all substrates compared to the unfractionated SPP200, apart from R-14, having approximately 1.5-fold lower hydrolysis yields following 72 h hydrolysis (data not shown). The R-14 fraction consisted of very large particles that were likely not well pretreated and not well defibrated (and therefore could not be analyzed by the particle size analyzer or analyzed under the microscope), resulting in low enzymatic digestibility. Del Rio et al. (2012) similarly found no influence of particle length during low solids hydrolysis of size-fractionated organosolv-pretreated lodgepole pine samples using the same size fractionation technique used here. A caveat that should be noted however is that the different fractions of the poplar substrate (a hardwood, compared to the softwood used by Del Rio et al.) likely differ in their relative abundance of cell types (such as fibers and vessel elements), which in turn may differ in their enzymatic digestibility. Nonetheless, the difference in hydrolysis yields observed between low solids (1 %) and high solids (15 %) reactions is notable and indicates an influence of particle length on mass transfer and the ease of hydrolysis at high solids loadings. It is also worth noting that the longer fractions saw more rapid reductions in particle length over the same time span 0481216200 0.5 1 1.5 2 2.5Frequency (%)Particle length (mm)AR-28R-48R-100R-20002550751000 0.5 1 1.5 2 2.5Frequency (%)Particle length (mm)BR-28R-48R-100R-200Mean 290 μm 608 μm 951 μm 1420 μm 72 in comparison to the shorter particle fractions (Fig. 12B), something which has been observed previously with pure cellulose (Peters et al., 1991). This may be explained by the lower mechanical force required to break longer particles following weakening of cell walls by enzymatic hydrolysis (Thygesen et al., 2014). Figure 12. High-solids enzymatic hydrolysis of size-fractionated steam-pretreated poplar (SPP200) at 50 °C, 15 % (m/m) solids with 10 mgCTec3 gfiber-1. (A) Hydrolysate glucose concentration after 120 h of enzymatic hydrolysis. (B) Particle lengths over the course of enzymatic hydrolysis. Not determined for R-28 or R-14 due to difficulty in sampling these large particles representatively during enzymatic hydrolysis. Having examined the hydrolysis of the SPP200 fractions, their yield stress was determined next (Fig. 13A). Yield stress initially increased from the shortest fraction, R-200 (290 μm mean length; 99 Pa yield stress), to R-100 (608 μm; 290 Pa) and R-48 (951 μm; 330 Pa) as might be expected. The next fraction, R-28, unexpectedly had a much lower yield stress than R-48 (150 Pa), despite having a much higher mean particle length of 1420 μm. The R-14 fraction registered an even lower yield stress (54 Pa), despite comprising very large particles. The relationship between yield stress and mean particle length (Fig. 13B) therefore seems less than straightforward, especially with the irregularly shaped particles produced by thermochemical pretreatment. As mentioned earlier, the lack of a clear relationship is likely at least partly attributable to the fact that the complexity of particle size distributions is not well-represented by a population mean (Wiman et al., 2011), but so far unexplored here and in the literature is the influence of interparticle interactions due to forces at 020406080100120140R14 R28 R48 R100 R200 SPPGlucose concentration (g l-1 )SubstrateA0.00.20.40.60.81.01.20 24 48 72 96 120Particle length (mm)Time (h)B R-48R-100SPP200R-200 73 particle contacts, which have been noted to be important in determining rheology of wood pulp slurries ahead of papermaking (Kerekes, 2006). The electrochemical, surface tension, bending, and hooking forces at fiber contacts important for papermaking slurries likewise can be expected influence pretreated lignocellulose slurry rheology. Indeed, wood fiber properties such as fibrillation, curl, and stiffness have been found to influence slurry yield stress, albeit at low (0.5–1.5 %) solids loadings (Sha et al., 2015). Further work on the influence of fiber morphology and surface characteristics with respect to bioconversion is therefore warranted, especially regarding the influence of these characteristics on flocculation of particles, which has been shown to have a strong effect on fiber slurry rheology (Schmid et al., 2000). Figure 13. Yield stress of size-fractionated steam-pretreated poplar (SPP) suspensions (A) and its relation to particle length (B). Slurries were prepared at 10 % (m/m) solids. Considering these results along with the yield stress profiles determined for the range of substrates in the previous section (3.5), it becomes clear that no one single factor can predict the rheology of lignocellulose slurries, and that instead it is the product of a complex interaction of factors, including particle morphology, interparticle interactions, and substrate–water interactions. 0 100 200 300 400R-14R-28R-48R-100R-200Yield Stress (Pa)Fractionated sampleAR-28R-48R-100R-2001010010000.1 1Yield Stress (Pa)Particle length (mm)B 74 3.7 Conclusions It was apparent that mass transfer is an important factor in high-solids enzymatic hydrolysis, being affected by the mixing method, the solids loading, and the properties of a substrate. The mass transfer boundary, the point at which mass transfer becomes sufficiently limited as to result in a precipitous reduction in hydrolysis yield, was seen to be substrate-specific and correlated to the hygroscopy of a substrate. As a result of worsening mass transfer conditions at increasing solids loadings, the time required for enzymatic liquefaction was furthermore seen to increase in a power-law relationship with solids loading, akin to the power-law relation between yield stress and solids loading observed here and in the literature (Nguyen et al., 2015). The reduction in liquefaction efficiency has direct implications on the time-to-target for bioconversion processes and thus process economics, showing the importance of understanding the underlying mechanisms of enzymatic liquefaction and the substrate properties that affect slurry rheology. It was also shown that it is possible to partially overcome mass transfer limitations without sacrificing volumetric productivity through whole-slurry hydrolysis, provided that the inhibitory compounds in the pretreatment liquid fraction are detoxified. While product inhibition during whole-slurry hydrolysis was seen to have a negative influence on yield, the benefits of relieving mass transfer limitations far outweighed the negative influence of product inhibition. In a survey of the yield stress profiles of a variety of woody substrates, rheological behaviour was shown to differ greatly between different substrates. Steam-pretreatment was generally favourable in producing slurries with lower yield stresses in comparison to other methods such as mechanical or organosolv pretreatment. The scaling of yield stress appeared to be correlated to substrate hygroscopy, reflecting the earlier findings of the influence of hygroscopy on mass transfer. While particle length seemed to have an influence, the factors affecting slurry behavior are multifarious and no single factor could reliably predict slurry rheology. Thus, there remains a need to conduct rheometry of pretreated biomass slurries in order to be able to predict processability at high solids loadings. An important outcome of these findings is that the efficacy of a given pretreatment method should be tested at high solids loadings to reflect the substrate’s rheological behaviour. 75 4 The influence of substrate composition on slurry rheology and enzymatic liquefaction 4.1 Background The composition and physicochemical properties of lignocellulosic substrates play an important role in determining their ease of enzymatic hydrolysis (Mansfield et al., 1999; Zhang and Lynd, 2004). However, digestibility tests are typically conducted at low solids loadings, ignoring the potential influence of substrate composition and physicochemical properties on slurry rheological behaviour. This will likely be critically important in determining mass transfer kinetics and therefore conversion yields at the high solids loadings required for an economically viable process. The work in the previous section (3) assessed the rheological behaviour of pretreated woody substrates with a wide variety of origins and treatment histories. The results indicated that the relationship between substrate characteristics and slurry rheology is complex. While correlations were indicated regarding the influence of substrate composition and physicochemical properties on slurry rheology, the multivariate differences between the range of substrates, and especially their different feedstock species origins, made it difficult to identify specific conclusions with regard to each variable. Ideally, to be able to carry out a useful assessment of how substrate composition and physicochemical properties influence processability at high solids loadings, a representative lignocellulose feedstock should be modified via pretreatment to allow variation of the relative fractions of cellulose, hemicellulose, and lignin, as well as their properties. To this end, differentially pretreated poplar (Populus tremuloides) was prepared using acidic steam pretreatment, neutral steam pretreatment, mechanical pretreatment, laccase-mediated grafting, and delignification, to modify the composition and properties of the hardwood substrate. Poplars are among the fastest growing trees in temperate climates, and advances in their genetic manipulation has enhanced modification of their properties for enhanced amenability to enzymatic hydrolysis (Mansfield et al., 2012). The negative influence of lignin and hemicellulose on cellulose depolymerisation by cellulases has been well documented as lignin physically shields cellulose, restricts fiber swelling and non-productively adsorbs enzymes (Berlin et al., 2006; Nakagame et al., 2011a; Rahikainen et al., 2013). In contrast, hemicellulose primarily acts as a physical barrier coating cellulose fibrils (Hu et al., 2011; Öhgren et al., 2007). However, the roles of lignin and hemicellulose in determining biomass slurry rheology remain unclear. Although both lignin and hemicellulose are amorphous polymers, they 76 differ greatly in the nature of their interactions with water, which, as seen in the previous section (3), is an important property in determining high-solids slurry rheology. Hemicelluloses are highly hydrophilic (Chandra et al., 2016; Piao et al., 2010), while lignin is much more hydrophobic (Grabber, 2005; Tian et al., 2017). These opposing water-interaction tendencies of hemicellulose and lignin have important roles in determining the substrates’ water retention capacity and slurry free water distribution. For example, removal of hemicellulose from lignocellulose has been shown to reduce water retention capacity, while correspondingly, lignin removal was shown to increase water retention (Pejic et al., 2008). In the following section, the influence of the change in water interactions on slurry rheology and high-solids enzymatic hydrolysis was assessed, while examining the influence of substrate composition and physicochemical properties on enzymatic liquefaction at high solids loadings. 4.2 Preparation and characterization of aspen poplar substrates Differential pretreatment of aspen poplar chips was successfully used to produce eight aspen substrates differing in their fractional abundance and characteristics of cellulose, hemicellulose, and lignin (Table 3). Steam pretreatment was used as the basis for six of the eight substrates: SP-Asp, SP-Asp-LGal, SP-Asp-LRes, SP-Asp-Delig, N-SP-Asp, and N-SP-Asp-Delig. The SP-Asp substrates were steam-pretreated under acidic conditions with SO2 as a catalyst, while the N-SP-Asp substrates were subjected to steam pretreatment neutralized with sodium carbonate to maintain a pH of ~7 throughout the treatment. In doing so, acid hydrolysis during steam pretreatment was minimized, which would otherwise solubilize large fractions of the labile hemicellulose polymer. As a result, the N-SP substrates retained a considerable amount of hemicellulose (14–15 %) while, as expected, the conventionally steam-pretreated SP-Asp substrates had lower hemicellulose contents (4.3–4.8 %). Both SP-Asp and N-SP-Asp were furthermore delignified using chlorite bleaching, resulting in the SP-Asp-Delig and N-SP-Asp-Delig substrates. Apart from steam pretreatment, mechanical pretreatment (disc refining) was also used to produce an aspen substrate variant with native, unmodified fractions of cellulose, hemicellulose and lignin. This substrate, RMP-Asp, was further subjected to chlorite bleaching, resulting in the RMP-Asp-Delig substrate. To enable modification of surface lignin properties, SP-Asp was grafted with the phenolic acids gallic acid and resorcinol using laccase-catalyzed radical–radical coupling to produce the SP- 77 Asp-LGal and SP-Asp-LRes substrates, respectively. The intended purpose and properties of these substrates will be discussed in more detail in Section 4.3. Table 3. Composition, water retention capacity, and morphological properties of aspen substrates pretreated using acidic steam pretreatment (SP), neutral steam pretreatment (N-SP), and mechanical refining (RMP). The substrate changes resulting from the differential pretreatment were clear in the visual appearance of the substrates (Fig. 14). The acidic steam-pretreated substrates appeared dark-brown in colour, likely reflecting caramelization of soluble carbohydrates and formation of pseudo-lignin (carbohydrate dehydration products) during pretreatment (Sannigrahi et al., 2011). The light brown colour of the N-SP-Asp substrate suggests that the neutral pH conditions during its pretreatment reduced these degradative reactions. The delignified variants of SP-Asp and N-SP-Asp both exhibited a bleached appearance following removal of lignin (as well as pseudo-lignin and caramelization products). The neutral beige colour of the RMP-Asp substrate likely reflected its native, unmodified structure, while the only slightly lighter colour of its delignified variant likely reflected the limited delignification that occurred during chlorite bleaching (reducing from 29 % in RMP-Asp to 19 % in RMP-Asp-Delig). On the other hand, both the acidic and neutrally steam-pretreated substrates had high extents of delignification (<5 % lignin remaining). However, the neutrally steam-pretreated substrate required two rounds of chlorite bleacing to achieve this low level of lignin, indicating that the acidic steam-pretreatment was most effective in enhancing subsequent delignification, as has been observed previously (Panagiotopoulos et al., 2013). Substrate Composition (% dry matter) WRV (g g-1) Particle lengtha Particle width Particle diameterb Glucan Lignin Xylan Mannan (μm) (μm) (μm) SP-Asp 60 (0.2) 35 (1.5) 1.6 (0.1) 2.9 (0.1) 2.12 447 21.9 (0.5) 116 SP-Asp-LGal 60 (0.5) 35 (1.8) 1.5 (0.1) 2.8 (0.1) 2.84 428 21.7 (0.5) 112 SP-Asp-LRes 60 (0.4) 41 (0.4) 1.5 (0.1) 2.9 (0.1) 2.59 435 22.1 (0.5) 111 SP-Asp-Delig 91 (1.5) 4.5 (0.5) 1.9 (0.1) 2.9 (0.1) 2.88 461 21.3 (0.5) 114 N-SP-Asp 58 (0.1) 30 (0.6) 11 (0.1) 3.0 (0.1) 2.20 744 23.4 (0.3) 208 N-SP-Asp-Delig 85 (0.5) 4.3 (1.4) 12 (0.1) 2.9 (0.1) 2.92 706 21.4 (0.2) 206 RMP-Asp 45 (0.3) 29 (0.3) 13 (0.1) 4.8 (0.1) 2.02 526 25.5 (0.7) 216 RMP-Asp-Delig 63 (0.2) 19 (0.4) 14 (0.2) 4.8 (0.2) 2.71 488 27.3 (0.8) 235 aLength-weighted mean obtained with optical analysis; bSurface-weighted mean obtained with laser diffraction analysis Values in brackets indicate standard error 78 Figure 14. Picture of aspen substrate variants, as labeled. Substrates were vacuum-filtered to a moisture content of ~70 % by mass. Table 4. Qualitative composition summary of aspen substrate variants. The result of the differential pretreatment on substrate composition is summarized in Table 4. Acidic steam pretreatment resulted in a low hemicellulose content due to acid hydrolysis (especially of the xylan), while mechanical pretreatment retained the highest fractional amount of hemicellulose. Neutral steam pretreatment effectively minimized hemicellulose hydrolysis during pretreatment, with only small fractional losses compared to the mechanically pretreated substrate. Due to extensive Substrate Qualitative relative composition Cellulose Lignin Hemicellulose SP-Asp Medium High Low SP-Asp-LGal Medium High (modified) Low SP-Asp-LRes Medium High (modified) Low SP-Asp-Delig High Low Low N-SP-Asp Medium Medium Medium N-SP-Asp-Delig High Low Medium RMP-Asp Low Medium High RMP-Asp-Delig Medium Medium1 High Criteria: Cellulose: High (>80 %), Medium (50–80 %), Low (<50 %) Lignin: High (>35 %), Medium (10–35 %), Low (<10 %) Hemicellulose: High (>15 %), Medium (5–15 %), Low (<5 %) 1Slightly reduced but still in the Medium category SP-Asp SP-Asp-LGal SP-Asp-LRes SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig RMP-Asp RMP-Asp-Delig 79 removal of hemicellulose, the non-delignified acidic steam-pretreated substrates had the highest lignin content (Table 4). When the water retention capacities (as indicated by the water retention values; WRVs) of the substrates was compared, the mechanically pretreated substrate RMP-Asp had the lowest measured WRV (2.02; Table 3). This reflected its largely native structure, where apart from particle size reduction, likely no substantial changes to cellulose porosity or accessibility occurred. Both acidic and neutral steam-pretreatment slightly increased the WRV (2.12 for SP-Asp; 2.20 for N-SP-Asp) compared to mechanical pretreatment. The higher WRV of the N-SP-Asp substrate likely reflects its higher hemicellulose content. The intermediate WRV of the SP-Asp substrate was likely a result of the balance of the increased porosity afforded by steam pretreatment versus the relative increase in the fractional abundance of lignin. Delignification of each substrate increased the substrate water retention capacity to a similar extent, increasing the WRV 1.33–1.36 fold. This reflected the loss of lignin and fractional increase of hydrophilic polymers (cellulose and hemicellulose) (Pejic et al., 2008). The WRVs of SP-Asp-LGal and SP-Asp-LRes will be discussed in Section 4.3. Figure 15. Volume-based particle size distributions of pretreated aspen substrate variants obtained through laser diffraction particle size analysis. (A) Probability density functions. (B) Cumulative distribution functions. As the differential pretreatment likely resulted in different substrate particle size distributions, particle size analysis of the various aspen substrates was performed in two ways. The 0.00.51.01.52.02.53.03.54.04.50.1 1 10 100 1000Volume (%)Diameter (μm)A SP-AspSP-Asp-LGalSP-Asp-LResSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig02550751000.1 1 10 100 1000Volume(%)Diameter (μm)B 80 first method used was volume-based using laser diffraction analysis, and the second method was number-based using optical fiber analysis. Laser diffraction analysis measures particle size distributions based on the scattering of a laser beam in particulate suspensions and subsequent interpretation of the light scattering data according to Mie theory. This method provides equivalent sphere diameters. While these diameters do not describe true particle dimensions, this method has the advantage that very small particles can easily be measured (down to the submicron range). Laser diffraction size analysis indicated high similarity among the SP-Asp substrates, but large differences between the SP-Asp, N-SP-Asp, and RMP-Asp substrates (Fig. 15). The N-SP-Asp and RMP-Asp substrates exhibited bimodal distributions and the poor particle fragmentation resulting from neutral steam pretreatment is apparent in the peak around 500 μm. Alternatively, acidic steam pretreatment clearly resulted in reduced particle sizes for the SP-Asp substrates, shifting the particle size distributions to the left. These differences are also reflected in the surface-weighted mean diameters (Table 3). Optical fiber analysis is a method developed for the pulp and paper industry and uses a charge-coupled device camera to measure number-based particle dimensions using circular polarized light. Although this method can determine the true dimensions of particles, the method is limited to particles greater than 72 μm in length. While this lower limit suffices for regular wood pulps used for pulp and paper, the particle size distributions of pretreated woody substrates that undergo particle fragmentation cannot be fully measured using this technique, as seen with the pretreated substrates used here (Fig. 16). It was apparent that much of the SP-Asp and RMP-Asp substrates’ particle size distribution was not measurable. Only the right-most peak of the N-SP-Asp bimodal distribution seen with the laser diffraction method was detected. As a result, this method indicated the N-SP-Asp particles to be the largest on average, with mean lengths of 706–744 μm, compared to 488–526 μm for the RMP-Asp substrates and 428–461 μm for the SP-Asp substrates. In contrast, laser diffraction suggested that the RMP-Asp substrate had the largest particles on average, with mean diameters of 216–235 μm, compared to 206–208 μm for the N-SP-Asp substrates and 111–116 μm for the SP-Asp substrates. Comparing the volume-based cumulative distribution functions (Fig. 15B), this might be explained by the slight increase in very large particles seen at the far right of the curves. Apart from showing the limitations of the optical analysis method, these results also seem to confirm the findings that population means often do not represent the underlying particle size distributions well (Wiman et al., 2011). However, population means do provide a convenient value by which to examine whether particle fragmentation is occurring, e.g. during enzymatic hydrolysis. They can also be derived from 81 either volume-based or number-based particle size analysis methods, given that larger particles have a disproportionately greater influence on fiber network formation and slurry rheology (Derakhshandeh et al., 2011). Figure 16. Number-based particle size distributions of pretreated aspen substrate variants obtained through optical fiber analysis. (A) Probability distribution function of particle length. (B) Cumulative distribution function of particle length. Having examined the composition, morphology, and water interaction behavior of the substrates, the rheology of the substrates was next studied. Yield stress curves were determined at increasing solids loadings for all aspen substrate variants (Fig. 17). The different aspen substrate variants differed greatly in their yield stress profiles, with the N-SP-Asp substrates registering a yield stress of 100 Pa at ~3.75 % solids, while the SP-Asp substrate did not do so until a solids loading of ~10 %. It is remarkable that delignification of the SP-Asp substrate resulted in a tremendous yield stress profile shift, with the SP-Asp-Delig registering a yield stress of 100 Pa at ~5.5 %, nearly halving the solids loading needed to reach the same yield stress. Delignification of the other substrates (RMP-Asp and N-SP-Asp) did not achieve the same effect, with the delignified and non-delignified variants having essentially identical yield stress curves. The reasons for this are not clear, given the essentially identical particle size distributions of the delignified variants compared to their non-delignified counterparts and the similar fold-increases in water retention capacity following delignification. However, it is possible that the coalesced lignin and pseudo-lignin deposited on the SP-Asp particle 02468101214160.08 0.8Frequency (%)Particle length (mm)ASP-AspSP-Asp-LGalSP-Asp-LResSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig0204060801000.08 0.8Frequency(%)Particle length (mm)B 82 surfaces following acidic steam pretreatment (Donaldson et al., 1988; Sannigrahi et al., 2011) resulted in weaker interparticle interactions (e.g. through repulsion, reductions in coefficients of friction, reduced hydrogen-bonding interactions). This effect would be reduced when the lignin/pseudo-lignin is removed via chlorite bleaching. Although not confirmed here, such an effect is supported by the conclusions of a study by Dibble et al. (2011) who found that mechanical fragmentation of biomass particles did not reduce slurry yield stress while dilute acid-pretreatment did. These authors ascribed this difference to changes imparted at particle surfaces. Dilute acid pretreatment, like steam pretreatment, has been shown to result in deposition of lignin at the surface of biomass particles (Donohoe et al., 2008; Selig et al., 2007). The benefit of lignin coalescence at particle surfaces with regard to rheology would likewise explain the general greatly reduced yield stress of steam-pretreated substrates compared to pulps that are not prepared under conditions that promote lignin deposition, as observed in Section 3. All considered, these results support the notion that retention of lignin within the substrate alongside removal of hemicellulose can be beneficial for improving slurry rheology. The yield stress curves of SP-Asp-LGal and SP-Asp-LRes in comparison to SP-Asp will be discussed further in Section 4.3. Figure 17. Slurry yield stress values of pretreated aspen substrate variants determined through unidirectional shear stress ramps at different solids loadings and power-law regression fits shown on linear (A) and log–log plots (B). The power law relationships of the substrates are listed in (B), calculated using the fractional consistency, Cm, in the form τy = a𝐶,8 . 04008001200160020000 2 4 6 8 10 12Yield stress (Pa)Solids loading (%)A N-SP-Asp-DeligN-SP-AspRMP-Asp-DeligRMP-AspSP-Asp-DeligSP-Asp-LGalSP-Asp-LResSP-Asp1101001000100001 10Yield stress (Pa)Solids loading (%)B τy = 5.1×106Cm3.31 τy = 5.8×106Cm3.36 τy = 3.4×107Cm4.32 τy = 6.0×108Cm5.42 τy = 1.1×109Cm5.75 τy = 8.8×107Cm5.47 τy = 2.8×107Cm5.15 τy = 1.8×107Cm5.07 83 To expand upon the previous analysis conducted in Section 3 on the relationship between substrate properties and slurry rheology, we next conducted combined analysis of the yield stress profile data sets of the aspen substrate variants (Fig. 17) and the variety of substrates examined in Section 3 (Fig. 7) with respect to their measured properties (Table 1 and Table 3). We hoped that doing so could provide further insight into the substrate properties that are most influential in determining slurry rheology. To assess how strongly substrate factors could account for slurry rheology, factorial regression analysis of the combined data set was performed using water retention capacity and mean particle aspect ratio as covariates. These two factors were chosen as they were the most suitable proxies available in the combined data set for substrate hygroscopy and overall substrate morphology. The first dependent variable examined in the factorial regression was the yield stress power law exponent b, which describes the proportionality of yield stress to solids loading. Multiple linear regression with water retention capacity and particle aspect ratio as the independent variables (covariates) provided a moderate coefficient of determination (R2) of 0.543. However, independent regression with water retention capacity or particle aspect ratio resulted in R2 values of 0.079 and 0.509, respectively. This suggested that the particle aspect ratio was the more influential factor in accounting for the variability in the yield stress power law exponent, when examined across all substrates. Similarly, when the solids loading at the onset of yield stress (i.e. the solids loading at which the slurry begins to register a measurable yield stress) was used as the independent variable, multiple linear regression provided an R2 of 0.426, while independent regression of water retention capacity and particle aspect ratio provided R2 values of 0.040 and 0.381, respectively. However, while the factorial regression analysis across the combined data set suggested that water retention capacity had near-negligent explanatory power for slurry rheology, it is important to remember that the strength of the factors as predictors of slurry rheology depends on their strength in capturing the biomass characteristics for which they are supposed to be a proxy. In Section 3, it was evident that the water retention capacity correlated strongly to the proportionality of yield stress to solids loading when compared among conventional wood pulps (R2 = 0.944) or among steam-pretreated pulps (R2 = 0.804) separately, but not when examined across both sets of substrates (R2 = 0.368). This was likely due to the vast difference in substrate–water interactions following steam-pretreatment compared to the conventional pulping methods, which made the water retention capacity a poor proxy for overall substrate hygroscopy. Similarly, mean particle aspect ratios are a simplification of the complexity of pretreated biomass particle size distributions, and thus a simplified 84 proxy of substrate morphology. Given the inadequacy of the proxy substrate properties it was not surprising that no strong correlation could be determined across the combined data set. Consequently, it was difficult to draw generalizations with regard to the relationship between substrate properties and slurry rheology. Figure 18. Cellulose hydrolysis of aspen substrate variants during enzymatic hydrolysis with 2.5 mgprotein gcellulose-1 T. reesei preparation (CTec3) at 2 % solids in 2-ml centrifuge tubes rotated end-to-end, showing hydrolysis extent (A) and glucose concentration (B). Hydrolysis of aspen substrates was conducted at a low enzyme loading (2.5 mgprotein gcellulose-1 of a T. reesei cellulase preparation) and a low solids loading (2 %) to establish enzymatic digestibility of the substrates in the absence of the influence of mass transfer limitations (Fig. 18). The mechanically pretreated substrate, RMP-Asp, showed poor digestibility, as might be expected given the largely native structure following its minimal pretreatment. Delignification of RMP-Asp resulted in a 3.4-fold increase hydrolysis extent following 27 h, with RMP-Asp-Delig reaching 27.5 % hydrolysis compared to 8.1 % for the RMP-Asp substrate. This was expected given the negative influence of lignin on enzymatic digestibility and the benefit of its removal (Kumar et al., 2012), especially for mechanical pulps (Mooney et al., 1998). Neutral steam pretreatment resulted in a less digestible substrate than acidic steam pretreatment, with N-SP-Asp achieving 23.3 % hydrolysis at 27 h compared to 32.3 % for the SP-Asp substrate, likely a result of limited hemicellulose removal and 010203040500 6 12 18 24Hydrolysis extent (%)Time (h)A N-SP-Asp-DeligSP-Asp-LGalSP-AspRMP-Asp-DeligSP-Asp-DeligN-SP-AspSP-Asp-LResRMP-Asp010203040500 6 12 18 24[Glucose] (mM)Time (h)B 85 particle fragmentation. However, the delignified variant of N-SP-Asp resulted the highest extent of hydrolysis, reaching 43.1 % hydrolysis and a glucose concentration of 48 mM. In contrast, the extent of hydrolysis of the SP-Asp-Delig substrate was reduced compared to SP-Asp (Fig. 18A), although the hydrolysate glucose concentration was still higher than achieved with SP-Asp as a result of the higher relative cellulose fraction (Fig. 18B). It is possible that the relatively large fraction of hemicellulose present in the N-SP-Asp substrate acted as a spacer between cellulose fibrils, preventing collapse of the fibrillary structure during delignification, thereby maintaining higher accessibility to the cellulose (Ishizawa et al., 2009; Pihlajaniemi et al., 2016). The relative absence of hemicellulose in SP-Asp during delignification therefore may have allowed collapse of the cellulose microfibrils, resulting in reduced enzymatic digestibility. The enzymatic digestibility of SP-Asp-LGal and SP-Asp-LRes will be discussed in the next section. 4.3 Modification of lignin through laccase-catalyzed grafting and its influence on rheology and enzymatic hydrolysis Lignin is a major obstacle restricting effective enzymatic deconstruction of lignocellulosic materials due to its steric hindrance and unproductive adsorption of cellulolytic enzymes (Li et al., 2016; Nakagame et al., 2011a). Native lignin is relatively hydrophobic due to its aromatic moieties, which is thought to be important in causing unproductive adsorption through interactions with solvent-exposed hydrophobic patches in cellulases such as the aromatic residue-rich binding faces (Sammond et al., 2014). While lignin can be removed through delignification to negate its negative influence on enzymatic hydrolysis, these methods tend to be costly and chemically intensive, as well as compromising hemicellulose recovery (Chandra et al., 2016; Tian et al., 2017). Pretreatments that lessen lignin’s inhibitory effects through its partial removal, relocation and/or modification such as steam pretreatment tend to be more economically favourable and have been extensively researched (Zhu et al., 2010). Following such pretreatments, the properties of the remaining lignin fraction are heavily modified, producing a wide range of physicochemical characteristics sensitive to the nature of the treatment and the plant species (Guo et al., 2014; Pareek et al., 2013). However, through modification of pretreatment conditions (Trajano et al., 2013) or through co-treatments such as sulfonation or carboxylation (Siqueira et al., 2017), lignin’s properties can be controlled and made more favourable with regard to enzymatic hydrolysis, such as through decreasing lignin’s hydrophobicity to reduce unproductive adsorption. 86 In studies examining the connection of lignin physicochemistry and unproductive adsorption of cellulases, it has been shown that it is favourable to reduce lignin hydrophobicity (Huang et al., 2017). Lignin carboxylation and sulfonation for example decreased lignin inhibition by up to 96 % (Yang and Pan, 2016). Correspondingly, genetic engineering studies have shown that enzyme surface hydrophobicity correlates with adsorption to lignin (Sammond et al., 2014) and that removal of the CBM of TrCel7A (which has a hydrophobic binding face) reduces binding to lignin (Rahikainen et al., 2013). Site-directed mutagenesis of the TrCel7A has further shown that introduction of negatively charged residues increases binding specificity to cellulose (Strobel et al., 2016). While modification of lignin to reduce its hydrophobicity during pretreatment could minimize unproductive adsorption, this at the same time will affect the substrate’s water adsorption and water retention capacity. In the previous section (3), as well as in studies by other authors (Roberts et al., 2011; Selig et al., 2012), it was shown that substrate–water interactions are important in determining slurry rheology and high-solids hydrolysis kinetics. The hygroscopic nature of lignocellulosic biomass, i.e. its tendency to absorb water, creates a significant challenge for its processing at high solids loadings. Thus, modification of lignocellulose for increased hydrophilicity could potentially compound this challenge and worsen mass transfer conditions at high solids loadings. To study the influence of altered lignin hydrophobicity on both unproductive adsorption and substrate–water interactions, laccase-catalyzed grafting can be used. Laccases are copper-containing oxidase enzymes that catalyze the reduction of oxygen to water with concomitant oxidation of another molecule, typically a phenolic compound, that serves as a hydrogen donor (Baldrian, 2006). As a result of the electron transfer during oxidation, the substrate molecule becomes a stable radical that can undergo coupling reactions. By incubating laccase with phenolic compounds in the presence of lignocellulosic materials, phenoxy radicals are formed that can be grafted onto lignocellulose via covalent coupling. Such reactions have been explored for functionalization of various lignocellulosic materials (Kudanga et al., 2011). Laccase-catalyzed grafting of the phenolic compounds resorcinol and gallic acid was performed on SP-Asp, resulting in the SP-Asp-LRes and SP-Asp-LGal substrates (Fig. 19A). In doing so, the lignin of an industrially relevant steam-pretreated substrate was specifically modified while leaving cellulose and hemicellulose unaltered. The carboxylic acid gallic acid (3,4,5-trihydroxybenzoic acid) was used to increase the carboxylic acid content of the lignin, thereby increasing its hydrophilicity. Increasing the carboxylic acid content of lignin has previously been shown to reduce unproductive adsorption (Nakagame et al., 2011b). The benzenediol resorcinol 87 (benzene-1,3-diol) was chosen to introduce additional phenolic moieties, thus increasing hydrophobicity. Higher phenolic acid content in lignin has also been shown to correlate to reductions in cellulose hydrolysis (Yang and Pan, 2016). Grafting was done according to the conditions described by Chandra et al. (2004) using 1 mmol of gallic acid or resorcinol per gram of substrate with a Myceliophthora thermophila laccase. A Figure 19. Laccase-mediated grafting of phenolic compounds onto lignin. (A) Reaction scheme for laccase-mediated grafting of phenolic compounds (gallic acid, 3,4,5-trihydroxybenzoic acid; resorcinol, benzene-1,3-diol) onto lignin. The laccase structure shown is a representative laccase from Trametes versicolor (Protein Data Bank code 1KYA). (B) Enzymatic hydrolysis of untreated and laccase-grafted steam-pretreated aspen (SP-Asp) substrates at 2 % m/m for 24 h with increasing enzyme loading. (C) Control reactions (5 mgprotein gcellulose-1) of SP-Asp incubated with non-grafted resorcinol, gallic acid, or laccase individually following washing. (D) Hydrolysis following bovine serum albumin (BSA) blocking (1 h BSA block, 1 % solution by mass; 24 h hydrolysis at 5 mgprotein gcellulose-1). 02550751000 10 20 30[Glucose] (mM)Enzyme loading (mg g-1)BSP-Asp-LGalSP-AspSP-Asp-LRes01020300 6 12 18 24Time (h)CSP-Asp+ resorcinol+ gallic acid+ laccase010203040SP-AspSP-Asp + BSALGalLGal + BSA LResLRes + BSADO2 H2O Laccase Lignin + Phenolic compound + 88 Table 5. X-ray photoelectron spectroscopy surface analysis of steam-pretreated aspen (SP-Asp), gallic acid-grafted steam-pretreated aspen (SP-Asp-LGal), and resorcinol-grafted steam-pretreated aspen (SP-Asp-LRes). Substrate Carbon I (%) Carbon II (%) Carbon III (%) Carbon IV (%) O/C ratio SP-Asp 63.4 22.5 11.9 2.22 0.300 SP-Asp-LGal 61.3 26.0 9.38 3.38 0.303 SP-Asp-LRes 65.7 19.9 12.7 1.69 0.298 Carbon I: C-C, C-H, C=C; Carbon II: C-O; Carbon III: C=O, O-C-O; Carbon IV: O-C=O Previous work with laccase-catalyzed grafting has shown that resorcinol tends to form carbon–carbon bonds (Dong et al., 2016) while gallic acid tends to form ether bonds at the para-hydroxyl group (Widsten et al., 2010), as illustrated in Fig. 19A. Following grafting, the fractional composition of SP-Asp-LGal was essentially identical compared to SP-Asp, while the lignin content of SP-Asp-LRes increased from 35 % to 41 % of dry matter (1.17-fold increase) (Table 3). It appeared that, at least in terms of net addition of material, grafting of resorcinol was more effective than grafting of gallic acid. However, it should be noted that the radicalized phenolic compounds can serve as redox mediators that in turn oxidize lignin and cause its depolymerization. The balance of the opposing mechanisms of polymerization and depolymerization depends on the reaction conditions and nature of the mediator (Felby et al., 2004). A recent study showed that delignification was insignificant when gallic acid was used as a mediator during laccase treatment of birch or spruce (Goacher et al., 2017). Instead, it has been shown that gallic acid can be effectively grafted onto wood pulp, resulting in an increase in pulp carboxylic acid content (Chandra et al., 2004). The increase in the carboxylic acid content of SP-Asp-LGal was likewise confirmed through conductometric titration (71 μmol g-1 for SP-Asp-LGal, compared to 57 μmol g-1 for SP-Asp). Accordingly, the reaction equilibrium for resorcinol may have favoured a net addition to the SP-Asp substrate, while for gallic acid the opposing mechanisms were more balanced under the conditions studied here, resulting in no apparent net change in the amount of lignin present. Analysis of substrate surface composition using X-ray photoelectron spectroscopy (XPS) furthermore indicated modest surface lignin modification (Table 5). While the oxygen/carbon ratio remained relatively constant, changes in the different carbon classes as revealed by deconvolution of the carbon signal reflected successful grafting. SP-Asp-LGal showed increased class II (C-O) carbon compared to SP-Asp, reflecting the increase in hydroxyl content following grafting of gallic acid, as well as an increase in class IV (O-C=O) carbon, corresponding to the carboxyl group of gallic acid. SP-Asp-LRes on the other hand showed an 89 increase in class I carbon, reflecting an increase in carbon–carbon linkages as a result of resorcinol grafting. Figure 20. Water contact angles of acidic steam-pretreated aspen (SP-Asp), gallic acid-grafted steam-pretreated aspen (SP-Asp-LGal), and resorcinol-grafted steam-pretreated aspen (SP-Asp-LRes) determined through the sessile drop method. The box plots were derived from 10 measurements per sample. Despite an apparent lack of change in the amount of lignin for SP-Asp-LGal and modest changes detected by XPS, contact angle measurements indicated increased hydrophilicity for SP-Asp-LGal and increased hydrophobicity for SP-Asp-LRes (Fig. 20). As a result, enzymatic hydrolysis of the grafted substrates at 2 % solids clearly showed the influence of laccase treatment in a manner fitting with the unproductive binding of cellulase to lignin for both SP-Asp-LGal and SP-Asp-Lres (Fig. 19B). Overall, this suggested successful modification of the substrate with gallic acid and resorcinol. Following 24 h of hydrolysis at an enzyme loading of 30 mg g-1, SP-Asp-LGal showed 1.07-fold increased glucose yield compared to SP-Asp, while SP-Asp-LRes had 0.94-fold the glucose yield of SP-Asp. At an enzyme loading of 2.5 mg g-1, the effect was more pronounced, with the glucose yield of SP-Asp-LRes being only 0.71-fold that achieved with SP-Asp. At an enzyme loading of 10 mg g-1 the effect was intermediate, resulting in a yield 0.83-fold that of SP-Asp. Likewise, the increase for SP-Asp-LGal was most pronounced at a low enzyme loading, with a 1.22-fold higher glucose yield at 2.5 mg g-1, and an intermediate effect at 10 mg g-1 with a 1.10-fold increase. Differences in hydrolysis yield were largest at low enzyme loadings, indicating that grafting of gallic acid and the increase in carboxylic acid content reduced unproductive binding, enabling modest increases in enzymatic 90 hydrolysis. On the other hand, grafting of resorcinol caused glucose yield reductions, suggesting increased unproductive binding as a result of the hydrophobic character imparted on the SP-Asp-LRes substrate. Control treatments were also conducted where the SP-Asp substrate was incubated with gallic acid or resorcinol in the absence of laccase under the same conditions of grafting, followed by extensive washing to remove the phenolic compounds. Enzymatic hydrolysis of the control substrates showed identical hydrolysis behaviour as observed with the SP-Asp substrate, confirming that the imparted properties were a result of laccase catalysis (Fig. 19C). When the SP-Asp substrate was also treated with laccase, this, unexpectedly, resulted in reduced hydrolysis (0.88-fold at 22 h). It is possible that, in the absence of phenolic compounds to react with, the laccase reacted with the lignin deposited at the steam-pretreated substrate’s surface, increasing lignin cross-linking (Felby et al., 2004) and thereby reducing substrate accessibility. Figure 21. (A) Enzymatic digestion of untreated and laccase-grafted steam-pretreated aspen (SP-Asp) substrates at 10 % solids for 43 h with increasing enzyme loadings. (B) Yield stress plots of the untreated and laccase-grafted SP-Asp substrates on linear and log–log (inset; base two, error bars removed for clarity) scales, with fitted power-law curves. The power law relationships of yield stress to solids loading (expressed as a consistency fraction, Cm) are given. To further examine the impact of grafting of gallic acid and resorcinol on unproductive adsorption, lignin was blocked with bovine serum albumin (BSA) prior to subsequent enzymatic hydrolysis (Fig.19D). Incubation of lignocellulose with BSA has been shown to effectively minimize 01002003004005006000 10 20 30 40[Glucose] (mM)Enzyme loading (mg g-1)ASP-Asp-LGalSP-AspSP-Asp-LRes01002003004004 5 6 7 8 9 10Yield stress (Pa)Solids loading (%)B2202004 8 16τy = 8.8×107Cm5.47 τy = 2.8×107Cm5.15 τy = 1.8×107Cm5.07 91 unproductive adsorption of cellulase through non-specific irreversible adsorption of BSA onto lignin (Yang and Wyman, 2006). Following BSA-blocking of lignin, enzymatic hydrolysis yields were increased 1.30-fold for SP-Asp, 1.19-fold for SP-Asp-LGal, and 1.41-fold for SP-Asp-LRes. The larger increase for SP-Asp-LRes compared to SP-Asp following BSA-blocking provided further evidence for the increased unproductive binding following grafting of resorcinol. The lower increase of SP-Asp-LGal appeared to indicate that unproductive binding was already partly mitigated through grafting of gallic acid, resulting in a relatively lower benefit gained from BSA adsorption. While the enzymatic hydrolysis results were consistent with increased hydrophilicity for SP-Asp-LGal and increased hydrophobicity for SP-Asp-LRes, both substrates were found to have increased water retention capacity (2.84 and 2.59 gwater gsubstrate-1 respectively compared to 2.12 gwater gsubstrate-1 for SP-Asp; Table 3). Although the increase was unexpected for SP-Asp-LRes given the apparent hydrophobization of the substrate, it is possible that at the same time this hydrophobization increased the entrapment of water in the substrate. As noted earlier, substrate–water interactions are important in determining high solids hydrolysis kinetics and slurry rheology. To examine the influence of grafting and concurrent increases in water retention capacities during high solids reactions, enzymatic hydrolysis of SP-Asp and its grafted variants was conducted at 10 % solids (Fig. 21A). In contrast to hydrolysis at a low solids loading, at 10 % solids, where the yield stress of SP-Asp-LGal was 1.83-fold that of SP-Asp (Fig. 21B), SP-Asp-LGal reached lower glucose yields than SP-Asp. Apparently, the benefit of reduced unproductive binding was negated by the increased yield stress and resulting poor mixing/mass transfer conditions during enzymatic hydrolysis. At a low enzyme loading of 5 mg g-1, the difference between SP-Asp and SP-Asp-LGal was minimal, indicating that the reduced unproductive binding of SP-Asp-LGal partly made up for the poorer mass transfer conditions. However, at higher enzyme loadings, where the issue of unproductive binding becomes negated by enzyme saturation, SP-Asp reached hydrolysis yields that were up to 1.23-fold higher. The yield stress of SP-Asp-LRes was also significantly higher at 10 % solids, although less so than SP-Asp-LGal, with a 1.26-fold increase over SP-Asp. As a result of the yield stress of SP-Asp-LRes scaling less quickly with solids loading, SP-Asp-LRes reached a higher hydrolysis yield than SP-Asp-LGal at an enzyme loading of 40 mg g-1, despite its increased hydrophobicity. Overall, these results again point to the complex and paradoxical nature of certain substrate treatments that was also observed in Section 3. For example, while the increased hydrophilic character 92 of the SP-Asp substrate lignin following gallic acid grafting showed a beneficial effect during enzymatic digestion at low (2 %) solids, the increased yield stress and worse mass flow at a higher solids loading (10 %) resulted in decreased hydrolysis performance. As was hypothesized at the beginning of this work, modification of lignocellulose for increased hydrophilicity was shown to compound the rheological challenge and worsen mass transfer conditions at high solids loadings. This further showed the importance of testing the influence of substrate treatments at high solids loadings, since it was apparent that enzymatic hydrolysis kinetics differed dramatically between low and high solids loadings. With regard to hydrophilization of lignin to minimize unproductive adsorption, it would be beneficial if we could engineer feedstocks with low-hydrophobicity lignin (Mottiar et al., 2016), as long as the resulting substrate’s properties (particularly the substrate’s hygroscopy) make it amenable to high-solids hydrolysis. Having examined the characteristics and enzymatic hydrolysis of SP-Asp-LGal and SP-Asp-LRes in detail, the rest of the work in this section limited its focus to the other aspen substrate variants. 4.4 Examination of substrate–water interactions using isothermal thermogravimetric analysis By studying a broad range of woody substrates (Section 3), as well as the grafted substrates SP-Asp-LGal and SP-Asp-LRes, substrate–water interactions were shown to be of principal importance in determining slurry rheology and high solids hydrolysis kinetics. The main method used to assess substrate–water interactions was the water retention value (WRV) test. Although the values obtained through this test were indicative of the hygroscopy of different substrates, the WRV test does not provide a direct measurement of the free water conditions at a given solids loading. Considering the amount of free water available in the reaction medium, the point at which all water becomes associated with the substrate is likely an important indicator with regard to mass transfer kinetics in enzymatic hydrolysis reactions. Hemicellulose and lignin can be expected to have significant impacts on changing these interactions, given their opposing hydrophilic and hydrophobic properties, respectively. Thus, being able to measure the free water boundary might help predict the processability of a substrate at high solids loadings and elucidate the influence of hemicellulose and lignin on high-solids hydrolysis kinetics. 93 Figure 22. Isothermal thermogravimetric analysis (TGA) of steam-pretreated aspen (SP-Asp) drying. (A) Derivative thermogravimetric (DTG) curve (left axis; first derivative of the TGA curve) showing mass flow rate, and the solid fraction curve (right axis) showing the fraction of solids of the total mass. The arrow on the DTG curve indicates the aberration in the ‘constant’ rate zone. (B) A close-up of the ‘constant’ rate zone (black curve; left axis) of the DTG curve and its derivative curve (blue curve; right axis), DDTG, showing the ‘dip’ in the mass flow rate. The minimum of the DDTG curve was taken as the boundary of the higher rate and lower rate zones, and the associated mass fraction at this time point was taken as the boundary mass fraction. Previous work using isothermal thermogravimetric analysis (TGA) to study the drying of wood pulps showed that distinct water populations associated with pulp could be determined (Park et al., 2006). In particular, these authors examined the water population closely associated with the substrate. This so-called “hard-to-remove” water fraction was defined as the moisture content at the transition between the constant rate zone and falling rate zone of mass flow during isothermal evaporation (Fig. 22A). This water population is similar to the pore-entrapped water population determined by the WRV test, and indeed, the values obtained by the two methods were found to correlate closely (Park et al., 2006). In a follow-up paper examining microfibrillated cellulose, an additional critical point within the ‘constant’ rate zone was discovered, which was proposed to be related to water within the complex fiber network structure of microfibrillar material (Sen et al., 2012). This work suggested that, in addition to being able to determine the fraction of water adsorbed to/entrapped by the substrate (i.e. the hard-to-remove water), the TGA method may also be used to differentiate between free water and substrate-associated water. However, both of the aforementioned TGA studies were conducted on slurries prepared at a 10 % solids content. As observed earlier in this thesis work (sections 3.5, 4.2), the onset of yield stress and its associated mass transfer issues occurs 0.00.20.40.60.81.00.00.51.01.52.00 20 40 60Solid fractionMass flow rate (mg min-1)Time (min)A-0.3-0.2-0.10.01.51.61.71.81.92.02.12.25 15 25 35 45d(mass flow rate)/dt (mg min-2)Mass flow rate (mg min-1)Time (min)BWarm-up zone 'Constant' rate zone Falling rate zone 94 well before a solids loading of 10 %. Indicative of this, the picture of the SPP200 slurries prepared at increasing solids loading showed that free water is nearly nonexistent at 10 % solids (section 3.3, Fig. 3). Accordingly, to try to characterize the population of free water and the solids loading boundary at which the free water population is depleted, slurries were prepared at less than 3 % solids prior to TGA measurement using substrates varying in their relative hemicellulose and lignin contents. Using SP-Asp as an initial test substrate for isothermal TGA, the ‘constant’ rate zone was consistently seen to exhibit a mid-zone drop in mass transfer rate (indicated by the arrow in Fig. 22A). As seen in the close-up of the ‘constant’ rate zone (Fig. 22B), this critical point in the derivative thermogravimetric (DTG) curve is preceded by a reduction in the mass flow rate leading up to a large drop at the critical point, followed by further rate reduction prior to the falling rate zone. The second derivative thermogravimetric (DDTG) curve provides additional confirmation of this critical point (Fig. 22B). Following triplicate measurement, the solids content at which the critical point occurred for SP-Asp was found to be 9.9 ± 0.7 %. It was hypothesized that this critical point in the mass flow rate is due to the exhaustion of free, non-biomass-associated water. Accordingly, the initial higher rate portion of the ‘constant’ rate zone during thermogravimetric analysis ahead of the critical point corresponds to the evaporation of primarily free water, while the lower rate portion corresponds to evaporation of primarily biomass-associated water found in cell lumen and large pores/fractures. If this critical point in the DTG curve indeed corresponds to a slurry free water boundary, the hygroscopy of a substrate would be expected to have a direct influence on the solids loading at which the boundary occurs. To test this hypothesis, the TGA method was used to measure the free water boundary for SP-Asp-Delig (low in hemicellulose and low in lignin content) and N-SP-Asp (high in cellulose, hemicellulose, and lignin content), in addition to the SP-Asp substrate (low in hemicellulose, high in lignin and cellulose) measured earlier. In doing so, three substrates prepared from the same biomass feedstock with precisely controlled hemicellulose and lignin contents could be tested for their difference in substrate–water interactions. It was apparent that the WRVs of SP-Asp, SP-Asp-Delig and N-SP-Asp of 2.12, 2.90 and 2.20 mg g-1, respectively, reflected their fractional hydrophilic biopolymer content by the fact that, the higher the cellulose/hemicellulose content, the higher the WRV (Table 3). Following TGA measurement, free water boundary values of 6.2 ± 0.2 % for SP-Asp-Delig and 8.8 ± 1.0 % for N-SP-Asp were determined. It was again apparent that these free water boundary values were inversely correlated to the substrates’ WRVs, as the higher the WRV (hygroscopy) of a substrate, the earlier the boundary solids content is reached. Thus, the TGA method appeared to provide an accurate measurement of the solids loading at which slurry free water 95 depletes. As was hypothesized, the relative hydrophilic biopolymer (cellulose/hemicellulose) to hydrophobic biopolymer (lignin) ratio correlated to the free water boundary, indicating the influence of hemicellulose and lignin in determining high solids processability of biomass slurries. Thus, the TGA mass transfer boundary results provided further support of the notion that removal of hemicellulose while retaining lignin in the substrate may be beneficial for high-solids hydrolysis with respect to mass transfer kinetics. This would be particularly true if the lignin could be modified to have a low cellulase-binding capacity, provided that such modifications do not compromise high-solids mixability, as seen in the previous section with phenolic compound-grafting. 4.5 Oscillatory rheometry of aspen substrate variants Thus far in the thesis work, rheological characterization had been limited to yield stress determination through unidirectional shear flow with a simple viscometer. While slurry yield stress is one of the most, if not the most, relevant rheological parameters for industrial processes (Derakhshandeh et al., 2011; Knutsen and Liberatore, 2009), a more detailed rheological characterization might prove additionally instructive with regard to the influence of substrate characteristics on slurry rheology. Furthermore, the unidirectional flow rheometry used thus far could not be applied at high solids loadings due to fracture at the edge of the vane. Sample fracture leads to a slip layer between the vane plug and the surrounding material in the measurement cup. This has been noted to be a common problem with unidirectional shear rheometry (Mas and Magnin, 1997), as well as having been reported for biomass slurries (Stickel et al., 2009). As outlined in the Introduction (section 1.3), dynamic measurement during sinusoidal shear deformation with an oscillatory rheometer allows detailed viscoelastic characterization of biomass slurries while avoiding edge fracture. Parameters that individually quantify the viscous and elastic properties of a material can be defined, which in turn can be related to the material’s processability within an industrial context (Marin, 1993; Weitz et al., 2007). Oscillatory rheometry was therefore performed on the aspen substrate variants at 15, 10, and 5 % solids over a frequency range of 1–100 Hz (Fig. 23), providing the complex viscosity (h*; A–C), storage modulus (G¢; D–F), and loss modulus (G″; G–I) of these materials as a function of oscillatory frequency. 96 15 % solids 10 % solids 5 % solids Figure 23. Small angle oscillatory sweeps of aspen substrate variants at 15, 10, and 5 % solids (arranged in columns). Complex viscosity profiles (A, B, C), storage modulus profiles (D, E, F), and loss modulus profiles (G, H, I) are shown for each solids loading. 0.0010.010.11101001 100Complex viscosity, η*(kPa∙s)Frequency (Hz)ASP-AspSP-Asp-DeligSP-Asp-LGalSP-Asp-LResN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig0.0010.010.11101001 10 100Frequency (Hz)B0.0010.010.11101001 10 100Frequency (Hz)C0.010.111010010001 100Storage modulus, G′(kPa)Frequency (Hz)D0.010.111010010001 10 100Frequency (Hz)E0.010.111010010001 10 100Frequency (Hz)F0.010.111010010001 100Loss modulus, G′′(kPa)Frequency (Hz)G0.010.111010010001 10 100Frequency (Hz)H0.010.111010010001 10 100Frequency (Hz)I 97 The order of the substrates with regard to their relative complex viscosity, storage modulus, and loss modulus values determined here reflected the same substrate order for the relative yield stresses measured earlier using unidirectional flow rheometry (Fig. 17). This suggests that the two rheometry methods are comparable, at least with regard to the relative order of rheological parameters of the substrates. As expected for lignocellulosic materials (Knutsen and Liberatore, 2009), the frequency dependence of complex viscosity reflected strong shear-thinning behaviour, generally decreasing two orders of magnitude from 1 Hz to 100 Hz for all substrates (Fig. 23A–C). At a solids loading of 5 %, a departure from linear viscoelastic response at high frequencies was apparent, especially for the SP-Asp, SP-Asp-LGal, SP-Asp-LRes, and SP-Asp-Delig substrates (Fig 23C, F, I). Measurements outside the linear response region for these substrates were therefore omitted. The decreasing linearity in the viscoelastic response was also noticeable in the increasing standard error of the triplicate measurements at higher frequencies for the other substrates, denoted with the error bars. The h*, G¢, and G″ functions of the acidic steam-pretreated (SP-Asp) substrates grouped together neatly at 15 % solids, with separation of their rheological behaviour becoming apparent, first for SP-Asp-Delig at 10 % solids, and then for SP-Asp-Delig and SP-Asp-LGal at 5 % solids. This suggested that the hydrophilization of lignin afforded by laccase-catalyzed grafting of gallic acid had the strongest effect at more dilute rheological regimes, with the SP-Asp-LGal h*, G¢, and G″ values being approximately 4-fold higher than those of SP-Asp. At 10 % and 15 % solids, the difference was much less pronounced, with the SP-Asp-LGal values on average being 1.2–1.7-fold higher than those of SP-Asp across the studied range of frequencies. On examination of the rheological behaviour of SP-Asp-Delig, it appeared that the substrate changes imparted by delignification not only had a large effect at the more dilute rheological regime of 5 % solids (with the h*, G¢, and G″ functions being on average a magnitude higher than those of SP-Asp), but also at the more concentrated rheological regime of 10 % solids. At this substrate concentration, a 2.5–3.9-fold gap remained between SP-Asp-Delig and SP-Asp, while at a 15 % solids concentration the SP-Asp-Delig values were reduced to around 2-fold those of the SP-Asp substrate. Thus, an increase in the relative fraction of hydrophobic biopolymers due to delignification and the concomitant increase in substrate hygroscopy resulted in significant increases in the rheological parameters h*, G¢, and G″ that persisted into high solids loadings. Interestingly, the delignification of the RMP-Asp and N-SP-Asp substrates did not appear to have this same effect. Instead, RMP-Asp-Delig and N-SP-Asp-Delig were nearly equivalent to their non-delignified variants in rheological behaviour at 15 % solids and only minor differences at 10 and 5 % solids, most noticeably so in the G″ functions. Although it is not clear why delignification of SP- 98 Asp, but not of RMP-Asp and N-SP-Asp, resulted in large increases in the rheological parameters, it may be that other physicochemical characteristics controlled the rheological behaviour of the RMP-Asp and N-SP-Asp substrates. It is possible for example that their larger particle dimensions (Table 3) overshadowed the influence of the increased hygroscopy following delignification. When the general dependency of the rheological parameters on solids loading for the different substrates was assessed it was apparent that the acidic steam-pretreated substrates, apart from SP-Asp-Delig, saw a near order of magnitude reduction between 15 % and 10 % solids. In contrast, the mechanically refined RMP-Asp and neutrally steam-pretreated N-SP-Asp substrates showed minimal reductions, only decreasing 1.2–2-fold over the same range. Going from a solids loading of 10 % to 5 %, the SP-Asp substrate exhibited a reduction of rheological parameters that was nearly two orders of magnitude, while the RMP-Asp and N-SP-Asp substrates displayed an approximate order of magnitude reduction. These results provided additional evidence that acidic steam-pretreatment results in substrates with favourable rheological characteristics, presumably due to the acidic hydrolysis and “smoothing” of the substrate surfaces (Dibble et al., 2011) and deposition of lignin at the substrate surfaces. 99 Table 6. Power law regression analysis of complex viscosity, storage modulus and loss modulus following logarithmic transformation over the linear viscoelastic region for aspen substrate variants at solids loadings (SL) of 15, 10, and 5 %. Substrate SL (%) Complex viscosity, h* (Pa×s) Storage modulus, G¢ (Pa) Loss modulus, G¢¢ (Pa) n* K* n¢ K¢ n¢¢ K¢¢ SP-Asp 15 -0.92 ± 0.01 9.2 ± 0.06 0.074 ± 0.01 11.0 ± 0.06 0.32 ± 0.03 8.7 ± 0.10 10 -0.91 ± 0.01 7.5 ± 0.03 0.074 ± 0.01 9.3 ± 0.03 0.32 ± 0.01 7.3 ± 0.04 5 -0.92 ± 0.06 3.1 ± 0.63 0.066 ± 0.06 5.3 ± 0.12 0.22 ± 0.02 3.9 ± 0.06 SP-Asp-Delig 15 -0.93 ± 0.02 9.9 ± 0.05 0.059 ± 0.02 11.8 ± 0.05 0.32 ± 0.04 9.4 ± 0.06 10 -0.94 ± 0.00 8.8 ± 0.09 0.046 ± 0.00 10.7 ± 0.09 0.30 ± 0.03 8.2 ± 0.08 5 -0.96 ± 0.05 5.8 ± 0.10 0.065 ± 0.04 7.7 ± 0.17 0.36 ± 0.01 5.5 ± 0.09 SP-Asp-LGal 15 -0.91 ± 0.01 9.7 ± 0.04 0.086 ± 0.01 11.6 ± 0.05 0.32 ± 0.02 9.3 ± 0.02 10 -0.90 ± 0.02 7.7 ± 0.10 0.088 ± 0.02 9.5 ± 0.10 0.26 ± 0.02 7.5 ± 0.15 5 -0.94 ± 0.04 4.9 ± 0.12 0.064 ± 0.02 6.8 ± 0.12 0.26 ± 0.01 4.9 ± 0.07 SP-Asp-LRes 15 -0.90 ± 0.02 9.4 ± 0.09 0.089 ± 0.02 11.2 ± 0.09 0.31 ± 0.00 9.1 ± 0.12 10 -0.90 ± 0.01 7.4 ± 0.06 0.094 ± 0.01 9.2 ± 0.06 0.20 ± 0.07 7.4 ± 0.23 5 -0.97 ± 0.05 3.9 ± 0.08 0.012 ± 0.06 5.7 ± 0.09 0.30 ± 0.02 4.0 ± 0.03 N-SP-Asp 15 -0.94 ± 0.01 10.8 ± 0.03 0.054 ± 0.01 12.6 ± 0.03 0.21 ± 0.01 10.3 ± 0.02 10 -0.94 ± 0.00 10.0 ± 0.06 0.056 ± 0.00 11.8 ± 0.06 0.23 ± 0.00 9.5 ± 0.08 5 -0.95 ± 0.01 7.7 ± 0.12 0.037 ± 0.01 9.6 ± 0.12 0.17 ± 0.03 7.2 ± 0.12 N-SP-Asp-Delig 15 -0.88 ± 0.00 10.6 ± 0.08 0.120 ± 0.01 12.4 ± 0.08 0.23 ± 0.01 10.6 ± 0.09 10 -0.88 ± 0.01 9.9 ± 0.04 0.116 ± 0.01 11.7 ± 0.05 0.31 ± 0.01 9.7 ± 0.07 5 -0.91 ± 0.04 7.7 ± 0.17 0.104 ± 0.02 9.6 ± 0.18 0.34 ± 0.00 7.5 ± 0.01 RMP-Asp 15 -0.93 ± 0.02 11.0 ± 0.14 0.064 ± 0.02 12.9 ± 0.15 0.17 ± 0.03 10.5 ± 0.08 10 -0.95 ± 0.00 10.6 ± 0.14 0.053 ± 0.00 12.5 ± 0.14 0.23 ± 0.07 9.9 ± 0.10 5 -0.99 ± 0.10 7.1 ± 0.04 0.098 ± 0.10 9.9 ± 0.06 0.16 ± 0.02 6.7 ± 0.04 RMP-Asp-Delig 15 -0.91 ± 0.01 10.9 ± 0.14 0.086 ± 0.01 12.7 ± 0.14 0.17 ± 0.01 10.7 ± 0.13 10 -0.91 ± 0.01 10.6 ± 0.18 0.086 ± 0.01 12.5 ± 0.18 0.26 ± 0.02 10.3 ± 0.16 5 -0.93 ± 0.05 7.6 ± 0.18 0.092 ± 0.02 9.5 ± 0.18 0.22 ± 0.01 7.4 ± 0.14 To further assess the influence of the h*, G¢, and G¢¢ functions of the aspen substrates, the data was fit to the power laws h* = K*(w)n*, G¢ = K¢(w)n¢, and G¢¢ = K¢¢(w)n″ (Choi and Chang, 2012). The values of the n and K power-law parameters for h*, G¢, and G″ at each solids loading were listed in Table 6, as determined through linear regression following log–log transformation. For all of the substrates, the complex viscosity power-law exponent n* (i.e. the slope of the log–log plot) remained relatively unchanged, suggesting that the degree of shear-thinning does not change over this solids loading range. No general trends were apparent for n¢ or n¢¢ individually as a function of solids loading across all substrates. However, comparing n¢ and n″, it appeared that n″ was generally several-fold higher than was n¢. This suggested that the loss modulus is more sensitive than the storage modulus to the oscillatory frequency, reflecting the shear-thinning behaviour of the 100 slurries. The K parameter (i.e. the intercept of the log–log plot) decreased consistently for all of the substrates with a decrease in solids loading, as expected from the curves in Fig. 23. However, for the RMP-Asp and N-SP-Asp substrates, the K parameter values only decrease slightly from 15 to 10 % solids, reflecting their largely similar rheological behaviour at these solids loadings, as noted above. K¢ was also greater than K″ at all solids loadings for all of the substrates, indicating primarily elastic rather than viscous behaviour. 15 % 10 % 5 % Figure 24. Loss tangent (tan δ; G″/G′) summary of small angle oscillatory sweeps of aspen substrate variants at 15 % (A), 10 % (B), and 5 % (C) solids. Further characterization of the relative viscoelasticity of the slurries is possible through determination of the loss tangent, or tan d, which describes the ratio of viscous to elastic portions of the deformation behaviour (i.e. G″/G′). This normalizes the viscoelastic behaviour across the different substrates. For all substrates at every solids loading, tan d remained well below 1 (Fig. 24), indicating that rheological behaviour was primarily elastic, as suggested earlier by the K″/K′ ratio. The behaviour of the acidic steam-pretreated substrates generally was the most liquid-like, having the highest tan d values. Delignification of RMP-Asp and N-SP-Asp resulted in a considerable increase in liquid-like behaviour, shifting the tan d curve up by up to 1.6-fold. The opposite shift occurred for delignification of SP-Asp. This likely reflected the removal of surface-deposited lignin that enabled lower friction at particle surfaces, thereby increasing viscous behaviour, as discussed earlier in Section 4.2. Overall, a 0.050.150.250.350.451 10 100Tan δFrequency (Hz)ASP-AspSP-Asp-DeligSP-Asp-LGalSP-Asp-LResN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig0.050.150.250.350.451 10 100Frequency (Hz)B0.050.150.250.350.451 10 100Frequency (Hz)C 101 general shift toward increased tan d values (increased liquid-like behaviour) was observed with decreasing solids loading for the SP-Asp substrates. In contrast, the tan d curves for the RMP-Asp and N-SP-Asp substrates were largely the same at each solids loading, indicating the highly solid-like behaviour of these substrates, even at a solids loading of 5 %. Beyond the frequency sweeps described above and the viscoelastic parameters derived from them, oscillatory rheometry also allows measurement of slurry yield stress through oscillatory amplitude sweeps. In this case the imposed stress is continuously increased until the G′ and G″ functions deviate from linearity (i.e. they exit the linear viscoelastic region). The yield stress of a slurry can then be defined as either the point of initiation of non-linearity or the crossover point between the G′ and G″ functions, i.e., the point at which tan d becomes greater than one (Dinkgreve et al., 2016). The latter definition is sometimes preferred since it defines the point at which there is a transition from predominantly solid to liquid-like behavior (Shih et al., 1999). This definition of oscillatory rheometry-determined yield stress was used in the work reported here. Using the oscillatory amplitude sweep method for yield stress determination, all of the aspen substrate variants were found to follow power-law relationships (as shown by the power-law fits for each substrate) over this range of solids loadings, apart from the RMP substrates (Fig. 25). The yield stress of RMP-Asp and RMP-Asp-Delig appeared to level off at around 10 % solids and was only slightly increased at 15 % solids. The mechanically refined RMP-Asp substrates were observed to have high bulk densities. Therefore, it is likely that most of the water in the slurry at 10 % solids was already absorbed into the bulk of the RMP substrates. Any further reductions in the water content therefore did not significantly alter inter-particle interactions at 15 % solids, resulting in only a slight increase in yield stress. 102 Figure 25. Yield stress scaling of aspen substrate variants with solids loading as determined by oscillatory rheometry on a log–log scale. Power law fits are shown, except for RMP-Asp and RMP-Asp-Delig, which did not appear to follow the power law relation. The reason for this deviation is discussed in the text. Figure 26. Comparison of yield stresses determined through unidirectional controlled deformation (CD) and oscillatory rheometry (OR), shown for acidic steam-pretreated aspen (SP-Asp) and neutral steam-pretreated aspen (N-SP-Asp). Solids loading is shown on a base-two log scale. In general, the yield stress profiles determined through oscillatory rheometry reflected the same order of substrates determined earlier through unidirectional rheometry (using the controlled 0.010.11104 8 16Yield stress (kPa)Solids loading (% by mass)SP-AspSP-Asp-LResSP-Asp-DeligSP-Asp-LGalN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig0.0010.010.11102 4 8 16Yield stress (kPa)Solids loading (% by mass)OR N-SP-AspCD N-SP-AspOR SP-AspCD SP-Asp 103 deformation, CD, method; Fig. 17). The CD yield stress curves suggested that the RMP-Asp substrates would eventually overtake the N-SP-Asp substrates at higher solids, as was observed at 10 % solids with oscillatory rheometry. Taking SP-Asp and N-SP-Asp as examples, it was apparent that the power-law relationships determined through the two different methods were highly similar in slope, but differed in their intersects on the log–log plot (Fig. 26). This suggested that both methods show the same scaling tendency of yield stress with solids loading, but provide different absolute values. In previous work that compared different methods for yield stress measurement, the G′ and G″ crossover method was found to provide the highest yield stress values, but the yield stress scaling was otherwise found to be same across the different methods (Dinkgreve et al., 2016). This reflected the findings made here. Therefore the oscillatory rheometry and controlled deformation methods seem to measure the same underlying phenomenon (i.e. of the slurry yielding), although assigning different absolute values, serving as a reminder that these methods are relative in nature. In summary, acidic steam-pretreated substrates were confirmed through oscillatory rheometry to display the most favourable slurry rheology over a 5–15 % solids range, characterized by low complex viscosity, low storage and loss moduli, low yield stresses, and high loss tangents (tan d). In contrast, retention of hemicellulose due to a lack of acid hydrolysis during neutralized steam-pretreatment resulted in highly unfavourable slurry rheology. These neutralized steam-pretreated substrates displayed highly elastic (solid-like) behaviour over the entire solids loading range, exhibiting no increase in the loss tangent even at 5 % solids. The mechanically pretreated aspen substrate variants likewise demonstrated decidedly elastic behaviour compared to the more viscous behaviour of the acidic steam-pretreated substrates over the solids loading range examined. It can be expected therefore that the neutralized steam-pretreated substrates and mechanically pretreated substrates will exhibit poor enzymatic liquefaction and mass transfer conditions at high solids loadings, as will be examined in the next section. 4.6 High-solids liquefaction of aspen substrate variants Having closely examined the rheology of the aspen substrate variants using oscillatory rheometry, their liquefaction at high solids (15 %) was next studied. Since the laccase-grafted substrates were studied in detail in section 4.3, they were left out of the analysis here and the focus was on the SP-Asp, N-SP-Asp and RMP-Asp substrates and their compositional differences. 104 Figure 27. Hydrolysis extent of aspen substrate variants during liquefaction at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). Table 7. Average hydrolysis rates of aspen substrate variants during enzymatic liquefaction at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). Substrate Timespan Ratea (mmol h-1) Rateb (percent h-1) Normalized ratec SP-Asp 0 – 3 h 1.19 4.34 1.00 3 – 6 h 0.90 3.27 0.75 6 – 9 h 0.82 3.00 0.69 SP-Asp-Delig 0 – 3 h 1.62 3.92 1.00 3 – 6 h 1.04 2.51 0.64 6 – 9 h 0.66 1.58 0.40 N-SP-Asp 0 – 3 h 1.34 5.05 1.00 3 – 6 h 0.52 1.95 0.39 6 – 9 h 0.66 2.47 0.49 N-SP-Asp-Delig 0 – 3 h 2.52 5.99 1.00 3 – 6 h 1.37 3.25 0.54 6 – 9 h 0.51 1.21 0.20 RMP-Asp 0 – 3 h 0.25 1.21 1.00 3 – 6 h 0.23 1.13 0.94 6 – 9 h 0.04 0.20 0.17 RMP-Asp-Delig 0 – 3 h 1.21 4.20 1.00 3 – 6 h 0.64 2.21 0.53 6 – 9 h 0.23 0.80 0.19 ammol of glucose; bpercent of theoretical glucose yield; cNormalized against the 0–3 h average rate 0102030400 3 6 9Hydrolysis extent (%)Time (h)SP-AspSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig 105 The aspen substrates were enzymatically hydrolyzed using a complete T. reesei cellulase cocktail for 3, 6, and 9 h, after which the reaction was terminated and the partially hydrolyzed substrates were collected for further analysis. In contrast to enzymatic hydrolysis at low solids (Fig. 18), the SP-Asp substrate showed the highest extent of hydrolysis following 9 h of hydrolysis (Fig. 27) and had the highest normalized average hydrolysis rates throughout the reaction (Table 7). Similarly, the N-SP-Asp substrate appeared to hydrolyse better at 15 % solids relative to the other substrates in comparison to their relative hydrolysis at 2 % solids. When the particle length reduction of the substrates during liquefaction was assessed (Fig. 28A), the SP-Asp substrates showed the most significant reductions in particle length, followed by the N-SP-Asp substrates and lastly the RMP-Asp substrates, which had minimal reductions in mean particle length. These differences in particle fragmentation during enzymatic hydrolysis were even more apparent when the mean particle lengths were normalized to the initial mean particle lengths of each substrate (Fig. 28B). Notably, each delignified variant showed reduced particle fragmentation when compared to its non-delignified variant. It is possible that the dehydration and fibrillary structure collapse following delignification (Ishizawa et al., 2009; Pihlajaniemi et al., 2016) affected dislocations, the sites at which particle fragmentation is thought to occur (Hidayat et al., 2012; Thygesen et al., 2011), thereby reducing the particle fragmentation efficacy. The more rapid and higher degree of particle fragmentation observed for the acidic steam-pretreated substrates appeared to confirm the benefit of the more viscous rheological behaviour of these substrates during high-solids enzymatic hydrolysis. This had been anticipated following the characterization via oscillatory rheometry in the previous section. 106 Figure 28. Particle size reduction of aspen substrate variants during hydrolysis at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3) measured with optical number-based fiber analyzer. (A) Mean particle length progression over time. (B) Mean particle lengths normalized to the mean particle length of the non-hydrolyzed substrates. The partially hydrolyzed aspen substrate variants were next characterized using oscillatory rheometry to examine the development of viscoelastic parameters over the course of enzymatic liquefaction (Fig. 29). The complex viscosity, storage modulus, and elastic modulus of each substrate at 3, 6, and 9 h were determined as a function of oscillatory frequency in comparison to the unhydrolyzed (0 h) substrate. The SP-Asp substrate exhibited the largest changes in the rheological parameter curves, especially at 9 h, reflecting the relatively large hydrolysis extent and degree of fragmentation. However, at 3 h, little change was observed for the complex viscosity of SP-Asp, despite ~15 % hydrolysis and a ~28 % reduction in mean particle length. Nonetheless, a slight reduction in the storage modulus and a concurrent increase in the loss modulus could be seen, especially at low oscillatory frequencies. This will be discussed further below with respect to the loss tangent (tan d) curves. The SP-Asp-Delig, N-SP-Asp, and RMP-Asp substrates showed steady reductions in their rheological parameters, while the N-SP-Asp-Delig and RMP-Asp-Delig substrates exhibited a large change following 3 h of hydrolysis, with minimal changes thereafter. These liquefaction trends did not appear linked to the composition of the substrates, given the large substrate differences within these two groups. The rapid initial reduction of the parameters followed by minimal reductions for 0.00.20.40.60.81.00 3 6 9Mean particle length (mm)Time (h)A SP-AspSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-Delig0.30.40.50.60.70.80.91.00 3 6 9Normalized mean particle length (mm)Time (h)B 107 the N-SP-Asp-Delig and RMP-Asp-Delig substrates may instead reflect modifications of the particle surfaces. This could be a result of the hydrolysis of loosely associated cellulose fibrils and the more amorphous regions that tend to hydrolyze rapidly in the early stages of enzymatic hydrolysis (Hildén et al., 2005; Mansfield et al., 1997). Although such surface ‘smoothing’ might be expected to contribute to liquefaction, the development of rheological parameters appeared to stall following the initial reductions. 108 η* (kPa∙s) G′ (kPa) G′′ (kPa) SP- Asp SP-Asp-Delig N-SP-Asp N- SP-Asp- Delig RMP -Asp RMP -Asp-Delig Frequency (Hz) 0.010.11101001 10 100A 0 h3 h6 h9 h0.111010010001 10 100B0.111010010001 10 100C0.010.11101001 10 100D0.111010010001 10 100E0.111010010001 10 100F0.010.11101001 10 100G0.111010010001 10 100H0.111010010001 10 100I0.010.11101001 10 100J0.111010010001 10 100K0.111010010001 10 100L0.010.11101001 10 100M0.111010010001 10 100N0.111010010001 10 100O0.010.11101001 10 100P0.111010010001 10 100Q0.111010010001 10 100R 109 Figure 29. Oscillatory rheological characterization of aspen substrate variants over the course of enzymatic hydrolysis at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). Complex viscosity (η*) (first column; A, D, G, J, M, P), storage modulus (G′) (second column; B, E, H, K, N, Q) and loss modulus (G′′) (third column; C, F, I, L, O, R) are shown for each substrate across the rows. As discussed earlier, the loss tangent (tan d) might provide additional insights into the liquefaction of biomass slurries, as it can be considered a normalized descriptor of the relative viscous versus elastic behaviour of viscoelastic materials. Both the SP-Asp and SP-Asp-Delig substrates showed clear tendencies toward viscous behaviour (with an increase in tan d), especially at lower oscillatory frequencies (Fig. 30). At a frequency of 1 Hz, the tan d for SP-Asp increased from 0.11 ± 0.00 at 0 h to 0.18 ± 0.01 at 3 h, 0.27 ± 0.01 at 6 h, and then decreased slightly to 0.25 ± 0.02 at 9 h (Fig. 30A). For the SP-Asp-Delig substrate, the tan d increased from 0.10 ± 0.00 at 0 h to 0.18 ± 0.01 at 3 h, 0.24 ± 0.01 at 6h, and 0.27 ± 0.01 at 9 h (Fig. 30B). Figure 30. Loss tangent (tan δ; G″/G′) summary for the small angle oscillatory sweeps of the aspen substrate variants after 0, 3, 6, and 9 h of enzymatic hydrolysis at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3). 00.10.20.30.40.51 10 100Tan δFrequency (Hz)A 0 h3 h6 h9 h00.10.20.30.40.51 10 100Tan δFrequency (Hz)B00.10.20.30.40.51 10 100Tan δFrequency (Hz)C00.10.20.30.40.51 10 100Tan δFrequency (Hz)D00.10.20.30.40.51 10 100Tan δFrequency (Hz)E00.10.20.30.40.51 10 100Tan δFrequency (Hz)FSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig RMP-Asp RMP-Asp-Delig 110 In contrast, the increase in viscous behaviour during enzymatic liquefaction for the N-SP-Asp and RMP-Asp substrates was only evident at higher oscillatory frequencies (Fig. 30C–F). For these neutrally steam-pretreated and mechanically refined substrates, the delignified variants showed the most significant increase in viscous behaviour. This was likely as a result of their higher digestibility and therefore greater extent of hydrolysis (Fig. 27). The greater the extent of hydrolysis, the greater the extent of solubilisation of carbohydrates, and thus the lower the active insoluble solids content, thereby causing rheological behaviour to become more viscous (liquid-like) in nature. Ultimately, the yield stress of biomass slurries is the rheological parameter with the most practical significance as it is directly instructive toward the minimum mixing force required to enable slurry movement. Therefore, yield stress measurements were conducted on all substrates using oscillatory stress sweeps, as exemplified using SP-Asp in Fig. 31, and summarized for all substrates in Fig. 32. Figure 31. Example of yield stress determination from oscillatory stress sweeps, shown here for steam-pretreated aspen (SP-Asp). Stress sweeps were done at a frequency of 10 Hz at a measuring duration of 5 s. The arrow indicates the progression of enzymatic hydrolysis. The yield stress was taken as the intersection of the storage (filled symbols) and loss (empty symbols) moduli curves, averaged over three replicates. 0.010.11101000.01 0.1 1 10G′, G′′(kPa)Stress amplitude (kPa)0 h 3 h 6 h 9 h 111 As noted earlier, the SP-Asp substrate showed little change in complex viscosity following 3 h of hydrolysis, while the loss tangent suggested an increase in viscous behaviour. This was also reflected in the yield stress of the SP-Asp at 3 h, where, despite having nearly identical storage and loss moduli values (Fig. 31), the yield stress was reduced to 2.26 ± 0.19 kPa, down from 3.21 ± 0.07 kPa for the unhydrolyzed substrate (Fig. 32). While all other substrates also saw considerable reductions in yield stress, none were reduced below 1 kPa. All of the other substrates, other than SP-Asp-Delig, retained a yield stress greater than 4 kPa following 9 h of hydrolysis. These high yield stresses suggested poor mass transfer conditions, and this was reflected in the average hydrolysis rates over the course of enzymatic liquefaction (Table 7). While not having the highest absolute hydrolysis rate initially (from 0–3 h), the SP-Asp substrate maintained the highest rate of hydrolysis during the rest of the liquefaction. From 6–9 h, SP-Asp still had a normalized reaction rate of 0.69, while the N-SP-Asp-Delig, RMP-Asp and RMP-Asp-Delig substrates were reduced to a normalized rate of less than 0.2. The SP-Asp-Delig substrate registered the second-lowest yield stresses (Fig. 32) and accordingly exhibited relatively high normalized reaction rates that reduced only gradually from 0.64 between 3–6 h to a normalized rate of 0.40 between 6–9 h. In comparison, the N-SP-Asp substrate showed a large reduction in reaction rate, initially to a normalized rate of 0.39 between 3–6 h, which then recovered to a normalized rate of 0.49 between 6–9 h. This was likely due to improved mass transfer conditions after 6 h of hydrolysis and concomitant material dilution. This was also reflected in the improved rate of yield stress reduction from 6–9 h (Fig. 32). In the liquefaction experiments performed here, care was taken to ensure effective dispersal of the enzymes at the start of the reaction. This was achieved through separate preparation of the solid (substrate) and liquid (water, buffer, and enzyme) portions prior to their combination, ensuring effective absorption of the reaction medium and the enzymes into the biomass. As a result, all of the substrates should initially have been relatively unaffected by mass transfer limitations. However, following initial hydrolysis, localized accumulation of hydrolysis products and poor subsequent dispersal of enzymes would likely have restricted hydrolysis of substrates with high yield stresses, where poor mass transfer conditions prevailed throughout the liquefaction stage. This was reflected in the rapid decline of hydrolysis rates (Table 7) of the high-yield-stress substrates RMP-Asp, RMP-Asp-Delig and N-SP-Asp-Delig. However, the N-SP-Asp substrate seemed to oppose this trend despite having the highest yield stress values throughout hydrolysis. This was possibly due to its relatively high particle fragmentation (Fig. 28) and concomitantly increased accessible surface area for enzymatic hydrolysis. 112 Overall, we confirmed that slurry rheological behaviour is directly related to liquefaction efficiency. It is evident that high slurry yield stresses limit enzymatic liquefaction through poor mass transfer kinetics, even when enzymes were thoroughly dispersed throughout the slurry at the start of the reaction. Pretreatments that result in substrates that have low slurry yield stresses, such as acidic steam-pretreatment, are therefore especially beneficial for achieving effective high-solids cellulose hydrolysis. In contrast, the substrates characterized by challenging rheological behaviour (i.e. the RMP and N-SP substrates) showed poor enzymatic liquefaction and retained high yield stress throughout the reaction, resulting in stagnating hydrolysis rates following the initial thorough dispersal of enzymes. Figure 32. Yield stress reduction over the course of enzymatic hydrolysis of aspen substrate variants at 15 % solids with 10 mgprotein gglucan-1 T. reesei enzyme preparation (CTec3) as determined through oscillatory stress sweeps, shown on a semi-log scale. 4.7 The degree of the solids effect in the hydrolysis of the aspen substrates In the previous section, the early stages of enzymatic hydrolysis were assessed rheologically to try to characterize and compare the enzymatic liquefaction behaviour of the various pretreated aspen substrates. The practical significance of a substrate’s rheological and liquefaction behaviour lies in the impact these processing characteristics will have on the time-to-target for an industrial process. In effect, the more challenging the lignocellulosic material is to handle and mix, the slower its enzymatic 0.010.11101000 3 6 9Yield stress (kPa)Time (h)SP-AspSP-Asp-DeligN-SP-AspN-SP-DeligRMP-AspRMP-Asp-Delig 113 hydrolysis rate, and the longer its time-to-target. It is therefore important to examine how well a given substrate scales to high solids loadings, or in other words, how influential the ‘solids effect’ is. As mentioned earlier, the ‘solids effect’ can be summarised by the observation that enzymatic hydrolysis yields decrease with increasing solids loadings (Jørgensen et al., 2007). While the solids effect has been observed to affect different substrates to various extents (Kristensen et al., 2009), the underlying reasons for this differential scaling of the solids effect has not been fully explored. Figure 33. Influence of solids loading on the extent of enzymatic hydrolysis (A) and the normalized extent of hydrolysis (B), normalized to the maximum yield at 2.5 % solids. Reactions were run for 48 h with 10 mgprotein gglucan-1 of a T. reesei cellulase cocktail (CTec3). Quadratic fits to the data are shown. To assess the degree to which each of the pretreated aspen substrates was affected by the solids effect, the substrates were hydrolyzed for 48 h at 10 mgprotein gglucan-1 using a T. reesei cellulase cocktail (CTec3) at solids loadings from 2.5 to 20 %, at a reaction volume of 15 ml in horizontally rotated 35-ml serum bottles (Fig. 33A). The RMP-Asp substrate was not included in these experiments due to it having very low digestibility and not reaching a sufficient extent of hydrolysis that would warrant its use as a biorefining substrate. The data were fit to second degree polynomial (quadratic) functions to model the reduction in the extent of hydrolysis (yield) with increasing solids loading. The SP-Asp substrate appeared to have a near-linear reduction in the extent of hydrolysis as a function of solids loading over the range examined. Similarly, the SP-Asp-Delig substrate showed a near-linear dependency on the extent of hydrolysis, albeit with a much greater reduction per unit 204060801000 5 10 15 20Hydrolysis extent (%)Solids loading (%)ASP-AspSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-Asp-Delig0.30.40.50.60.70.80.91.02.5 7.5 12.5 17.5 22.5Normalized hydrolysis extentSolids loading (%)B 114 solids loading. The extent of SP-Asp-Delig hydrolysis was reduced ~2.3 percentage points per 1 % increase in solids loading, in comparison to ~1.2 percentage points per 1 % increase in solids loading for the SP-Asp substrate. The scaling of the extent of hydrolysis with solids loading for the rest of the substrates (N-SP-Asp, N-SP-Asp-Delig, and RMP-Asp-Delig) was well described by quadratic functions. This showed an increasingly rapid reduction of the extent of hydrolysis with increasing solids loading. This was especially apparent when the extent of hydrolysis was normalized to the maximum extent of hydrolysis at a 2.5 % solids loading (Fig. 33B). Normalization of the data reinforced the difference in hydrolysis yield scaling of the SP-Asp and other substrates, especially at the highest solids loadings. While hydrolysis of the SP-Asp substrate at a 20 % solids loading resulted in a normalized fractional extent of hydrolysis of 0.78, the next highest extent of hydrolysis at this solids loading, reached by SP-Asp-Delig, was 0.50. At the same solids loading, the RMP-Asp-Delig substrate only reached a normalized fractional extent of hydrolysis of 0.36. It was apparent that the hydrolysis yield of the SP-Asp substrate scaled most favourably with solids loading, or in other words, the SP-Asp substrate was least affected by the solids effect. Tying these results back to the rheological characterization of liquefaction in the previous section, the SP-Asp substrate was found to have the lowest initial yield stress and resulted in the most efficient liquefaction. Thus, not surprisingly, the SP-Asp substrate performed best at high solids loadings. In contrast, the other substrates showed much higher initial yield stresses and poorer liquefaction, which indicated that these substrates were strongly influenced by the solids effect. While the extent of hydrolysis of the N-SP-Asp-Delig substrate was comparable to the SP-Asp substrate at low solids loadings (~90 % of theoretical yield), its hydrolysis yield dropped precipitously at solids loadings greater than 10 %, and reached only 45 % hydrolysis at 20 % solids loading in comparison to 70 % for the SP-Asp substrate. These results showed the direct influence that rheological characteristics have on achieving effective enzymatic hydrolysis and the benefit gained by producing a substrate that has favourable rheological behaviour. 4.8 Conclusions Differential pretreatment of aspen poplar chips was used to produce eight substrates that differed in the amount and characteristics of cellulose, hemicellulose, and lignin. These substrates were used to assess the possible influence that the various substrate characteristics might have on slurry rheology, enzymatic liquefaction, and hydrolysis efficiency at high solids loadings. 115 Modification of steam-pretreated aspen lignin through laccase-catalyzed grafting of phenolic compounds resulted in the modification of the unproductive binding potential. This increased cellulose hydrolysis yields at a low substrate loading, likely through the addition of hydrophilic carboxylic acid groups while reducing hydrolysis yields through incorporation of hydrophobic benzenediol groups. However, when hydrolysis was tested at higher substrate loadings (10 % solids), the grafted substrates showed significantly reduced hydrolysis yields compared to the original steam-pretreated substrate. This was likely due to the large increase (nearly two-fold) in slurry yield stress at 10 % solids caused by laccase-grafting. This worsened mass transfer limitations and reduced hydrolysis efficiency. These results reinforce the hypothesis that substrate digestibility needs to be tested at industrially relevant conditions (i.e. high solids loadings) to fully appreciate the influence of the various factors that limit effective enzymatic hydrolysis. Using isothermal thermogravimetric analysis, a correlation between substrate composition and substrate–water interactions was determined. Specifically, the relative hydrophilic biopolymer (cellulose and hemicellulose) content was correlated with the free water boundary solids loading. It was found that, the more hygroscopic the substrate is, the lower the solids loading at which all free water in the slurry is taken up by the substrate. Extensive rheological characterization was conducted on the differentially pretreated aspen substrates. Delignification generally caused an increase in yield stress, likely due to increased hygroscopy. This was especially the case for the acidic steam-pretreated substrate (SP-Asp). In general, substrates that had been steam-pretreated under acidic conditions had the most favourable rheological characteristics, followed by steam-pretreatment under neutral conditions. The least favourable were the mechanically pretreated substrates. Over a range of 5–15 % solids, the neutrally steam-pretreated and mechanically pretreated substrates registered yield stresses that were more than an order of magnitude greater than those of the acidic steam-pretreated substrates. The high yield stresses of these substrates was likely due to higher particle lengths and unfavourable particle surface properties. When the aspen substrate variants were subjected to enzymatic liquefaction at a high solids loading (15 % solids), rheological changes, such as changes in viscosity, storage modulus, loss modulus and yield stress of the substrates indicated that the substrate with the most favourable rheology, the acidic steam-pretreated SP-Asp substrate, liquefied most efficiently. The observed rapid reduction in the rate of hydrolysis during the liquefaction stage of high-yield-stress substrates, 116 following initial thorough dispersal of enzyme, indicated the critical role that efficient mass transfer plays in promoting efficient hydrolysis at high solids loadings. By assessing the ‘solids effect’ for each substrate (i.e. how much the hydrolysis yield was reduced with increasing solids loading), it was shown that the more favourable the rheological characteristics of a substrate, the less pronounced the solids effect. This was most noticeable with the substrate with the lowest yield stress, SP-Asp, where 70% of the substrate was hydrolyzed at a solids loading of 20 % (m/m). The hydrolysis yield of the high-yield-stress N-SP-Asp-Delig substrate was only 45 % at this same solids loading, even though, at a 2.5 % solids loading, the two substrates had equivalent hydrolysis yields (~90 %). Thus, it was apparent that slurry rheological behaviour directly influences high-solids hydrolysis efficiency. 117 5 Characterizing the mechanisms of enzymatic liquefaction 5.1 Background Enzymatic liquefaction of lignocellulosic substrates is increasingly recognized as an important process phase in high-solids hydrolysis (Cardona et al., 2015; Jørgensen et al., 2007). Furthermore, as demonstrated in the previous sections, enzymatic liquefaction is critical in determining the efficacy of high-solids enzymatic hydrolysis. This suggests that improving enzymatic liquefaction is an important strategy for overcoming the challenges of conducting bioconversion at industrially relevant conditions. However, relatively little is known mechanistically of how enzymatic hydrolysis of the substrate leads to yield stress/viscosity reductions (as summarized in the Introduction, Section 1.6). The main mechanism by which viscosity is reduced during enzymatic digestion of lignocellulose has traditionally been thought to be material dilution, which is the reduction of the insoluble solids loading through enzymatically catalyzed hydrolysis of insoluble polysaccharides to soluble species (Roche et al., 2009a). However, recent findings (Skovgaard et al., 2014) have indicated that liquefaction and saccharification may in fact be separate processes, with liquefaction possibly being achieved by substrate deconstruction mechanisms that are distinct from the hydrolysis of bulk cellulose and thus not due to material dilution alone. These authors showed that enzyme-induced particle fragmentation early in the reaction precedes much of the cellulose solubilisation (with conversion extents as little as 5 %), and which was found to correlate well to viscosity reduction. The authors suggested therefore that particle fragmentation at fiber dislocations caused viscosity reduction (Skovgaard et al., 2014). Other studies have suggested that a loss of water retention as a result of enzymatic substrate deconstruction plays a role in liquefaction (Viamajala et al., 2009), as well as alteration of interparticle interactions due to cellulase action on particle surfaces (Dibble et al., 2011). However, direct evidence for these mechanisms is sparse, and in general, the nature and contribution of the different deconstruction mechanisms that may lead to viscosity reduction have yet to be fully resolved. Gaining a better understanding of these mechanisms could inform ways to improve enzymatic liquefaction and help overcome the rheological challenge of high-solids bioconversion. To this end, this part of the thesis used various lignocellulosic substrates with different treatment histories and properties to try to identify individual mechanisms that may be occurring as part of enzymatic liquefaction. 118 5.2 Tracking substrate properties over the course of enzymatic liquefaction To enable a detailed characterization of the physicochemical changes occurring during enzymatic hydrolysis that lead to slurry liquefaction, steam-pretreated poplar (SPP200) was enzymatically hydrolyzed to various extents and collected following termination of the reaction to allow further measurement of substrate properties. A nearly pure cellulose substrate, HW-DP, was similarly assessed to minimise the influence of lignin and hemicellulose on the liquefaction of cellulose. It was apparent that the glucose yield of the two substrates was comparable, reaching a hydrolysis extent of around 75 % after 24 h (Fig. 34). Figure 34. The extent of hydrolysis and yield stress over the course of enzymatic hydrolysis of (A) steam-pretreated poplar (SPP200) and (B) hardwood dissolving pulp (HW-DP) at 10 % solids with 20 mgprotein gglucan-1 of the enzyme preparation CTec3. The extent of hydrolysis was determined through HPAEC-PAD analysis of the hydrolysates and yield stress was determined using the controlled deformation method averaged over five replicates. However, as detailed in Section 3, the yield stress profiles of these two substrates were considerably different, with the HW-DP substrate showing considerably higher yield stress values than did the SPP200 substrate. Under the conditions studied here, the yield stress of HW-DP was roughly two-fold that of the SPP200 substrate (Fig. 34). Nonetheless, likely due to the increased enzymatic digestibility as a result of the low lignin content and increased accessibility, the HW-DP substrate liquefied rapidly, occurring over the same timespan as the SPP200 substrate and reaching full liquefaction (at which a yield stress could no longer be detected) after 7 h of enzymatic hydrolysis. 02550751000400800120016000 6 12 18 24Hydrolysis extent (%)Yield stress (Pa)Time (h)A Yield stressHydrolysis extent02550751000400800120016000 6 12 18 24Hydrolysis extent (%)Yield stress (Pa)Time (h)BSPP200 HW-DP 119 5.2.1 Cellulose accessibility and crystallinity Prior to assessing the various mechanisms that have been proposed to account for enzymatic liquefaction, the first objective was to examine whether there is a delineation between the liquefaction and saccharification stages of enzymatic hydrolysis. It has been suggested (Arantes and Saddler, 2011; Hall et al., 2010) that accessibility and crystallinity are two of the most important cellulose characteristics that determine enzymatic digestibility. Since liquefaction is thought to occur as a result of mechanisms that are distinct from general saccharification of the bulk cellulose and can occur with minimal (<5 %) conversion extents (Skovgaard et al., 2014), it might be expected that the substrate modification occurring due to enzymatic liquefaction also influences these properties. It has also been suggested that liquefaction may be occurring as part of a cellulose disruption/loosening stage of enzymatic hydrolysis, sometimes termed amorphogenesis (Arantes and Saddler, 2010). Figure 35. Cellulose accessibility of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) over the course of enzymatic digestion expressed as maximum adsorption per gram of substrate over time (A and B) and per gram of cellulose as a function of glucan hydrolysis extent (A′ and B′), as determined through stilbene dye-binding (Direct Orange). By testing the accessibility of cellulose through a stilbene dye-binding assay that has been shown to have high specificity and reproducibility toward assessment of lignocellulosic substrates (Chandra and Saddler, 2012), it was apparent that a dramatic reduction in accessibility (determined as the maximum adsorption from adsorption isotherms) occurs over the course of enzymatic hydrolysis 5070901101300 6 12 18 24Maximum adsorption(mg g substrate-1)Time (h)A5070901101300 6 12 18 24Maximum adsorption (mg g substrate-1)Time (h)BSPP200 HW-DP 0501001500 20 40 60 80Conversion extent (%)A′0501001500 20 40 60 80Conversion extent (%)B′ 120 of SPP200 (Fig. 35A) while a slight reduction occurs during the hydrolysis of HW-DP (Fig. 35B). However, when plotted against the extent of hydrolysis, it was apparent that for both substrates the reduction in maximum adsorption closely correlated with the extent of cellulose hydrolysis (Fig. 35A′ and 35B′). Since the accessibility measurement is determined as the maximum adsorption per gram of substrate, the linear correlation between hydrolysis and maximum adsorption means that the reduced apparent accessibility is simply due to the increased fraction of lignin following cellulose hydrolysis. It is likely that the difference in maximum adsorption losses during enzymatic hydrolysis between HW-DP and SPP200 can be explained by the fact that the HW-DP substrate comprises 93 % cellulose. Therefore, the relative reduction in maximum adsorption is small (being reduced from 86 to 70 mg g-1), while due to its 34 % lignin content, the relative reduction in maximum adsorption for SPP200 is considerable (from 121 to 54 mg g-1). Therefore, cellulose accessibility per unit of cellulose does not appear to change over the course of enzymatic hydrolysis, nor does it indicate correspondence to a ‘liquefaction’ or ‘amorphogenesis’ stage. Previous work that looked at the crystallinity of a hardwood dissolving pulp, similar to the one used here, over the course of enzymatic hydrolysis showed that, following a rapid initial increase, crystallinity remained constant (Gourlay et al., 2015). This was reasoned to be the result of the rapid hydrolysis of highly accessible amorphous cellulose fibrils, followed by sequential hydrolysis of crystalline cellulose layers. Crystallinity has been shown to remain constant during enzymatic hydrolysis of microcrystalline cellulose (Avicel), without an initial increase in crystallinity because of a lack of amorphous fibrils in the highly crystalline Avicel substrate (Hall et al., 2010). Similarly, no influence on crystallinity was found when following partial enzymatic hydrolysis of fully bleached kraft pulps (Ramos et al., 1999). To examine if the same is true with thermochemically pretreated substrates containing lignin and hemicellulose, the crystallinity of the SPP200 substrate was determined using X-ray diffraction analysis in the form of a crystallinity index, CrI (Fig. 35). It was apparent that the crystallinity of SPP200 decrease steadily over the course of enzymatic hydrolysis (Fig. 35A). However, because CrI provides an averaged value, incorporating the influence of hemicellulose and lignin, it is not a specific cellulose crystallinity value. Accordingly, when the CrI was plotted against the extent of hydrolysis, a clear linear relationship was apparent (Fig. 35B). This suggested that the decrease in CrI was due to the removal of cellulose and the corresponding relative increase in lignin and hemicellulose. As was the case with dissolving-grade pulp and microcrystalline cellulose, the crystallinity of cellulose in thermochemically pretreated substrates appeared to remain constant over the course of enzymatic hydrolysis. Thus, no relationship to enzymatic liquefaction was 121 apparent, and instead the results provide evidence that no distinct liquefaction stage exists as assessed at a nanoscopic scale via the accessibility and crystallinity of cellulose. Figure 36. Crystallinity index of steam-pretreated poplar (SPP200) over the course of enzymatic hydrolysis (A) and its relationship to cellulose conversion (B) as determined by X-ray diffraction. SPP200 was hydrolyzed at 10 mgprotein gcellulose-1 CTec3 at 2 % solids in 2-ml tubes and reactions were terminated by heat-inactivation. 5.2.2 Particle fragmentation Having ruled out changes at the nanoscopic scale (accessibility and crystallinity) being related to enzymatic liquefaction, the other mechanisms proposed in the literature were next assessed. Given the recent focus of particle fragmentation as a primary mechanism of enzymatic hydrolysis (Skovgaard et al., 2014; Thygesen et al., 2014; Tozzi et al., 2014), attention was first placed on the development of particle size distributions of SPP200 and HW-DP over the course of enzymatic hydrolysis (Fig. 37). However, the particle size analysis employed (Fiber Quality Analyzer) was limited to detection of particles greater than 72 μm in length. It was apparent from the frequency distributions that a considerable amount of the particles were below detectable limits for both substrates (Fig. 37A and 37B). Nevertheless, given the disproportionate influence of longer biomass fibers in establishing fiber networks (with the crowding number scaling with the square of fiber length; Kerekes and Schell, 1992), this method still provided a useful characterization of the fiber network-forming capability of the substrates and hence the slurry rheology dynamics during enzymatic liquefaction. 30354045500 6 12 18 24CrI (%)Time (h)A1 h3 h5 h24 h30354045500 25 50 75 100CrI (%)Hydrolysis extent (%)B 122 SPP200 HW-DP Figure 37. Particle length probability distributions of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) over the course of hydrolysis shown as probability density functions (A, B) and cumulative distribution functions (A′, B′). (C) Comparison of the cumulative distributions of HW-DP and SPP200 at full liquefaction (τy<20 Pa; 5 h). 02468100 0.5 1 1.5Frequency (%)Particle length (mm)A 0 h 1 h 3 h 5 h 7 h 9 h 24 h02468100 0.5 1 1.5Frequency (%)Particle length (mm)B0204060801000 0.5 1 1.5Frequency (%)Particle length (mm)A′0204060801000 0.5 1 1.5Frequency (%)Particle length (mm)B′2550751000 0.5 1Frequency (%)Particle length (mm)CHW-DPSPP200 123 Given the precise manufacturing and product quality requirements of dissolving-grade pulps, particularly regarding particle size (Gehmayr et al., 2011), the HW-DP substrate was found to have a more apparent Gaussian distribution and relatively low variance in comparison to the disperse distribution of SPP200 particles. However, during enzymatic hydrolysis, both substrates showed clear reductions in particle length, especially the largest particles. After three hours, the SPP200 substrate already reached close to its final (24 h) particle size distribution, while the HW-DP particle fragmentation was slower and a leveling off of particle length was not apparent until 7 h. This was reflected in both the probability density (Fig. 37A and 37B) and cumulative distribution functions (Fig. 37A′ and 37B′). The particle size distribution of HW-DP showed little change following 1 h of hydrolysis, probably as a result of the initially poorer mass transfer conditions given its high yield stress. If particle fragmentation is intricately linked to liquefaction, it is possible that full liquefaction is achieved when particle lengths are reduced below a threshold amount, below which the particles can no longer form a coherent network. When the cumulative distribution functions of SPP200 and HW-DP at the point of full liquefaction were compared (defined here as τy<20 Pa, given that this value is at the edge of the controlled deformation method’s sensitivity for yield stress), this possibility seems to be supported by the congruency of the functions (Fig. 37C). It is worth noting that the point of full liquefaction corresponded to similar mean particle lengths for both substrates, occurring at 188 μm for SPP200 and 175 μm for HW-DP (Fig. 38A). Although both substrates saw further fiber fragmentation beyond the point of full liquefaction, these reductions were minimal compared to the reductions preceding it. 124 B Hydrolysis time (h) 0 1 3 5 7 9 24 SPP200 HW-DP Figure 38. Particle fragmentation over the course of hydrolysis of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) (A) and the result on sedimentation measurements (B), performed on 10 mg dry mass of substrate at each time point. Sedimentation was done overnight in water following staining with Direct Orange 15 dye of HW-DP to enhance contrast. Fiber network formation can be examined through fiber settling (or sedimentation), a method that has been used in the pulp and paper sector as a means to understand the physical mechanisms of particle interactions (Gourlay et al., 2018; Martinez et al., 2001; Young et al., 2006). After applying sedimentation measurements to the hydrolyzed SPP200 and HW-DP samples, the influence of enzymatic hydrolysis on fiber network formation was evident (Fig. 38B). While an equivalent mass of substrate was present in each measurement shown in Fig. 38B, the ability to form a fiber network was increasingly impeded with increasing enzymatic hydrolysis while the volume occupied by the fibers was decreased. Similar observations on the influence of enzymatic hydrolysis on fiber sedimentation have been made previously with a dissolving-grade pulp (Gourlay et al., 2015). The sedimentation of the non-hydrolyzed (t0) SPP200 and HW-DP substrates was quite different, with the sedimentation height of HW-DP being more than 2.6-fold greater than that of the SPP200 substrate. This discrepancy in sedimentation behaviour occurred despite the similar mean particle length of the two substrates, which was 539 μm for SPP200 and 565 μm for HW-DP. The mean particle aspect ratios (22.2 for SPP200 compared to 36.3 for HW-DP; 1.64-fold greater) also do not seem to fully account for the observed differences in fiber network formation. What might at least partially account for this difference in sedimentation is that narrow particle size distributions have been noted to reduce particle packing (Wiman et al., 2011). It is also likely that other factors not detected by the particle size analyzer influenced fiber network formation, such as surface roughness 0.00.20.40.60 6 12 18 24Particle length (mm)Time (h)ASPP200HW-DP 125 and interfiber friction forces (Huang et al., 2009), as well as extent of flocculation (Hearnshaw et al., 2004; Kerekes and Schell, 1992). Although further sedimentation experiments may be useful to probe interparticle interactions, it is not clear if examination of fiber network formation through sedimentation measurements (which is done at low solids loadings) will actually reflect the behaviour of slurries at high solids loadings. To further examine whether the point of liquefaction relates to a threshold particle length, SPP200 was enzymatically hydrolyzed at a solids loading of 17.5 % with cellulase at doses between 7.5–60 mgprotein gcellulose-1 (Fig. 39). It was apparent that complete liquefaction was achieved with the 60, 30, and 15 mg cellulase treatments, in each case corresponding to a similar mean particle length of 158 ± 4 μm. While particle fragmentation was clearly slower with the 15 mg treatment, full liquefaction was still achieved once this apparent threshold mean particle length was reached. In contrast, the 7.5 mg treatment never achieved sufficient particle fragmentation and did not fully liquefy, leveling off at a mean particle length of 242 ± 5 μm. These data again support the notion of a threshold mean particle length, below which insufficient interparticle interactions occur to allow fiber network formation. It is worth noting that the threshold mean particle length for liquefaction of SPP200 at 17.5 % solids was lower than at 10 % solids (158 μm and 188 μm, respectively). Perhaps due to the increased amount of insoluble material present at 17.5 % solids, additional particle fragmentation was required to eliminate fiber network formation and to achieve full liquefaction. The crowding number equation (in the form of N = (πCmL2)/6w, where Cm is the consistency expressed as a fraction, L is the fiber length, and w is the fiber coarseness; Kerekes and Schell, 1992), could partially explain this observation as an increase in solids loading would increase the crowding number and thus also increases interparticle interactions. The increase in the Cm term would therefore need to be offset by a decrease in the length (L) term in order to achieve the same reduction in fiber network formation. 126 Figure 39. Particle fragmentation during enzymatic hydrolysis of steam-pretreated poplar (SPP200) at 17.5 % solids with different doses of enzyme (CTec3), as indicated. The visual point of liquefaction for each treatment is indicated by the orange frame surrounding the data point. Data before 16 h not shown for simplification. However, this interpretation of liquefaction through fiber network formation and the crowding number is complicated by the fact that cellulases have been shown to modify fibers/particles in ways other than just by fiber fragmentation. For example, enzyme action is known to alter substrate water sorption, causing swelling and increases in particle width (Arantes et al., 2014; Lecourt et al., 2010; Wang et al., 2012a). Returning to the comparison of SPP200 and HW-DP, particle width was indeed seen to increase considerably in the early stages of enzymatic hydrolysis (Fig. 40). The observed increase in particle width due to swelling results in an increase in the effective volumetric concentration of the particles, which would in turn be expected to counteract liquefaction by increasing substrate water retention capacity. This brings into question the loss of water retention capacity as a mechanism of enzymatic liquefaction. The contribution of this possible mechanism is examined more closely in the next section. 0.10.20.30.40.512 24 36 48 60 72Particle length (mm)Hydrolysis time (h)7.5153060Enzyme (mg g-1) 127 Figure 40. Particle width development during the liquefaction stage of steam-pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP). Dashed lines indicate 95% confidence interval as determined by the optical particle analyzer. 5.2.3 Loss of water retention capacity As mentioned above, another mechanism that has been suggested to contribute to enzymatic liquefaction is the loss of water retention capacity (Skovgaard et al., 2014; Viamajala et al., 2009). However, the measurement of particle widths of SPP200 and HW-DP over the course of enzymatic liquefaction indicated considerable swelling of the substrate following cellulase action. By measuring the timecourse water retention capacities of the SPP200 and HW-DP substrates during liquefaction, it was confirmed that cellulase action resulted in large increases in water retention capacity (Fig. 42). An initial spike (1.3-fold increase) in water-retention capacity was observed for SPP, followed by a gradual decrease that tended toward an asymptote at a value near that of the undigested substrate, well after the yield stress had leveled off (Fig. 42A). For the HW-DP substrate, enzymatic digestion considerably increased water retention capacity (1.4-fold), plateauing around the same time as yield stress (Fig. 41B). The initial rapid increase of water-retention capacity for both substrates could be explained by the creation of additional hydrated cellulose chain ends and concurrent increases in water sorption and swelling. For the SPP200 substrate, this started to become counteracted by the loss of cellulose and an increase in the relative amount of lignin. Overall, it appears that the loss of water-retention capacity is not a mechanism that contributes greatly to biomass liquefaction. In fact, 20222426280 1 2 3 4 5Particle width (μm)Time (h)A141618200 1 2 3 4 5Particle width (μm)Time (h)BSPP200 HW-DP 128 enzymatic hydrolysis resulted in swelling and increased water retention capacity for both a thermochemically pretreated substrate and a model, pure cellulose substrate. Figure 41. Slurry yield stress loss and changes in water retention during the hydrolysis of steam-pretreated poplar (SPP200) (A) and hardwood dissolving pulp (HW-DP) (B) at 10 % solids and an enzyme loading of 30 mgenzyme gcellulose-1 CTec3. Weiss et al. (2018) recently found that water retention capacity gradually increases during the enzymatic hydrolysis of steam-pretreated wheat straw with a T. reesei enzyme complex. However, their study did not show an initial rapid increase nor a subsequent leveling off of water retention capacity as was observed here with the SPP200 substrate. This difference could perhaps be attributed to the differences in the nature of woody and herbaceous biomass. Increased water retention capacity following T. reesei cellulase treatment of fully bleached softwood kraft pulp has also been noted (Park et al., 2007), while Liu et al. (2012) found that, following hydrolysis with xylanase, the water retention capacity of alkaline peroxide aspen mechanical pulp increased by ~11 % due to increased substrate porosity following xylan removal. Increased water retention capacity following enzyme action might also explain recent studies where initial increases in viscosity were observed during enzymatic hydrolysis (Kadić and Lidén, 2018; Le et al., 2017; Palmqvist et al., 2015). However, water retention capacity values were not reported in these studies to allow confirmation of this hypothesis. In the work reported in this thesis, the detrimental effects of increased water retention capacity on viscosity/yield stress were likely overshadowed due to the rapid particle fragmentation of SPP200 and HW-DP. Therefore, there was a net decrease in the apparent yield stress. 1.51.71.92.12.32.52.72.902004006008000 6 12 18 24Water retention (gwaterg fiber-1)Yield stress (Pa)Time (h)A1.51.71.92.12.32.52.72.90400800120016000 6 12 18 24Water retention (gwaterg fiber-1)Yield stress (Pa)Time (h)BHW-DP SPP200 129 5.2.4 Material dilution and its role at high solids loading In the work reported in the previous sections, particle fragmentation seemed to be a primary mechanism for enzymatic liquefaction. However, unlike previous studies that showed a distinct particle fragmentation phase prior to saccharification occurring before even 5 % of cellulose was hydrolyzed (Skovgaard et al., 2014; Szijártó et al., 2011b), 40–45 % of the cellulose had been solubilized by the time the SPP200 and HW-DP substrates were fully liquefied. This observation indicated that considerable material dilution—that is, conversion of insoluble carbohydrates to soluble species—had already occurred (Roche et al., 2009a). The work by Skovgaard et al. (2014) appeared to indicate that material dilution is secondary to particle fragmentation with regard to liquefaction. However, due to the technical limitations of their rheometry equipment, solids loadings of the hydrothermally pretreated wheat straw could not exceed 6 % dry matter, accordingly registering relatively low viscosities. When higher solids loadings are used, the slurry becomes increasingly solid-like in its rheological behavior and material dilution can be expected to play a significant role in liquefaction. This was likely the case at a 10 % solids loading for the highly fibrous woody substrates, resulting in high yield stresses and considerable carbohydrate solubilisation that occurred concurrently with particle fragmentation. Illustrative of this principle, Dasari et al. (2009) found a delineation of rheological concentration regimes. At solids loadings above 12 % of dilute acid-pretreated corn stover, the dominant factor influencing slurry viscosity was the insoluble solids content, whereas at lower solids loadings particle morphology was found to most influence the rheological behaviour (Dasari et al., 2009). As a result, enzymatic liquefaction may also be conditional to the insoluble solids content, or perhaps more accurately, the relative amount of free water in the system. Thus, depending on the slurry flow dynamics at a given phase of the reaction, different mechanisms dominate viscosity/yield stress reduction. However, even if the effects of the different mechanisms vary in their significance depending on the active insoluble solids loading, the underlying enzymatic reactions will be ongoing throughout the reaction. Thus, it can be difficult to isolate the effect of material dilution from concurrent deconstruction-induced substrate changes such as particle fragmentation. 130 Figure 42. The relative contribution of material dilution and particle fragmentation to the liquefaction of steam pretreated poplar (SPP200) and hardwood dissolving pulp (HW-DP) at a 10% substrate concentration and an enzyme loading of 20 mgprotein gcellulose-1 CTec3. (A) Yield stress reduction over time plotted on a semi-log scale, showing the exponential decay relationships of both substrates. (B) Yield stress plotted against cellulose hydrolysis (semi-log plot) showing dependence on material dilution. (C) Yield stress plotted against particle length (log–log plot) showing dependence on particle fragmentation. Coefficients of determination (R2) are indicated. When we reassessed the yield stress reduction observed during the digestion of the SPP200 and HW-DP substrates at a 10 % solids concentration (Fig. 34), it appeared that the overlapping dynamics of particle fragmentation and material dilution could be partially teased apart (Fig. 42). Both substrates exhibited an exponential decay of yield stress (Fig. 42A), albeit more rapidly for HW-DP, presumably due to being a highly digestible, low-lignin substrate, making up for its initially higher yield stress. Next, regression analysis of the trends in yield stress reduction in comparison to 0.555050050000 1 2 3 4 5 6 7Yield stress (Pa)Time (h)ASPP200HW-DP0.11101001000100000 20 40 60Yield stress (Pa)Hydrolysis extent (%)B01101001000100000.1 1.0Yield Stress (Pa)Particle length (mm)Cτy = 692e-0.718t τy = 1630e-1.093t R2 = 0.959 R2 = 0.897 R2 = 0.949 R2 = 0.811 131 hydrolysis extent (Fig. 42B) and particle fragmentation (Fig. 42C) was conducted. The lack of true linear response indicated that material dilution and particle fragmentation occurred simultaneously, blurring the distinction of their respective influence on yield stress reduction. It also showed that, at higher solids loadings, material dilution becomes an important liquefaction mechanism. Based on the coefficients of determination, the regression analysis also indicated that the liquefaction of the SPP200 substrate appeared to be more reliant on material dilution, while the HW-DP substrate, perhaps due to having a greater aspect ratio (36.3 compared to an aspect ratio of 22.2 for SPP), depended more on particle length reduction for its overall yield stress reduction. Therefore, liquefaction can be seen to exhibit substrate dependency, whereby the underlying mechanisms driving liquefaction will vary according to the physicochemical properties of a given substrate. 5.3 Isolation of material dilution While material dilution appeared to be an important mechanism in the enzyme-mediated liquefaction of the SPP200 and HW-DP substrates, simultaneous particle fragmentation muddled its specific influence. To further establish to what extent material dilution influences enzymatic liquefaction, the refiner mechanical pulp (RMP) substrate used in Section 3 was used to test material dilution in isolation from particle fragmentation. We had previously observed that no fiber fragmentation occurred during mild enzymatic digestion of this substrate. Following hydrolysis of ~23 % of the cellulose in the RMP substrate, the slurry yield stress was reduced 3.4-fold, from approximately 680 Pa to 200 Pa (Fig. 43A) while no concurrent change in the particle size distributions was observed (Fig. 43B), confirming the lack of fiber fragmentation. When cellulose hydrolysis was plotted against the corresponding yield stress of each time point on a semi-log plot, a distinct linear relationship was observed. This suggested that, in the absence of changes in particle morphology, material dilution can account for a considerable amount of slurry yield stress reduction (Fig. 43B inset). 132 Figure 43. (A) Yield stress and cellulose hydrolysis of refiner mechanical pulp (RMP) at 7 % solids and an enzyme loading of 30 mgenzyme gglucan-1 CTec3. (B) Particle length distribution of RMP after 0, 1 and 24 h of enzymatic hydrolysis. The inset shows the correlation between yield stress and cellulose hydrolysis on a semi-log plot. (C) Yield stress of unhydrolyzed RMP over a range of solids loadings. However, changes in interparticle interaction as a result of enzymatic action cannot be excluded and any such changes might also evade detection due to occurring simultaneously with material dilution. When the active insoluble solids content was calculated based on dissolution of polysaccharides (glucan, xylan, and mannan) following 23 % conversion, the theoretical yield stress at this solids content, based on the experimentally determined yield stress curve (Fig. 43C), would be expected to reach ~340 Pa. However, an effective yield stress of 200 Pa was measured. This discrepancy may indicate that other mechanisms apart from material dilution or particle fragmentation were responsible for yield stress reduction. Considering the volume fraction of the 010203002505007500 6 12 18 24Hydrolysis extent (%)Yield stress (Pa)Time (h)A02468100 0.5 1 1.5 2 2.5Frequency (%)Particle length (mm)B0 h1 h24 h505003 4 5 6 7 8Yield stress (Pa)Solids loading (%)C RMPRMP followinghydrolysis to 5.9% solids10010000 5 10 15 20 25Yield stress (Pa)Hydrolysis extent (%) 133 particles, it is in fact more likely that the population of particles that were digested down to an insoluble solids content of 5.9 % from 7 % solids would have a higher volume fraction than a directly prepared 5.9 % insoluble solids slurry due to maintenance of the fibrous structure from the lignin framework. Therefore, the digested slurry would be expected to have a higher yield stress than the slurry prepared at an equivalent insoluble solids content of fresh substrate. While no changes in particle length were detected following digestion of the RMP substrate, changes at the particle surface can go undetected with the particle analysis technique used here. It was possible that the observed additional yield stress reduction may have been due to changes in interparticle interactions resulting from cellulase action on substrate surfaces. 5.4 Interparticle interactions The action of cellulase enzymes on the surface of biomass fibers has been shown to have a ‘smoothing’ effect (Ander et al., 2008; Lee et al., 2000), which could influence interparticle interactions in the slurry. This could occur through reduction of the coefficient of friction of particle surfaces, which has been shown to be an important physical characteristic in determining the strength of interparticle interactions (Kerekes, 2006). Accordingly, changes in interparticle interactions have been suggested to be a mechanism by which enzymatic liquefaction occurs (Dibble et al., 2011). However, this mechanism is probably the most difficult to independently test on a bulk scale due to the heterogeneity of surface morphologies in pretreated substrates and the corresponding inability to quantify these surface properties. To this end, a northern bleached softwood kraft (NBSK) pulp was mildly refined at different refining severities to produce substrates that are similar except for their surface roughness levels (Fig. 44A). Substrates NBSK0 (unrefined), NBSK1, NBSK2, and NBSK3, in order of refining magnitude, were produced, as detailed in the Materials and Methods section. Particle size distributions confirmed congruency over the measured lengths, although some particle size reduction was evident for the most refined substrate NBSK3 (Fig. 44B). Yield stress measurements at equivalent solids loadings revealed considerable differences between the pulps. Yield stresses increased considerably with increased refining, up to a nearly 1.5-fold difference in yield stress between NBSK0 and NSBK3 (Fig. 44C), in spite of the slight particle size reduction of NBSK 3 that might be expected to result in a reduction of yield stress. It is important to note that the defibrillation and roughening of fiber surfaces can occur not only because of the refining used here, but also because of pretreatments that incorpate physical mechanisms such as steam pretreatment 134 with explosive decompression (Brownell and Saddler, 1987). Thus, such treatments could potentially have a substantial influence on slurry rheology. A NBSK0 (unrefined) NBSK1 (250 kWh t-1) NBSK2 (500 kWh t-1) NBSK3 (750 kWh t-1) Figure 44. (A) Scanning electron micrographs of northern bleached softwood kraft (NBSK) (0, 1, 2, and 3) pulps that were unrefined (0), refined at 250 kWh t-1 (1), 500 kWh t-1 (2), and 750 kWh t-1 (3). (B) Particle size distribution and cumulative distribution (inset) functions of the NBSK pulps. (C) Yield stress of NBSK pulps at 7.5 % solids. The impact of increased network strength and the corresponding influence on slurry rheology and reaction dynamics can be observed in the delay of yield stress reduction (Fig. 45A) as well as decreased conversion yield (Fig. 45B) in the earlier stages of enzymatic digestion at higher solids loadings. The more refined substrates, NBSK2 and NBSK3, retain relatively high yield stresses for the duration of the reaction. As a result, cellulose hydrolysis initially lags behind that of NBSK0 012345670 0.5 1 1.5 2 2.5Frequency (%)Particle length (mm)BNBSK 0NBSK 1NBSK 2NBSK 39211063117813628001000120014001600NBSK 0 NBSK 1 NBSK 2 NBSK 3Yield stress at 7.5 % solids (Pa)PulpC0204060801000 0.5 1 1.5 2 2.5Accumulated(%)Extent of refining 135 and NBSK1, with the positive influence of refining on enzymatic digestibility (Chen et al., 2013) being overshadowed by poorer mass transfer. However, once the yield stress was reduced enough to promote adequate slurry flow, the hydrolysis of the more refined substrates surpassed the less refined substrates. Considerable yield stress reductions were still realised for the more refined substrates, despite initial meager reductions in particle length (Fig. 45C). This indicated that some yield stress reduction might be accomplished through the removal of protruding fibrils and smoothing of the fiber surface (Mansfield et al., 1997). Although difficult to demonstrate in isolation from other mechanisms, these data suggest that alteration of interparticle interactions in the form of smoothing of the fiber surface, is a contributing mechanism of enzymatic liquefaction. It is worth noting that the interparticle interactions that were surveyed were primarily of a microscale fibrillary network-forming nature. Other interactions at the nanoscale level (such as interactions dominated by surface friction, adhesion, or zeta potential) could also have considerable impact on slurry rheology, as has been shown indirectly through additives that modify these interactions (Samaniuk et al., 2012). Further work is needed to directly detect and quantify interparticle interactions of this nature, given their likely importance at the crowded, low-free-water conditions of high solids bioconversion. As might be expected with regard to suspension dynamics, the rheological influences of fiber surface refining are alleviated when hydrolysis is conducted at low solids loadings where sufficient free water is present and particle interaction is greatly reduced (Fig. 45D). This showed a duality in terms of influence on enzymatic digestibility and rheological character. While refining increases the substrate’s accessibility to enzymatic catalysts and boosts low-solids digestion, the negative influences on slurry rheology can negate the benefits at higher solids loadings (Fig. 45D). Caution therefore needs to be taken in evaluating the efficacy of a pretreatment scheme merely through testing substrate digestibility at low solids loadings. It is apparent that, depending on a substrate’s morphological and physicochemical properties, processing and conversion of the substrate at high solids loadings can be strongly affected by its rheological or liquefaction characteristics. 136 Figure 45. (A) Yield stress reduction over the course of enzymatic hydrolysis of the differentially refined northern bleached softwood kradt (NBSK) pulps at 7.5 % solids. (B) Cellulose hydrolysis using an enzyme loading of 20 mgenzyme gcellulose-1 CTec3 at 7.5 % solids. (C) Particle length reduction during hydrolysis at 7.5 % solids. (D) Cellulose hydrolysis at 2 % solids and an enzyme loading of 10 mgenzyme gcellulose-1 CTec3. 5.5 Conclusions Timecourse analysis of substrate properties of a steam-pretreated substrate (SPP200) and a high-cellulose, low-lignin hardwood dissolving grade pulp (HW-DP) during high-solids hydrolysis indicated that substrate accessibility and crystallinity remain constant per unit cellulose over the course of hydrolysis. Thus, these nanoscopic substrate properties did not appear to be influential in enzyme-mediated liquefaction. 0400800120016000 1 2 3Yield stress (Pa)Time (h)ANBSK3NBSK2NBSK1NBSK002550751000 6 12 18 24Hydrolysis extent (%)Time (h)B0.00.51.01.52.02.53.00 6 12 18 24Particle length (mm)Time (h)C02550750 6 12 18 24Hydrolysis extent (%)Time (h)D2 % solids loading 7.5 % solids loading 137 In contrast, the macroscopic mechanism of particle fragmentation did appear to be an important mechanism that influenced enzymatic liquefaction. A threshold mean particle length was found to correlate with complete liquefaction (defined as the point at which τy ≤ 20 Pa). This value was found to be similar for the two substrates, despite the disparate rheological behaviour and particle size distributions between them prior to enzymatic hydrolysis. Over the course of enzymatic hydrolysis, the substrates’ particle size distributions and rheological behaviour became more similar and the cumulative distribution functions converged at the point of full liquefaction. Substrate particles underwent considerable swelling during enzyme action and this swelling coincided with large increases in water retention capacity in the early stages enzymatic hydrolysis (during liquefaction). However, later into the reaction, the water retention capacity evolved decidedly differently for the SPP200 and HW-DP substrates, likely due to the relative amounts of lignin in each substrate. The data suggested that the loss of water retention capacity was not a mechanism of enzymatic liquefaction, despite suggestions to the contrary in the literature, and that cellulose water sorption increased as a result of enzymatic hydrolysis. In contrast, material dilution was shown to be an important mechanism of liquefaction at high solids loadings and the relative influence of material dilution, as opposed to particle fragmentation, was dependent on substrate properties. The results also suggested that the relative influence of liquefaction mechanisms depends on the concentration or rheological regime of a lignocellulose slurry. However, when the influence of particle fragmentation was minimized (by using a refiner mechanical pulp that did not exhibit particle fragmentation under mild enzymatic hydrolysis), material dilution was confirmed as the predominant mechanism by which slurry yield stress is reduced under these conditions. Interparticle interactions and substrate properties that influence them (such as surface roughness and the coefficient of friction) were shown to be important in determining fiber slurry rheology. The alteration of these interparticle interactions by enzyme action on substrate surfaces has been hypothesized as another mechanism that influences enzyme-mediated liquefaction. However, these properties are difficult to quantify as a bulk quality. As a result, no clear evidence has been presented in the literature to support this hypothesis. By using specifically refined pulps with increasing levels of surface roughness the importance of interparticle interactions in determining slurry rheology and hydrolysis kinetics was confirmed. It was also shown that the smoothing of 138 substrate particles resulted in yield stress reductions. Thus, alteration of interparticle interactions was indicated as another mechanism that contributes to enzyme-mediated liquefaction. While substrate refining enhanced hydrolysis at low solids loadings by increasing the roughness and accessibility of the substrate, hydrolysis at high solids loadings was impeded by these same substrate properties due to the influence on slurry rheology. Therefore, an ongoing challenge is that substrate treatments, such as refining, that enhance enzyme accessibility to the cellulosic component of the substrate, are detrimental to slurry rheology and will likely impede enzyme-mediated liquefaction when high substrate concentrations are used. 139 6 Enzyme roles and synergism toward enzymatic liquefaction 6.1 Background The paradigmatic view of cellulose hydrolysis by fungal non-complexed enzyme systems is that of cellobiohydrolases acting as the primary catalysts, with auxiliary support from endoglucanases and beta-glucosidases. This primary function of cellobiohydrolases is reflected in the secretomes of fungal saprophytes such as that of T. reesei, where cellobiohydrolases comprise up to 80 % of the total secreted protein (Herpoël-Gimbert et al., 2008; Nidetzky and Claeyssens, 1994). Endoglucanases meanwhile make up a relatively small portion of the T. reesei secretome and in the enzyme in preparations derived from it, generally found to be less than 10 % of the total secreted protein (He et al., 2014; Markov et al., 2005). However, previous work examining viscosity reduction during hydrolysis of lignocellulosic materials with purified enzymes has suggested that endoglucanases are by far the most influential in bringing about enzyme-mediated liquefaction (Skovgaard et al., 2014; Szijártó et al., 2011b; Szijártó et al., 2011a). In these studies, no or minimal viscosity reduction occurred following enzymatic hydrolysis with purified cellobiohydrolases or xylanases. Replacing some of the endoglucanase with an equivalent amount of cellobiohydrolases or xylanase in fact reduced the extent of viscosity reduction (Szijártó et al., 2011b). These findings therefore suggest that current commercial cellulase cocktails, which are mostly based on fungal non-complexed systems, are poorly composed with regard to catalyzing enzymatic liquefaction. Improving enzymatic liquefaction therefore may require reconsideration of the composition of cellulase cocktails used in bioconversion processes. Although hydrolysis with purified xylanases has not been found to cause viscosity reduction, Skovgaard et al. (2014) showed that combining xylanase with endoglucanase or a cellulase mix resulted in more rapid viscosity reduction as well as increased particle fragmentation. This was in contrast to the work by Szijártó et al., who found that viscosity reduction was less effective upon partial replacement of endoglucanase with xylanase (Szijártó et al., 2011b). Both of these studies were conducted using hydrothermally pretreated wheat straw prepared under similar conditions. However, the wheat straw substrate used by Skovgaard et al. was pretreated at a lower temperature and had a xylan content of 10.8 % of dry matter, in comparison to a xylan content of 3.6 % in the substrate used by Szijártó et al. It is therefore perhaps not surprising that synergistic effects were found following xylanase addition during enzymatic liquefaction of a high-xylan substrate but not for a low-xylan 140 substrate. Moreover, the differential effect of xylanase substitution shows that, like saccharification, enzymatic liquefaction and the role of individual enzymes toward enabling viscosity reduction appear to be substrate-specific. Since studies examining the roles of enzymes in enzymatic liquefaction have been exclusively conducted with hydrothermally pretreated wheat straw, this further raises the question whether the relative roles of enzymes, and in particular the dominant role of endoglucanases, may vary for liquefaction of substrates pretreated with different methods and prepared from different lignocellulosic feedstocks. If so, optimization of enzymatic liquefaction, such as through development of liquefaction-specific enzyme cocktails, will require different enzyme cocktail compositions for different bioconversion substrates. To examine the substrate-specificity of enzymatic liquefaction and to further explore the roles of (hemi-)cellulolytic enzymes in mediating viscosity reduction, this section examined the enzymatic liquefaction of various woody substrates using different cellulase and hemicellulase cocktails, as well as purified enzymes, using both offline and real-time in situ rheometry to track the influence of enzymes on slurry rheology. 6.2 Liquefaction capacity comparison of a basic and an engineered Trichoderma reesei enzyme cocktail Currently available commercial cellulase preparations, including those geared toward bioconversion, are primarily based on the secretome of the fungus Trichoderma reesei. While T. reesei is industrially desirable due to its ability to secrete high amounts of extracellular protein (>100 g l-1), the T. reesei secretome natively has quite low carbohydrate-active enzyme diversity compared to other fungi, and has one of the smallest sets of hemicellulase genes in fungi for which genome sequences are available (Martinez et al., 2008; Pakula et al., 2016). For this reason, extensive protein engineering efforts have been directed towards improving the activity of T. reesei cellulases (Druzhinina and Kubicek, 2017), and auxiliary proteins such as hemicellulases have increasingly been incorporated into commercial cellulase preparations from exogenous sources (Reyes-Sosa et al., 2017). While these cellulase cocktail modifications have allowed incremental improvement of cellulose hydrolysis yields, it is not clear whether these same improvements have been beneficial toward improving enzymatic liquefaction. 141 Figure 46. Hydrolysis of steam-pretreated aspen (SP-Asp) at 15 % solids with a basic T. reesei enzyme preparation (Celluclast 1.5L supplemented with Novozyme 188) and an advanced cellulase preparation (CTec3) at an enzyme loading of 20 mgprotein gglucan-1. (A) Hydrolysis extent over time. (B) Yield stress over time, with semi-log inset. (C) Yield stress plotted as a function of hydrolysis extent, fitted with a second degree polynomial. (D) Particle length over the course of enzymatic hydrolysis. Yield stresses were measured using the controlled deformation method. To begin examining the role of individual enzymes and enzyme cocktail composition in enzymatic liquefaction, hydrolysis of steam-pretreated aspen (SP-Asp) at 15 % solids was conducted using a basic T. reesei cellulase cocktail (Celluclast 1.5L; Novozymes) and an advanced cellulase cocktail enriched with various additional carbohydrate-active enzymes (Cellic CTec3; Novozymes). Both preparations are based on the T. reesei platform, with Celluclast 1.5L being a relatively native form of the T. reesei secretome, whereas CTec3 is a later iteration in Novozymes’ product line improved through protein engineering and introduction of various exogenous proteins (Hu, 2013). Celluclast 1.5L was additionally supplemented with an Aspergillus niger beta-glucosidase preparation (Novozyme 188) to minimize product inhibition from cellobiose, since the native T. reesei secretome contains very low amounts of beta-glucosidase. 010203040500 2 4 6 8Hydrolysis extent (%)Time (h)A040080012000 2 4 6 8Yield stress (Pa)Time (h)B0.11.00 1 2 3 4 5Particle length (mm)Time (h)C11010010000 10 20 30 40 50Yield stress (Pa)Hydrolysis extent (%)D11010010000 2 4 6 8Advanced cocktail Basic cocktail 142 As expected, enzymatic hydrolysis yields were higher with the advanced cellulase cocktail at equivalent protein doses (Fig. 46A). Likewise, yield stress reduction (Fig. 46B) and particle fragmentation (Fig. 46C) rates were faster for the advanced cocktail. However, while hydrolysis rates and extents were significantly lower with the basic cellulase cocktail, considerable liquefaction occurred nonetheless. Examining yield stress as a function of hydrolysis extent (Fig. 46D), it could be seen that the basic cellulase cocktail required lower extents of hydrolysis to achieve the same yield stress reductions as the advanced cocktail. In other words, the advanced enzyme cocktail was more effective at hydrolyzing bulk cellulose (providing a higher rate of saccharification), but this did not translate into more efficient enzymatic liquefaction. This can also be seen in the initially low hydrolysis rate (from 0 to 1.5 h) with both enzyme preparations, both being negatively affected by the high solids loading conditions. Evidently, the enhancements made to the cellulase cocktail, while improving hydrolysis yields, have not enabled more efficient enzymatic liquefaction at high solids loadings. This supports the notion that liquefaction and saccharification are separate mechanisms, as explored in Section 5, and that these mechanisms need to be independently optimized to enable efficient high-solids enzymatic hydrolysis. To begin exploring the potential for optimizing enzymatic liquefaction, the next section will examine the role of hemicellulases in catalyzing enzymatic liquefaction. 6.3 The role of hemicellulases in enzymatic liquefaction Hemicellulases have been shown to synergize strongly with cellulase enzymes, improving hydrolysis of lignocellulosic materials (Gao et al., 2011; Hu et al., 2011). However, despite inclusion of additional auxiliary enzymes such as hemicellulases in enhanced commercial cellulase preparations, these changes did not appear to allow more efficient enzymatic liquefaction (Fig. 46). It is important to note however that the synergistic potential of hemicellulases has been shown to be highly substrate-specific (Hu et al., 2013). The ability of hemicellulases to promote enzymatic liquefaction likewise may depend on the substrate characteristics, and their influence may have been missed with the low-hemicellulose (4.5 % of dry mass) SP-Asp substrate used above. This is in line with the disparate findings with regard to the influence of xylanase on wheat straw slurry viscosity reduction, as discussed above. To further explore the role of hemicellulases in promoting enzymatic liquefaction and to examine potential substrate-specificity, a hemicellulase cocktail containing various hemicellulase 143 enzymes (Cellic HTec3; Novozymes) was used to hydrolyse the differentially pretreated aspen poplar substrates prepared in Section 4. A high enzyme loading (50 mgprotein gcellulose-1) was used to allow extensive hydrolysis of hemicellulose. Yield stress, complex viscosity, as well as storage and loss moduli were measured offline following enzymatic hydrolysis to examine the change in rheological behaviour. Even after extensive hydrolysis with hemicellulases, very little of the residual hemicellulose (xylan) in SP-Asp and SP-Asp-Delig could be removed (Fig. 47A). This recalcitrance of residual hemicellulose may be due to entrapment within the cellulose matrix as well as due to being associated with lignin–carbohydrate complexes (Gübitz et al., 1998). Nonetheless, around 13 % of glucan was hydrolyzed for both substrates, which may either be due to removal of glucosyl units in the hemicellulose or due to hydrolysis of cellulose. Hydrolysis of cellulose cannot be ruled out since some hemicellulases, GH10 xylanases in particular, exhibit considerable substrate promiscuity and are able to hydrolyse cellulose (Chu et al., 2017; Ichinose et al., 2012). Similar glucan hydrolysis extents were determined for the other aspen substrate variants, with a maximum of 18.7 % for RMP-Asp-Delig. Figure 47. Hydrolysis of aspen substrate variants with a hemicellulase preparation (HTec3; 50 mgprotein gcellulose-1) at 10 % solids for 24 h. (A) Hydrolysis extents of glucan and xylan. (B) Fractional yield stress (fraction of untreated substrate yield stress). (C) Fractional mean particle length. 020406080100SP-AspSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-DeligHydrolysis extent (%)AGlucanXylan00.20.40.60.8SP-AspSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-DeligFractional particle lengthB0.0030.0130.1480.0420.5600.00400.10.20.30.40.50.60.7SP-AspSP-Asp-DeligN-SP-AspN-SP-Asp-DeligRMP-AspRMP-Asp-DeligFractional yield stressC 144 No xylan hydrolysis could be detected for the mechanically refined RMP-Asp substrate, likely owing to its highly recalcitrant, largely unmodified cell wall structure. RMP-Asp also had the lowest glucan hydrolysis extent of 6.9 %. On the other hand, nearly 50 % of xylan was hydrolyzed for the delignified variant RMP-Asp-Delig, accompanied by 18.7 % glucan hydrolysis, showing that removal of lignin greatly increased accessibility of hemicellulose to enzymes. N-SP-Asp and N-SP-Asp-Delig both exhibited extensive xylan hydrolysis (70 and 92 %, respectively). Thus, while neutral steam pretreatment reserved hemicellulose in the substrate, the hemicellulose was made highly accessible to hemicellulases as a result of the pretreatment. Although the N-SP-Asp substrates showed the highest xylan hydrolysis extents, particle fragmentation was most extensive for the SP-Asp substrates (Fig. 47B), for which the mean particle lengths were reduced to a fraction of ~0.46 of the original. Both of the N-SP-Asp substrates and the RMP-Asp substrate nonetheless showed considerable particle fragmentation, reducing the mean particle lengths to 0.56–0.61 and 0.73 of their respective original mean particle lengths. Likewise, all substrates apart from RMP-Asp showed large reductions in slurry yield stress (Fig. 47C). Even RMP-Asp-Delig, which had a similar extent of particle fragmentation compared to RMP-Asp, had a near-complete elimination of detectable yield stress. Given the low degree of particle fragmentation, these results suggest that effective enzymatic liquefaction of RMP-Asp-Delig was achieved through smoothing of particle surfaces and material dilution (see Section 5). Meanwhile, the yield stress of RMP-Asp reduced to 0.56-fold that of the starting yield stress, suggesting that the low degree of particle fragmentation as a result of 6.8 % glucan hydrolysis, in addition to alteration of interparticle interactions, enabled a near two-fold reduction in yield stress. Of the other substrates, N-SP-Asp still had the highest fractional yield stress, despite its slightly higher degree of particle fragmentation than N-SP-Asp-Delig. This was likely due to the lower degree of hydrolysis and therefore lower degree of material dilution, although the effect of altered interparticle interactions cannot be ruled out. 145 Figure 48. Storage (G′) and loss (G″) moduli as well as complex viscosity (η*) of aspen substrate variants before (empty symbols) and after (filled symbols) hydrolysis with a hemicellulase preparation (HTec3; 50 mgprotein gcellulose-1) at 10 % solids for 24 h. Overall, it appears that hemicellulases are able to cause particle fragmentation and enzymatic liquefaction, even with low extents of hydrolysis. The influence of hemicellulases on slurry rheology could also clearly be detected with oscillatory rheometry. Apart from RMP-Asp, all substrates showed considerable reductions in the storage modulus, loss modulus, and complex viscosity (Fig. 48). 0.0010.010.111010010000.010.111010010001 10 100η* (kPa∙s)G′, G′′(kPa)Frequency (Hz)AG′G′′η* 0.0010.010.111010010000.010.111010010001 10 100η* (kPa∙s)G′, G′′(kPa)Frequency (Hz)B0.0010.010.111010010000.010.111010010001 10 100η* (kPa∙s)G′, G′′(kPa)Frequency (Hz)C0.0010.010.111010010000.010.111010010001 10 100η* (kPa∙s)G′, G′′(kPa)Frequency (Hz)D0.0010.010.111010010000.010.111010010001 10 100η* (kPa∙s)G′, G′′(kPa)Frequency (Hz)E0.0010.010.111010010000.010.111010010001 10 100η* (kPa∙s)G′, G′′(kPa)Frequency (Hz)FSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig RMP-Asp RMP-Asp-Delig 146 Likewise, considerable increases in the loss tangent were evident (Fig. 49), suggesting increased viscous (liquid-like) rheological behaviour. Figure 49. Loss tangent (tan δ; G″/G′) summary for aspen substrate variants before (empty symbols) and after (filled symbols) hydrolysis with a hemicellulase preparation (HTec3; 50 mgprotein gcellulose-1) for 24 h. However, as noted before, hemicellulases, such as glycoside hydrolase family 10 xylanases, are known to display substrate promiscuity and can potentially hydrolyse cellulose. Furthermore, it is possible that some cellulase contamination is present in the hemicellulase preparation. Further examination of the influence of hemicellulases will therefore require purified enzymes, as was explored in Section 6.6. In order to do so effectively, an in-rheometer real-time enzymatic liquefaction monitoring method needed to be developed, as will be described in the next section. 00.20.40.61 10 100Tan δFrequency (Hz)A00.20.40.61 10 100Tan δFrequency (Hz)B00.20.40.61 10 100Tan δFrequency (Hz)C00.20.40.61 10 100Tan δFrequency (Hz)D00.20.40.61 10 100Tan δFrequency (Hz)E00.20.40.61 10 100Tan δFrequency (Hz)FSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig RMP-Asp RMP-Asp-Delig 147 6.4 In-rheometer reaction method development Thus far in this work, enzymatic liquefaction has been quantified through off-line rheometry following termination of enzymatic hydrolysis. However, tracking enzymatic liquefaction in this manner requires numerous reactions for each treatment to construct a meaningful timecourse profile of yield stress or viscosity reduction. The accuracy and throughput of liquefaction analyses could therefore be improved if rheological measurements were made on-line in real time. One way to achieve this is to use the rheometer itself as a stirred reactor, whereby rotation is set to a constant rate and slurry viscosity is measured by monitoring the torque required to maintain the stirring rate (Szijártó et al., 2011b). This method was explored here using reactions within a temperature-controlled cup using a rheometer equipped with a four-bladed vane geometry, as used above for oscillatory rheometry. Figure 50. In-rheometer reactions of microcrystalline cellulose (Avicel PH-101) at 20 % (m/m) with T. reesei cellulase (CTec3) at 20 mgprotein gcellulose-1 as well as controls with buffer and bovine serum albumin (BSA; 20 mgprotein gcellulose-1) at 50 °C. The arrow denotes the point at which buffer (50 mM sodium acetate, pH 4.8) or enzyme was added to the add-in-place control or add-in-place cellulase reactions, respectively. First, to test the in-rheometer setup, one-hour control reactions were performed on 20 % (m/m) suspensions of highly pure microcrystalline cellulose (Avicel PH-101) (Fig. 50). 0.00.10.20.30.40.50 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)Buffer - PremixedBuffer - Add-in-placeCellulase - PremixedCellulase - Add-in-placeBSA - 1BSA - 2BSA Buffer Cellulase 148 Microcrystalline cellulose is produced through acid hydrolysis of wood or cotton and is often used as a model cellulose substrate, given its relative heterogeneity and availability as a consistent commercial product. However, microcrystalline cellulose comprises very small particles (~50 μm for Avicel PH-101) and lacks fibrillar architecture, and therefore likely is not representative of the rheology of fibrous biomass. Moreover, microcrystalline is known to readily form gels (Rudraraju and Wyandt, 2005) and indeed in the current work the microcrystalline cellulose suspensions appeared to behave like stable colloids. Because of this, interesting rheological behaviour was observed. Although an immediate drop in viscosity was evident following addition of cellulase, slurry viscosity remained stable and did not appear to reduce following one hour of hydrolysis. This was likely due to a lack of particle fragmentation of the small, highly crystalline particles and the low degree of material dilution achieved following one hour of hydrolysis. It indeed has been shown that even following extended enzymatic hydrolysis, the average degree of polymerization of microcrystalline cellulose does not reduce appreciably (Kafle et al., 2015), nor does the particle volume change significantly (Peciulyte et al., 2016). Despite no evident enzymatic liquefaction, it appeared that addition of enzyme did reduce signal noise in comparison to the buffer-only control. This suggests that enzyme action caused stabilisation of interparticle interactions in the suspension, likely through disaggregation of particle conglomerates through hydrolysis at particle surfaces (Olsen et al., 2016). Comparing addition of enzyme to the addition of non-enzyme protein (BSA), it appears that the immediate change in viscosity compared to the buffer-only control for both the BSA and enzyme treatment was simply due to the change in viscosity as a result of protein addition. The opposing influence of BSA and cellulase addition is likely explained by electroviscous effects resulting from the difference in molecular charge of the proteins (Yadav et al., 2011) as well as the difference in their partitioning in the solid–liquid system, where cellulases would rapidly specifically adsorb via CBMs to the cellulose, whereas BSA would primarily remain in the interstitial liquid. Using microcrystalline cellulose slurries as a model, the influence of enzyme dispersal method on rheological system stability was examined. Add-in-place reactions, where enzyme or the equivalent volume of buffer was pipetted into the reaction cup after ~7 min (as indicated by the arrow in Fig. 49), showed considerable noise in the viscosity signal immediately following injection before stabilizing at similar values to the respective pre-mixed replicates. Stabilization of the signal required nearly 10 min following cellulase addition. This indicated that vertical mixing within the rheometer setup was inadequate for rapid enzyme dispersal, and that in-rheometer experiments require pre-mixing of enzyme prior to the initiation of reactions. This method was used for the rest of the work in 149 this section. Thus, while microcrystalline cellulose slurries are not adequately representative of biomass fiber slurries, their use allowed a well-controlled examination of the in-rheometer method and identified how to proceed with in-rheometer reactions with pretreated biomass slurries, as will be reported on in the next section. 6.5 In-rheometer liquefaction using a cellulase cocktail To establish a baseline of enzymatic liquefaction for comparison of the influence of purified enzymes, in-rheometer hydrolysis reactions were performed with a complete cellulase cocktail on the aspen substrate variants (Fig. 51). Reactions were performed at 2.5 % solids, given that at this solids loading all substrates could be effectively mixed in the rheometer without plug formation. Reactions were conducted in duplicate and the logarithmic fit to the combined data set was plotted. 150 Figure 51. In-rheometer reactions of aspen substrate variants at 2.5 % (m/m) solids with an advanced enzyme cocktail (CTec3) at 20 mgprotein gcellulose-1 and a shear rate of 60 s-1. Blue trend lines show the logarithmic best fits to the replicates. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). (E) Refiner mechanical pulp aspen (RMP-Asp). (F) Delignified refiner mechanical pulp aspen (RMP-Asp-Delig). 0.000.050.100.150.200 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)A ControlReplicate 1Replicate 2Logarithmic fit0.00.10.20.30.40.50.60 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)B0.00.51.01.52.00 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)C012340 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)D00.10.20.30.40.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)E00.10.20.30.40.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)FSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig RMP-Asp RMP-Asp-Delig 151 Both SP-Asp and its delignified variant SP-Asp-Delig showed rapid viscosity reduction, reducing 4-fold from 0.10 Pa×s to 0.025 Pa×s and 10-fold from 0.40 to 0.040 Pa×s, respectively, after 60 min in comparison to the control reactions. A slight reduction was observed over time for the SP-Asp control, which was likely due to particle settling that was observed over the course of the 60 min incubation. The initial viscosity of the N-SP-Asp substrates was considerably higher, and showed less rapid but nonetheless substantial viscosity reduction, reducing 2.4-fold from 1.15 Pa×s to 0.48 Pa×s for N-SP-Asp and 3-fold from 2.8 Pa×s to 0.95 Pa×s for N-SP-Asp-Delig. The RMP-Asp substrates, while having much higher yield stress than the SP-Asp substrates in the 5–15 % solids range as determined earlier (Section 4), here at 2.5 % solids had viscosities that were in the same range as the SP-Asp substrates. Surprisingly, no viscosity reduction was evident. This was likely due to poor particle fragmentation, as seen in Section 4, in combination with insufficient time to allow material dilution to have a meaningful impact on slurry viscosity. Especially since the in-rheometer experiments are conducted in a relatively dilute rheological regime, it can be expected that particle length is the most important determinant of slurry rheology in these conditions, and thus the lack of particle fragmentation resulted in no detectable reduction of viscosity. Since no liquefaction was evident for the RMP-Asp substrates in the in-rheometer reaction setup even with a full cellulase cocktail, further experiments were restricted to the SP-Asp and N-SP-Asp substrates. 6.6 In-rheometer liquefaction using purified enzymes Having established a baseline of enzymatic liquefaction using a full cellulase cocktail, several carbohydrate-active enzymes were next purified for their individual application (Table 7). These included an endoglucanase from Humicola insolens (HiCel45A), the primary cellobiohydrolase (CBH I) of Trichoderma reesei (TrCel7A), a beta-glucosidase from Aspergillus niger, and two fungal xylanases: one from glycoside hydrolase family 10 (GH10Xyn) and one from family 11 xylanase (GH11Xyn). 152 Table 8. Enzymes utilized in this section, their isoelectric point (pI), molecular weight (MW), and method of purification. HiCel45A is a bimodular (CBM-containing) endoglucanase containing an open substrate-binding cleft with six subsites (Davies et al., 1996) and was obtained through anion exchange (Fig. 52A) from a crude preparation of HiCel45A cloned and expressed in Aspergillus oryzae. While the optimal pH for HiCel45A has been reported to be above pH 7 (Schülein, 1997), successful use of this enzyme at lower pH (4.8) has previously been reported (Thygesen et al., 2011), and likewise the activity at pH 5 seemed sufficient, chosen here to allow combination with T. reesei enzymes. TrCel7A was purified through anion exchange and size exclusion (Fig. 52B). The Aspergillus niger glycoside hydrolase family 3 beta-glucosidase was used as received following desalting. The two fungal xylanases provided representatives of the two major xylanase families and were chosen given the high xylan content of hardwood substrates and the high degree of synergy of xylanases observed with cellulases during enzymatic hydrolysis of xylan-rich substrates (Hu et al., 2011; Hu et al., 2013). GH10 xylanases typically have a higher molecular weight and tend to display substrate promiscuity, being capable of hydrolyzing short-chain cellulose (Collins et al., 2005). GH11 xylanases on the other hand are considered ‘true’ xylanases, in that they exclusively act on xylose-containing substrates, as well as generally having a lower molecular weight (Paës et al., 2012). GH10Xyn was purified via anion exchange from a commercial preparation of Aspergillus sp. origin (Hauch et al., 2012) (Fig. 52C). GH11Xyn was purified from a commercial preparation that primarily contains a family 11 xylanase from Trichoderma reesei (TrXyn2) through size exclusion and anion exchange (Fig. 52D). Identity of the proteins was confirmed through tandem mass spectrometry. Enzyme Enzyme preparation pI MW (kDa) Purification HiCel45A, endo-1,4-β-glucanase (EG) Crude preparation from Humicola insolens (Novozymes) ~5a 43b 1. Desalting 2. AIEC TrCel7A (CBHI), cellobiohydrolase Celluclast® 1.5L, Trichoderma reesei (Novozymes) 3.8c 56c 1. Desalting 2. AIEC 3. SEC GH10 xylanase Cellic® HTec, Aspergillus fumigatus, (Novozymes) ~4a 45–50e 1. Desalting 2. AIEC GH11 xylanase Multifect® Xylanase, Trichoderma reesei (Genencor) 9.0d 21e 1. SEC 2. AIEC GH3 β-glucosidase (BG) Novozyme 188, Aspergillus niger (Novozymes) 4.5f 100e 1. Desalting adetermined through IEF; b(Boisset et al., 2001); c(Pereira et al., 2017); d(Törrönen et al., 1992); edetermined through SDS-PAGE; f(Lima et al., 2013) 153 Figure 52. FPLC chromatograms showing purification of the enzymes used in this section. (A) TrCel7A: anion exchange followed by size-exclusion (inset) to obtain TrCel7A. The arrow indicates the peak containing TrCel7A that was used for size-exclusion. (B) HiCel45A: anion exchange. The initial two peaks are a 90 kDa protein (confirmed through SDS-PAGE) that could be removed from the preparation. The shaded area indicates the fraction collected for further use. (C) GH10Xyn: anion exchange. (D) GH11Xyn: Size exclusion followed by anion exchange (inset). SDS-PAGE analysis was used to confirm purification (Fig. 53). TrCel7A and HiCel7A showed single bands, as did the GH3 beta-glucosidase (not shown). GH10Xyn showed two closely spaced bands of approximately equal intensity and slightly different molecular weights, which were likely two isoforms that could not be unambiguously differentiated with tandem mass spectrometry. For GH11Xyn, a very faint band could be seen at around 45 kDa, although this band paled in comparison to the band at 20 kDa corresponding to the xylanase. 04080120160A280(mAu) A0.00.51.01.52.02.5A280(Au)B0100200300A280 (Au) C0.00.51.01.5A280 (Au) DTrCel7A HiCel45A GH11Xyn GH10Xyn 0123 Anion exchangeSize exclusion Anion exchange 0123Size exclusion 154 kDa 250 150 100 75 50 37 25 20 Figure 53. SDS-PAGE of purified enzymes and the preparations from which they were purified, flanked on either side with protein markers with molecular weights as indicated. Relevant activities of the purified enzymes were next measured (Table 8). EG contamination in Cel7A purifications from fungal culture broths has been noted as a common issue (Payne et al., 2015). Upon initial measurement, no activity on the CMC substrate could be detected with the Cel7A purified here. To ensure a lack of EG contamination, the Cel7A preparation was concentrated through ultrafiltration with a centrifugal filtration device with a nominal molecular weight limit of 10 kDa, providing concentrates of up to 60 g l-1. Using this concentrated preparation, the specific activity on CMC was found to be negligible (in the femtokatal mg-1 range). Conversely, HiCel45A did not exhibit activity on pNPC, but displayed slight activity toward birchwood xylan (0.13 nkat mg-1). Of the two xylanases, the GH10 xylanase showed the highest activity toward birchwood xylan, likely reflecting its less restrictive substrate structure requirements compared to the GH11 xylanase. Celluclast TrCel7A Hi Prep HiCel45A HTec GH10Xyn Multifect GH11Xyn 155 Table 9. Enzyme activities of purified preparations, tested in 50 mM sodium acetate buffer, pH 5. Name Enzyme Substrate Activity tested Specific activity (nkat mg-1) HiCel45A endo-1,4-β-glucanase from Humicola insolens CMCa endoglucanase 74.8 pNPCb cellobiohydrolase n.a.c BXd xylanase 0.13 TrCel7A cellobiohydrolase from Trichoderma reesei pNPC cellobiohydrolase 6.8 CMC endoglucanase n.a.e GH10Xyn GH family 10 xylanase, from Aspergillus fumigatus BX xylanase 898 GH11Xyn GH family 11 xylanase from Trichoderma reesei BX xylanase 670 GH3BG GH family 3 beta-glucosidase pNPGf β-glucosidase 6.7 acarboxymethylcellulose; bp-nitrophenyl β-D-cellobioside; cnegligible activity; dbirchwood xylan; eafter concentration through ultrafiltration, the specific activity was found to be in the femtokatal mg-1 range; fp-nitrophenyl β-D-glucopyranoside Having purified the enzymes and examined their activity, the enzymes were next applied individually on the differentially pretreated aspen poplar substrates to examine their ability to catalyze enzymatic liquefaction, as monitored in real-time with the rheometer. 156 6.6.1 Endoglucanase (HiCel45A) Since endoglucanases have thus far been shown to be the primary enzymes catalyzing enzymatic liquefaction (Skovgaard et al., 2014; Szijártó et al., 2011a; Szijártó et al., 2011b) as well as cellulose fragmentation (Walker et al., 1992), in-rheometer liquefaction was first examined with HiCel45A (Fig. 54). While SP-Asp, SP-Asp-Delig, and N-SP-Asp-Delig showed considerable viscosity reduction, no change in viscosity was detected for N-SP-Asp. Similarly, SP-Asp-Asp and SP-Asp-Delig both displayed a significant reduction in particle length (reducing from 447 μm to 390 ± 7 μm and from 461 μm to 409 ± 1 μm, respectively), yet neither N-SP-Asp nor N-SP-Asp-Delig showed a detectable reduction in particle length. This was surprising since N-SP-Asp-Delig nonetheless had a near two-fold reduction in viscosity, suggesting that other mechanisms such as modification of interparticle interactions accounted for this reduction. The lignin present in N-SP-Asp, which was removed in its delignified variant, presumably prevented these changes and therefore no viscosity reduction occurred. Although the N-SP-Asp substrate was shown to be quite digestible when subjected to a full cellulase cocktail, the application of purified endoglucanases to this substrate showed no discernible liquefaction effect. This was despite previous work that suggested that they would be the essential liquefaction-catalyzing enzymes. These results provided confirmation that the action of individual enzymes in catalyzing enzymatic liquefaction is highly substrate-specific and that promoting efficient enzymatic liquefaction requires optimization of the enzymes present in the enzyme cocktail. 157 Figure 54. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the endoglucanase HiCel45A at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). Since HiCel45A appeared highly effective in liquefying SP-Asp-Delig in particular, the dependency of its liquefaction-capacity on enzyme loading was examined next. Previous work has shown that very small amounts of endoglucanase can catalyze large rheological changes in suspensions of cellulosic materials on the time scale of minutes (Gourlay et al., 2018). Through stepwise reduction of the HiCel45A loading, it was seen that even at a low loading of 1.25 mg g-1, slurry viscosity could be greatly reduced (Fig. 55). Whereas an enzyme loading of 10 mg g-1 enabled a 5.4-fold reduction in viscosity, an 8-fold lower enzyme loading (1.25 mg g-1) still enabled a 3.6-fold 0.000.050.100.150.200.250 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)A ControlReplicate 1Replicate 2Logarithmic fit0.00.10.20.30.40.50.60 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)B0.00.51.01.52.00 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)C012340 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)DSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig 158 reduction in viscosity. Diminishing returns following increased enzyme loading with regard to viscosity reduction were therefore apparent. This suggests that small amounts of enzyme (such as HiCel45A) could be added to allow enzymatic liquefaction ahead of bioconversion reactions, such as in a pre-conditioning step following pretreatment (Brunecky et al., 2014; Hämäläinen et al., 2016). Figure 55. In-rheometer reactions of delignified steam-pretreated aspen (SP-Asp-Delig) at 2.5 % solids with HiCel45A at reducing enzyme loadings. Logarithmic fits to duplicate reactions are shown for each enzyme loading. Original response curves not shown for clarity. 6.6.2 Cellobiohydrolase (TrCel7A) In the work presented so far in the literature on the role of enzymes in enzymatic liquefaction conducted with wheat straw, cellobiohydrolases did not enable significant viscosity reduction (Szijártó et al., 2011a; Szijártó et al., 2011b). Nonetheless, TrCel7A has been shown to synergize with endoglucanases to promote fragmentation of microcrystalline cellulose (Walker et al., 1992). Cellulose crystal fragmentation has also been reported for TrCel7A acting on its own, although fragmentation was only observed at very high extents of hydrolysis of bacterial cellulose (Jeoh et al., 2013). However, these studies were performed on model substrates with highly crystalline cellulose lacking the dislocations present in biomass fibers. These dislocations are important in that they appear to be the failure points where fibers fragment due to mechanical action following weakening by enzymatic hydrolysis (Thygesen et al., 2014). The cellulose within dislocations was previously 0.00.10.20.30.40.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)HiCel45A (mg g-1) 1.25 2.5 5.0 10 159 hypothesized to be amorphous and therefore thought to be preferentially targeted and particularly susceptible to hydrolysis by endoglucanases (Ander et al., 2008). On the other hand, structural analysis of dislocations has suggested that cellulose structure and crystallinity is largely reserved, apart from having a higher microfibril angle, which allows for their visualization through polarized light microscopy (Hidayat et al., 2012). Increased reactivity at dislocations may instead be attributed to localized reductions in lignin and hemicellulose, as observed for hemp fibers using Fourier-transform infrared spectroscopy (Dai and Fan, 2011). This would therefore suggest that cellobiohydrolases should also be able to catalyze hydrolysis efficiently at dislocations, provided that chain-threading can be initiated. Indeed, Suchy et al. (2009) reported preferential hydrolysis at dislocations by cellobiohydrolases from Thermoascus aurantiacus (TaCel7A). Using semi-quantitative laser scanning confocal microscopy, Hidayat et al. (2015) furthermore showed that T. reesei endoglucanase (EG II; TrCel5A) and cellobiohydrolases (TrCel7A and TrCel6A) adsorbed to dislocations to a similar degree as they did to the surrounding cell wall. Incidentally, only HiCel45A showed preferential binding affinity to dislocations. Although TrCel7A has been viewed as a strict exoglucanase, some research has also indicated the capacity for endo-mode initiation (Kurašin and Väljamäe, 2011; Silveira and Skaf, 2018; Ståhlberg et al., 1993). Such endo-initiation would further promote cellobiohydrolase action as dislocations. 160 Figure 56. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the cellobiohydrolase TrCel7A at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). By applying TrCel7A in in-rheometer reactions, considerable liquefaction could be achieved for SP-Asp, SP-Asp-Delig, and N-SP-Asp-Delig (Fig. 56). As before with HiCel45A, in contrast to its delignified variant, no viscosity reduction was evident for N-SP-Asp, suggesting that lignin prevented enzymatic liquefaction. As a result of hydrolysis with TrCel7A, the mean particle lengths of SP-Asp and SP-Asp-Delig reduced to a similar extent as for treatment with HiCel45A, reducing to 393 ± 15 μm and 410 ± 7 μm, respectively. The endoglucanase and cellobiohydrolase tested here therefore appeared to have similar particle fragmentation capacities. Interestingly, as before with application of 0.000.050.100.150.200 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)A ControlReplicate 1Replicate 2Logarithmic fit0.00.10.20.30.40.50.60 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)B0.00.51.01.52.00 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)C012340 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)DSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig 161 endoglucanase, the mean particle length of N-SP-Asp-Delig did not change (716 ± 1 μm following 60 min of hydrolysis), again implicating mechanisms other than particle fragmentation in liquefaction of this substrate. In contrast to the earlier literature, the work presented here showed that cellobiohydrolases can catalyze substantial enzymatic liquefaction and that their action was almost as effective as endoglucanases on an equivalent mass basis. Similarly, hydrolysis with purified cellobiohydrolases resulted in equivalent extents of particle fragmentation, indicating the ability of these enzymes to effectively hydrolyze and weaken fiber dislocations. 6.6.3 Glycoside hydrolase family 10 xylanase As discussed earlier, conflicting results can be found in the literature with regard to the influence of xylanases in catalyzing enzymatic liquefaction. To try to further elucidate the role of xylanases, two xylanases were selected, one from GH family 10 and another from GH family 11. First, in-rheometer reactions with GH10Xyn were conducted, which showed no evident viscosity reduction for any of the substrates (Fig. 57). This was surprising, since glycoside hydrolase family 10 xylanases tend to exhibit activity toward substituted xylan, and even low molecular weight cellulose (Collins et al., 2005). However, both studies on the influence of xylanase in enzymatic liquefaction reported in the literature (Skovgaard et al., 2014; Szijártó et al., 2011b) exclusively used GH family 11 xylanases, and their influence was tested next. 162 Figure 57. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the xylanase GH10Xyn at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). 0.000.050.100.150.200 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)AControlGH10Xyn0.00.10.20.30.40.50.60 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)B0.00.51.01.52.00 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)C01234560 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)DSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig 163 6.6.4 Glycoside hydrolase family 11 xylanase Despite GH10Xyn having the highest activity toward birchwood xylan (Table 2), and despite the fact that GH family 10 xylanases tend to be more tolerant of substitutions in the xylan polymer (Biely et al., 1997) and therefore tend to able to accommodate a larger variety of substrates (Collins et al., 2005), no viscosity reduction was evident during its in-rheometer hydrolysis. In contrast, GH11Xyn achieved considerable liquefaction of SP-Asp and SP-Asp-Delig (Fig. 58). Meanwhile, neither N-SP-Asp nor N-SP-Asp-Delig showed reduced viscosity, despite these substrates having much higher xylan contents than the SP-Asp substrates (11–12 % of dry mass compared to 1.5–1.6 % for the SP-Asp substrates). Thus, while very little residual xylan was present in the acidic steam-pretreated substrates, its hydrolysis by GH11Xyn promoted significant viscosity reduction. Hydrolysis with GH11Xyn also caused moderate particle fragmentation of the SP-Asp substrates, reducing the mean particle length of SP-Asp to 414 ± 5 μm and that of SP-Asp-Delig to 441 ± 2 μm. Presumably, the amount of xylan present in N-SP-Asp-Delig was too large to enable a noticeable effect on slurry viscosity following 60 min of reaction time, or the application of the specific ‘true xylanase’ GH11Xyn on its own was not enough to enable sufficient deconstruction of the more native xylan present in the neutrally steam-pretreated substrate. These results also reflect previous work (Pryor and Nahar, 2010) that has shown that assessment of enzyme activity on model substrates does not necessarily reflect the capacity to effectively hydrolyse pretreated substrates. 164 Figure 58. In-rheometer reactions of aspen substrate variants at 2.5 % solids (m/m) with the xylanase GH11Xyn at 10 mgprotein gcellulose-1. (A) Steam-pretreated aspen (SP-Asp). (B) Delignified steam-pretreated aspen (SP-Asp-Delig). (C) Neutral steam-pretreated aspen (N-SP-Asp). (D) Delignified neutral steam-pretreated aspen (N-SP-Asp-Delig). 6.6.5 Summary of purified enzyme in-rheometer liquefaction To allow comparison of the relative effect of the individual enzymes tested above, the logarithmic fits to the data of each in-rheometer reaction where viscosity reduction was evident are summarized in Fig. 59 for SP-Asp (A), SP-Asp-Delig (B), and N-SP-Asp-Delig (C). Note that the enzyme cocktail was applied at 20 mgprotein gcellulose-1 while the individual enzymes were used at a loading of 10 mgprotein gcellulose-1. The two-fold lower loading of the purified enzymes was intended to 0.000.050.100.150.200 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)A ControlReplicate 1Replicate 2Logarithmic fit0.00.10.20.30.40.50.60 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)B0.00.51.01.52.00 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)C012340 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)DSP-Asp SP-Asp-Delig N-SP-Asp N-SP-Asp-Delig 165 equal the amount of the most abundant enzyme in T. reesei enzyme cocktails, with TrCel7A generally making up about half of the total protein by weight (Hu, 2013; Markov et al., 2005). Figure 59. In-rheometer liquefaction summaries for steam-pretreated aspen (SP-Asp) (A), delignified steam-pretreated aspen (SP-Asp-Delig) (B), and delignified neutral steam-pretreated aspen (N-SP-Asp-Delig) (C) showing the logarithmic fits of the averaged data sets for each in-rheometer reaction. In contrast to the work reported in the literature on the enzymatic liquefaction of hydrothermally pretreated wheat straw (Szijártó et al., 2011a; Szijártó et al., 2011b), which showed marginal influence from cellobiohydrolases, the work reported here showed that TrCel7A had considerable ability to reduce the viscosity of the acidic steam-pretreated aspen substrates (Fig. 59A and 58B). While for both SP-Asp and SP-Asp-Delig the viscosity at 60 min was lower following treatment with the endoglucanase HiCel45A, TrCel7A in fact initially promoted more rapid viscosity 0.000.050.100.150.200 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)A ControlT. reesei cocktailHiCel45ATrCel7AGH11Xyn0.00.10.20.30.40.50.60.70 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)BControlT. reesei cocktailHiCel45ATrCel7AGH11Xyn0123450 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)C ControlT. reesei cocktailTrCel7AHiCel45ASP-Asp SP-Asp-Delig N-SP-Asp-Delig 166 reduction than did HiCel45A for SP-Asp (Fig. 59A; first 15 min of reaction). The efficacy of TrCel7A was also reflected in the extent of particle fragmentation, achieving similar mean particle lengths at the end of the reaction as for the reactions with HiCel45A. For both SP-Asp and its delignified variant, endoglucanase (HiCel45A) by itself achieved nearly the same rate and extent of viscosity reduction as did the full T. reesei cocktail, but at half the total enzyme loading. Marginal viscosity reduction occurred with GH11Xyn for both substrates. On the other hand, viscosity reduction of N-SP-Asp-Delig was significantly lower for either endoglucanase (1.48-fold) or cellobiohydrolase (1.82-fold) on their own compared to T. reesei cocktail (2.85-fold), and no viscosity reduction occurred following hydrolysis with GH11Xyn. These results therefore show that enzymatic liquefaction of the more native, less severely pretreated N-SP-Asp-Delig substrate (having been pretreated at neutral pH and retaining a large hemicellulose fraction) requires the cooperation of multiple enzymes for synergistic effects to achieve similar viscosity reduction. Such substrate-dependency of enzyme synergism has previously been reported in the literature (Andersen et al., 2008; Hu et al., 2013), and it would follow that the less severely pretreated substrate N-SP-Asp-Delig requires a more concerted effort from various enzymes to enable effective deconstruction. The GH family 3 beta glucosidase was also tested for all substrates, but did not show any influence on slurry viscosity, as was expected based on previous work (Szijártó et al., 2011a). 167 6.7 Enzyme synergy toward enzymatic liquefaction of neutral steam-pretreated aspen While the full cellulase cocktail was shown above to be able to reduce the viscosity of N-SP-Asp slurries more than two-fold (Fig. 50C), none of the purified enzymes applied individually were capable of reducing slurry viscosity. The delignified variant (N-SP-Asp-Delig) did show viscosity reduction from application of purified endoglucanase or cellobiohydrolase, but viscosity reduction with these enzymes applied individually was significantly less effective compared to that with the full cocktail. This was in contrast to the SP-Asp substrates, which exhibited decreases in slurry viscosity following hydrolysis with the individual purified enzymes that were in the same range as was achieved with the full cocktail. Previous work has shown that enzyme synergism is dependent on the properties of the substrate (Andersen et al., 2008; Ganner et al., 2012; Hu et al., 2013). As aforementioned, it is therefore likely that the lower severity of neutral steam pretreatment results in a substrate that is more dependent on enzyme synergism to achieve deconstruction and enzymatic liquefaction. To test this hypothesis, the purified enzymes were added in various combinations and applied toward in-rheometer reactions with N-SP-Asp at a combined total of 20 mgprotein gcellulose-1 to allow comparison to enzymatic liquefaction with the complete cellulase cocktail (Fig. 60). No viscosity reduction was evident following hydrolysis with the binary combinations of TrCel7A with HiCel45A (Fig. 60A), TrCel7A with GH11Xyn (Fig. 60B), or HiCel45A with GH11Xyn (Fig. 60C). Binary combinations of TrCel7A or HiCel45A with GH10Xyn were also tested but no viscosity reduction was apparent. 168 Figure 60. In-rheometer reactions of neutral steam-pretreated aspen (N-SP-Asp) at 2.5 % (m/m) with purified enzyme combinations. (A) TrCel7A/HiCel45A (both at 10 mgprotein gcellulose-1). (B) TrCel7A/GH11Xyn (both at 10 mgprotein gcellulose-1). (C) HiCel45A/GH11Xyn (both at 10 mgprotein gcellulose-1). (D) TrCel7A/HiCel45A/GH11Xyn (each at 6.67 mgprotein gcellulose-1). (E) TrCel7A/ HiCel45A /GH11Xyn/GH10Xyn (each at 5 mgprotein gcellulose-1). (F) Summary of logarithmic fits of the N-SP-Asp liquefaction reactions. 0.00.51.01.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)A0.00.51.01.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)B0.00.51.01.50 10 20 30 40 50 60Viscosity (Pa∙s)Time (min)C0.00.51.01.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)D0.00.51.01.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)E0.00.51.01.50 10 20 30 40 50 60Viscosity(Pa∙s)Time (min)FControlT. reesei cocktailTrCel7A/HiCel45A/GH11XTrCel7A/HiCel45A/GH10X/GH11XTrCel7A / HiCel45A TrCel7A / GH11Xyn HiCel45A / GH11Xyn TrCel7A / HiCel45A / GH11Xyn TrCel7A / HiCel45A / GH11Xyn / GH10Xyn 169 However, when TrCel7A, HiCel45A and GH11Xyn were formulated into a ternary enzyme combination, slurry viscosity was reduced nearly two-fold (Fig. 59D). Likewise, the quaternary combination of endoglucanase, cellobiohydrolase, and two xylanases resulted in considerable slurry viscosity reduction (Fig. 60E). Examining the logarithmic fit summary of the different in-rheometer reactions (Fig. 60F), it was evident however that the reduction of the other components through inclusion of GH10Xyn in the mixture reduced the rate and extent of viscosity reduction. This further suggests that the GH10Xyn tested here is not able to catalyze enzymatic liquefaction, neither on its own or in cooperation with other enzymes. Interestingly, both of the purified enzyme mixtures initially reduced slurry viscosity more rapidly than did the complete cellulase cocktail, although eventually the cocktail caught up and surpassed the mixtures in terms of fold-reduction of viscosity. It is possible that the lack of beta-glucosidase or beta-xylosidase in the purified mixtures allowed a build-up of oligomeric saccharides that exerted product inhibition in these reactions, thereby reducing their efficacy (Andrić et al., 2010; Qing et al., 2010), or it might be that other enzymes present in the T. reesei cocktail aided its efficacy. It is worth noting that Kadić and Lidén (2018) recently found that during the enzymatic hydrolysis steam-pretreated softwood, a transient increase in slurry viscosity occurred at the start of the reaction with either a T. reesei cocktail or with the endoglucanase TrCel5A, followed by the usual gradual reduction of viscosity. Similar findings of an initial increase in viscosity were made during enzymatic hydrolysis of organosolv-pretreated sugarcane bagasse with a T. reesei enzyme cocktail (Le et al., 2017). The authors of the latter study reasoned that initial increased in viscosity was due to a separation of particle agglomerates into individual particles, with a corresponding increase in the total number of particles per unit volume. Thus in essence, enzyme action caused deflocculation and increased the crowding number of the slurry. Reflecting on the findings of the current work, it is possible that such deagglomeration occurred simultaneously with mechanisms that reduced viscosity, but was not detected due to no net change or a net loss in slurry viscosity. The increase of viscosity due to deagglomeration may also have been sufficiently small as to evade detection given the general noise of the viscosity signal, which was particularly large for the N-SP-Asp substrate slurries. 6.8 High-solids enzymatic liquefaction with purified enzymes All work examining enzymatic liquefaction thus far, including the work here, has out of necessity been conducted at relatively low solids loadings to allow accurate in situ measurement of 170 viscosity while simultaneously promoting adequate slurry mixing. However, as explored in Section 3 and Section 4, the influence of different substrate characteristics (such as particle morphology, hygroscopy, or surface roughness) on slurry rheology is dependent on the solids loading. Likewise, the work in Section 5 showed that the relative influence of different enzymatic liquefaction mechanisms is dependent on the solids loading of the slurry. It is possible therefore that surveying liquefaction capacity at a relatively low solids loading does not represent the efficacy of enzymatic liquefaction at a high solids loading. To test whether enzymatic liquefaction behaviour at 2.5 % solids examined above with purified enzymes reflects the efficacy of these enzymes at high solids loadings, SP-Asp was hydrolyzed at 10 % solids with 10 mgprotein gcellulose-1 of the purified enzymes applied individually for 4 h. After 4 h of hydrolysis, the reactions were terminated through incubation in a water bath at 95 °C for 30 min, after which the slurries were analyzed for their rheological behaviour, particle length, and extent of hydrolysis (Fig. 61). 171 Figure 61. Purified enzyme reactions with steam-pretreated aspen (SP-Asp) at 10 % solids with 10 mgprotein gcellulose-1 for 4 h at 50 °C, at a reaction volume 50 ml in 100-ml wide-mouth screw-top bottles in duplicate, rotated horizontally at a rotation rate of 10 rpm. Oscillatory rheometry was used to determine complex viscosity (η*; A), storage (G′) and loss (G′′) moduli (B and C), tan delta (D), and yield stress (E). Mean particle lengths were determined using optical fiber analysis (F). Soluble carbohydrates, following acid-hydrolysis to depolymerize oligomers, were determined by HPAEC-PAD (F). HPAEC-PAD was also conducted prior to acid hydrolysis and the chromatograms are shown (H). Note that the baselines have been shifted up for each sample to allow clearer comparison. Fucose was used as an internal standard. 0.010.11101 10η* (kPa∙s)Frequency (Hz)A ControlGH10XynGH11XynHiCel45ATrCel7A1101 10G′(kPa)Frequency (Hz)B0.11101 10G′′(kPa)Frequency (Hz)C0.10.20.30.41 10Tan δ Frequency (Hz)D0200400600ControlHiCel45ATrCel7AGH10XynGH11XynYield stress (Pa)E0100200300400500ControlHiCel45ATrCel7AGH10XynGH11XynParticle length (µm)F0246810HiCel45ATrCel7AGH10XynGH11XynHydrolysis yield (%)G Glu Xyl01002003004000 10 20 30 40 50 60Charge(nC)Time (min)H TrCel7AHiCel45AGH11XynGH10XynFucose Glucose Xylose Cellobiose 172 While at a low (2.5 %) solids loading the endoglucanase HiCel45A showed the highest liquefaction capacity of the purified enzymes, this was not the case at a higher (10 %) solids loading. Surprisingly, hydrolysis with the cellobiohydrolase TrCel7A resulted in the largest reductions in the rheological parameters (complex viscosity, storage modulus, and loss modulus) and yield stress. Following 4 h of hydrolysis, the yield stress of the TrCel7A-treated slurry had reduced to 120 Pa, while that of the HiCel45A-treated slurry had reduced to 290 Pa (Fig. 61E) despite similar extents of particle fragmentation (Fig. 61F). Considerable yield stress reduction likewise occurred for both the GH10Xyn and GH11Xyn-treated slurries, reducing to 440 and 400 Pa, respectively. This was in stark contrast to the low-solids liquefaction tests, where no influence from GH10Xyn on slurry viscosity could be detected. Interestingly, despite a considerable reduction in slurry yield stress, no change in the complex viscosity or storage modulus was detected following hydrolysis with the xylanases (Fig 61A and 61B). However, a considerable drop in loss modulus was measured, which amounted to as much or even more than that of the HiCel45A-treated slurries (Fig. 61C). The efficacy of TrCel7A in promoting enzymatic liquefaction could also be seen in the considerable increase in the loss tangent compared to the control (Fig. 61D), which indicated increased viscous (liquid-like) behaviour. As a result of the lack of change in storage modulus alongside a drop in loss modulus, the xylanase-treated slurries in contrast exhibited a reduction in the loss tangent. The meaning of this reduction in loss tangent is not clear, given that slurry yield stress nonetheless reduced significantly, but might point to the fact that yield stress is a more reliable indicator of slurry behaviour as it relates to enzymatic liquefaction than is the loss tangent. Following rheological characterization, the hydrolysates of the enzyme-treated slurries were collected, acid-hydrolyzed to depolymerize oligomeric saccharides, and then monosaccharides in the hydrolysates were quantified using HPAEC-PAD (Fig. 61G). Surprisingly, some xylan hydrolysis was evident for all reactions, even for reactions with cellobiohydrolase. It is possible that the xylose that was detected was derived from loosely associated xylose or xylooligosaccharides that had been released following interaction of enzymes with the substrate. Such release of xylose has previously been reported in the literature following treatment of pretreated lignocellulose with the non-hydrolytic protein swollenin (Gourlay et al., 2013), and it is therefore possible that cellobiohydrolase here had a similar effect. Comparing the HiCel45A and TrCel7A treatments, hydrolysis with TrCel7A resulted in a slightly higher glucose yield (3.1 % compared to 1.8 % of theoretical yield), which may explain the greater degree of yield stress reduction achieved with TrCel7A. While in general the extents of hydrolysis were rather low (at most 3.1 % yield of glucose and 8.5 % yield of xylose), these 173 small extents of hydrolysis alongside large changes in slurry rheology reflect previous findings in the literature (Gourlay et al., 2018; Skovgaard et al., 2014). The low extents of hydrolysis are also not surprising, considering that enzymatic hydrolysis was conducted for only 4 h at a high solids loading with a low free water content. Moreover, single enzymes were applied, while effective enzymatic deconstruction requires the synergistic cooperation of multiple enzymes (Van Dyk and Pletschke, 2012). Examination of the chromatograms following HPAEC-PAD of hydrolysates without prior acid-treatment (Fig. 61H) indicates that various oligosaccharides were released, particularly for the xylanase treatment (see unlabeled peaks between 30–40 min and 50–55 min). The disparity between enzymatic liquefaction at 2.5 % and 10 % solids reflects the different rheological regimes present at these solids loadings. Previously in Section 5, it was evident that, while particle fragmentation is the dominant mechanism driving enzymatic liquefaction in a dilute (low solids) regime, material dilution and alteration of interparticle interactions become increasingly influential at higher solids loadings. This might be understood through consideration of the extent and nature of fiber network formation in highly concentrated slurries. Within the dense mass of fibers, interparticle interactions are sufficiently extensive that particle fragmentation does not diminish network formation as it would in a dilute regime. This is likely because the forces at the pervasive fiber contacts continue to sustain the network strength, despite reduction of fiber length. Thus, the crowding number remains sufficiently high following particle fragmentation such that the slurry persists in a concentrated regime. In parallel, ongoing hydrolysis at the particle surfaces increases the relative liquid content through material dilution, as well as reducing the strength of interparticle interactions through shaving/smoothing of cellulose fibrils. While endoglucanases have generally been shown to be the most important enzymes in inducing particle fragmentation (Skovgaard et al., 2014; Walker et al., 1992), their influence on material dilution and alteration of particle surfaces may be more limited. Cellobiohydrolases, being the central enzyme of cellulose hydrolysis, can be expected to have the greater influence on material dilution, as was observed here. The processive mode of action of cellobiohydrolases, which results in layer-by-layer erosion of cellulose particles (Arantes et al., 2014; Liu et al., 2011) and smoothing of particle surfaces (Ander et al., 2008; Lee et al., 2000), would permit effective reduction of the strength of interparticle interactions. As the influence of these liquefaction mechanisms will be more influential in a concentrated rheology regime, this could account for the higher yield stress reduction observed with the cellobiohydrolase TrCel7A at 10 % solids compared to the endoglucanase HiCel45A. 174 It has been shown that, following localized weakening of cell walls by enzymatic action, particle fragmentation is dependent on an applied force to break the particles (Thygesen et al., 2014). Accordingly, higher shear rates within stirred-tank reactors have been shown to promote particle fragmentation (Kadić et al., 2014). It is therefore useful to further consider the differences in physical and shear forces the fibers are exposed to in the 2.5 % solids in-rheometer reactions as compared to the 10 % solids horizontally mixed reactions. For the in-rheometer reactions, the particles are subjected to relatively high shear forces, due to continuous mixing of the entire slurry with a vane geometry at a shear rate of 60 s-1. In contrast, the shear forces the particles are exposed to in the horizontally mixed 10 % solids reactions rotated at 10 rpm are relatively low. This is especially true at this higher solids loading, as the particles form agglomerates and move as a coherent mass within which individual particles are relatively immobile and applied stresses are dissipated. Thus, in high-solids horizontally mixed reactions, both the absolute magnitude of the stress applied and the actual stress acting on each particle are lower than during shear-induced mixing within the vane-stirred rheometer. This likely further diminishes the influence of particle fragmentation as a mechanism of enzymatic liquefaction at higher solids loadings. High (10 %) solids reactions with purified enzymes were also conducted with N-SP-Asp to examine whether despite a lack of influence of enzymatic hydrolysis with purified enzymes at low solids, their influence could be detected at high solids loadings. No change was detected in yield stress or other rheological parameters after 3 h nor after an extended hydrolysis of 24 h (data not shown), which was in contrast to the considerable enzymatic liquefaction that occurred with a full cellulase cocktail. These results further stress that enzymatic liquefaction is highly substrate specific, and that liquefaction of N-SP-Asp requires the synergistic cooperation of multiple enzymes. Overall, the results with SP-Asp clearly show that considerable enzymatic liquefaction of an acidic steam-pretreated substrate can be achieved with a relatively low enzyme loading, which could be implemented as a pre-conditioning step ahead of saccharification (Brunecky et al., 2014; Hämäläinen et al., 2016). Furthermore, it appears that the liquefaction-capacity of an enzyme is highly dependent on the substrate solids loading, as well as the method by which liquefaction is tested. While most of the earlier studies in this area used short, in-rheometer reactions at relatively low solids loadings to allow real-time measurement, the results reported here indicate that the liquefaction capacity of an enzyme can be drastically different at higher solids loadings. This was likely due to the difference in rheological regimes, the different physicochemical properties that 175 govern the behaviour within these regimes, and the relative influence of the various enzymatic liquefaction mechanisms. 6.9 Conclusions By comparing a basic T. reesei cellulase cocktail and an advanced, enzyme-enriched cocktail, it was apparent that despite improvements in hydrolysis yields afforded by the cocktail enhancements, enzymatic liquefaction was not more efficient on the basis of yield stress reduction per degree of hydrolysis. These results support the notion that enzymatic liquefaction needs to be considered and optimized independently from bulk saccharification in order to alleviate mass transfer limitations. A commercial hemicellulase preparation was used to examine whether hemicellulases could promote enzymatic liquefaction of differentially pretreated aspen poplar substrates. Nearly complete yield stress reduction was achieved following extended hydrolysis with the hemicellulase preparation for all but the mechanically pretreated substrate. This did indeed suggest that hemicellulases can promote a high degree of enzymatic liquefaction for certain substrates. However, the influence of cellulase contamination in the preparation nor enzyme promiscuity could be excluded, and therefore the use of purified enzymes was next examined. A cellobiohydrolase, TrCel7A, an endoglucanase, HiCel45A, two xylanases from the two most abundant xylanase families, GH10Xyn and GH11Xyn, and a GH3 beta-glucosidase were purified for their application in real-time monitoring of enzymatic liquefaction. This was achieved through hydrolysis of differentially pretreated aspen poplar substrates in a temperature-controlled oscillatory rheometer. The liquefaction-capacity of the different enzymes was shown to be highly substrate-dependent. While TrCel7A or HiCel45A applied individually could reduce slurry viscosity nearly to the same extent as a full enzyme cocktail at half the enzyme loading for acidic steam-pretreated substrates, this was not the case for substrates steam-pretreated at a neutral pH. Perhaps because of the high hemicellulose content of these substrates, N-SP-Asp did not exhibit detectable viscosity reduction following application of any of the enzymes individually. Instead, the synergistic cooperation of the cellobiohydrolase, endoglucanase, and the GH family 11 xylanase together was required in order to achieve viscosity reduction. No viscosity reduction was evident for any of the substrates treated with the purified GH10Xyn, while the purified GH11Xyn achieved marginal viscosity reductions only during hydrolysis of the acidic steam-pretreated substrates. 176 To allow real-time in situ measurement of liquefaction, prior studies reported in the literature used relatively low solids loadings as to allow adequate in-rheometer mixing and simultaneous measurement of viscosity. Out of necessity, our studies were similarly performed at a low (2.5 %) solids loading. When the liquefaction capacity of the purified enzymes used here was examined at a higher (10 %) solids loading using off-line characterization, it was found that the liquefaction-capacity of enzymes can be dramatically different when examined at industrially relevant conditions. At this higher solids loading, the cellobiohydrolase TrCel7A was by far the most efficient in catalyzing enzymatic liquefaction of the acidic steam-pretreated substrate SP-Asp. In contrast, at low solids loadings the endoglucanase HiCel45A was seen to have the highest liquefaction-capacity. While GH10Xyn had no influence on slurry viscosity at 2.5 % solids, at 10 % solids its treatment resulted in a 1.3-fold reduction of yield stress. Evidently, the nature of enzymatic liquefaction and the role of individual enzymes is both highly substrate- and solids loading-dependent. 177 7 Conclusions and future work 7.1 Conclusions This work aimed to provide insight into the rheological challenges posed by conducting enzymatic hydrolysis of lignocellulosic materials at high solids concentrations. It also assessed how effective enzymatic hydrolysis at these conditions is influenced by the nature of the lignocellulosic substrate and the enzymes used. In particular, a major goal was to better understand how, mechanistically, enzymatic liquefaction takes place in order to be able to facilitate efficient bioconversion at high solids loadings. Challenges related to mass transfer and slurry rheology were shown to be key limitations that restricted reaction kinetics at high solids loadings. An important finding made early in the work was that the time required for liquefaction scales as the power of the solids loading, in a comparable fashion to the scaling of slurry yield stress with solids loading. This confirmed that the lack of efficient liquefaction is central to the challenge of high-solids bioconversion, and suggested that gaining a mechanistic and physicochemical understanding of biomass rheology and enzymatic liquefaction would be imperative toward realizing cost-effective biomass valorization. Given the wide variety of possible lignocellulosic feedstocks available and the even greater variety of possible pretreatments for the preparation of bioconversion substrates, it can be expected that this assortment of substrates with different physicochemical properties will have significant variations in their rheological behaviour and thus in their ease of use for high-solid enzymatic hydrolysis. Thus, apart from the direct influence of substrate properties on enzyme–substrate interactions and enzymatic digestibility, the indirect influence of these properties on reaction kinetics through their determination of slurry rheology is an important variable, one which can be examined through rheometry. Through rheometry of a range of differently sourced and/or differently pretreated woody substrates, slurry rheological behaviour was confirmed to be highly variable, showing up to two orders of magnitude yield stress difference between different substrates. While no single measured property correlated strongly to rheological parameters when examined across all substrates, both particle morphology and substrate hygroscopy were shown independently among substrate subsets to strongly influence slurry rheology. Substrate hygroscopy appeared to predict the degree of yield stress scaling with solids loading among similarly pretreated substrates, as well as correlating to the solids loading at which free water depletes in the slurry, at which point the slurry 178 reached a mass transfer boundary. Particle morphology, examined through a mean particle aspect ratio, most strongly correlated to rheological behaviour when examined through factorial regression, explaining up to 50.9 % of the variation in the power law exponent b across all substrates used in the thesis work. An additional important point that became clear through this work was that, while the ‘high solids’ state is often defined as being above a specific solids loading, from a rheological point of view, the ‘high solids’ regime seems to be a relative condition specific to each substrate, dependent on the properties of the substrate and their influence on slurry yield stress and free water content. To examine the relationship between substrate composition, slurry rheology and the efficiency of high-solids enzymatic hydrolysis in a more systematic manner, extensive rheological characterization of differentially pretreated aspen poplar substrates varying in their biopolymer composition and physicochemical properties was undertaken. The pretreatments were particularly designed to vary the relative amounts of cellulose, hemicellulose and lignin in order to examine the influence of the hydrophobic polymer lignin versus the influence of the hydrophilic polymers cellulose and hemicellulose in establishing slurry rheology and enzymatic liquefaction efficiency. It was evident from a near order-of-magnitude increase in yield stress following delignification of a steam-pretreated aspen substrate that retention of lignin in the insoluble fraction may be beneficial for high-solids rheology, particularly if the lignin is deposited on particle surfaces to reduce the strength of interparticle interactions and if it is modified to have low enzyme-binding capacity. At the same time, fractionation of the hydrophilic polymer hemicellulose into the soluble fraction during pretreatment, such as during acidic steam-pretreatment, appeared to be beneficial by reducing substrate hygroscopy. To examine whether rheological behaviour of these substrates is connected their high-solids hydrolysis kinetics, enzymatic liquefaction of the aspen substrate variants was tracked using oscillatory rheometry, and hydrolysis efficiency measured at increasing solids loadings. In doing so, slurry rheology was shown to be clearly predictive of both the rate of enzymatic liquefaction and overall reaction efficacy. Specifically, it was shown that the more favourable the rheological properties of a substrate were, the more rapid its liquefaction and the less its hydrolysis yield was affected by an increase in solids loading (i.e., the less strong its ‘solids effect’). Optimization of substrate pretreatment should therefore be directed toward producing slurries displaying favourable rheology with minimal yield stresses, which may be achieved by reduction of substrate particle aspect ratios and reduction of substrate hygroscopy through retention of lignin in the substrate while removing the hydrophilic polymer hemicellulose. 179 Throughout the work in the thesis, certain substrate treatments that improve accessibility of the cellulosic component of lignocellulosic biomass were seen to paradoxically decrease hydrolysis efficiency at high solids loadings. For example, while substrate disc-refining or laccase-mediated hydrophilization of lignin improved enzymatic hydrolysis when tested at low solids loadings, the increased fibrillation and water retention capacity respectively imparted on the substrates by these treatments significantly increased slurry yield stresses at high solids loadings. As a result, mass transfer worsened at high solids loadings and hydrolysis yields dropped considerably below that of the control. Therefore, while substrate digestibility tests are generally performed at low solids loadings for convenience, it is important that the efficacy of substrate treatments that aim to ‘open up’ the lignocellulosic matrix are also tested at industrially relevant high-solids conditions. Although various mechanisms have been proposed to account for the observed slurry viscosity reduction during enzymatic liquefaction, evidence for these mechanisms remains sparse. Through an examination of substrates specifically prepared to highlight specific structural changes occurring during enzymatic hydrolysis, the mechanisms that may play a role in enzyme-mediated liquefaction were investigated. Particle fragmentation, material dilution and alteration of interparticle interactions all appeared to contribute to the reduction of slurry yield stress/viscosity. Reduction of substrate water retention capacity, despite having been proposed to account of enzymatic liquefaction in the literature, did not appear to be a viable mechanism. It furthermore appeared that the mode of liquefaction is context-dependent, in that the relative influence of the different enzymatic liquefaction mechanisms depends on the substrate properties and solids loading/rheology regime. For example, material dilution was seen to have little influence at low solids loadings but it becomes an essential mechanism at high solids loadings, while particle fragmentation is more influential for substrates with high particle aspect ratios and becomes less influential at higher solids loadings. In a comparison of a basic and an advanced, enzyme-enriched commercial cellulase cocktail, it was apparent that despite improvements in cellulose hydrolysis efficiency, these enhancements have not resulted in more efficient enzymatic liquefaction. This suggested that, apart from the differing roles of enzymes with regard to liquefaction and saccharification examined in earlier work, that the ‘ideal’ composition of cellulase cocktails may not be the same for high-solids as it is for low-solids enzymatic hydrolysis. Therefore, enzyme cocktails may need to be independently optimized for enzymatic liquefaction. To try to gain a better understanding of the roles of enzymes in enzymatic liquefaction, purified cellobiohydrolase (TrCel7A), endoglucanase (HiCel45A) and glycoside hydrolase family 10 and 11 xylanases (GH10Xyn and GH11Xyn) were assessed for their liquefaction 180 capacity with differentially pretreated poplar substrates in real time with in-rheometer reactions. In order of efficacy, HiCel45A and TrCel7A could both catalyze viscosity reduction to nearly the same extent as a full cellulase cocktail, at half the enzyme loading. However, this was highly substrate dependent. For example, a substrate steam-pretreated at neutral pH required the synergistic cooperation of cellobiohydrolases, endoglucanases, and xylanases in order to be enzymatically liquefied; application of these enzymes on their own did not result in any viscosity reduction. The role of individual enzymes was also strongly dependent on the solids loading. Enzymatic liquefaction of an acidic steam-pretreated substrate was most efficiently catalyzed by endoglucanases at low solids loadings, while at high solids loadings, cellobiohydrolases had the dominant liquefaction role. Likewise, while application of the GH10Xyn at low solids did not result in any viscosity reduction, at a high solids loading its application resulted in a 1.3-fold reduction of slurry yield stress. As was hypothesized, the mechanisms of enzymatic liquefaction and the roles of individual enzymes in catalyzing these mechanisms thus were seen to be dependent on the rheology regime. In summary, this work provided rheological and enzymological insights into the highly disparate reaction kinetics and rheological challenge prevailing at commercially relevant substrate concentrations. The influence of substrate physicochemical and water-interaction properties was shown to be central in determining the extent of the rheological challenge. Optimizing pretreatment strategies to produce substrates with favourable rheological properties will likely provide considerable benefit for biorefining efforts. Nonetheless, the inherently fibrous and hygroscopic nature of lignocellulosic biomass remains a considerable challenge, and promotion of an efficient enzymatic liquefaction phase was indicated to be an important strategy for alleviating this challenge. Importantly, enzymatic liquefaction and the role of individual enzymes was shown to be highly substrate and solids-loading dependent. Future work will therefore need to combine pretreatment optimization and enzyme cocktail customization toward specific biorefining feedstocks to allow efficient enzyme catalysis at high solids loadings. 7.2 Future work 7.2.1 Development of biomass pretreatments that produce more favourable substrate slurry rheology Slurry rheology strongly influences the efficacy of enzymatic hydrolysis at high solids loadings. Traditionally, the efficacy of pretreatment methods is surveyed at low solids loadings where 181 the impact of slurry rheology goes unnoticed. As the processability and digestibility of the resulting substrates at high solids loadings has been largely overlooked, identifying pretreatment methods that result in favourable slurry rheology in order to improve industrial processing of lignocellulosic biomass should be a priority. 7.2.2 Screening for high-liquefaction-capacity enzymes Enzymatic liquefaction of lignocellulose slurries was shown in this thesis to be highly dependent on the nature of the substrate, the enzymes, and the solids loading of the reaction. This suggests the need for more work on identifying/discovering enzymes that can effectively catalyze yield stress/viscosity reduction at high solids loadings of substrates with differing compositions. Particularly, it would be beneficial to formulate a liquefaction cocktail containing highly thermostable enzymes, so that they could be applied during passive cooling following pretreatment ahead of saccharification. Such efforts should be pursued alongside and in combination with the aforementioned optimization of pretreatment strategies, given the substrate-dependent nature of enzymatic liquefaction. 7.2.3 Optimization of high-solids bioconversion through process design Previous work has explored a pre-hydrolysis step for viscosity reduction with low loadings of individual enzymes such as endoglucanases in order to enable subsequently enhanced reaction kinetics (Brunecky et al., 2014; Hämäläinen et al., 2016). Further examination of the process design of enzymatic hydrolysis and optimization of enzymatic liquefaction, similar to what has been done in the starch bioconversion industry, could likely prove essential in facilitating cost-effective biorefining of lignocellulosic biomass at industrially relevant conditions. 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Thesis/Dissertation
eng
Forestry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
The influence of enzymatic liquefaction and slurry rheology on high-solids cellulose hydrolysis
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