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B. De Baere et al. / Chemical Geology 413 (2015) 107–118
Elsevier
De Baere, Bart
François, Roger
Mayer, K. Ulrich
We explore the applicability of on-line flow-through time-resolved analysis (FT-TRA) to measure mineral dissolution rates, determine dissolution rate parameters, and monitor dissolution stoichiometry under both constant and transient eluent conditions. A custom-built automated flow-through system is used to subject mineral samples to controlled eluent flows of constant or varying composition, and the dissolution products aremeasured online with a quadrupole ICP–MS. Because forsterite dissolution has been extensively studied, this mineral provides an ideal benchmark to test the approach. FT-TRA has several advantages compared to the mixed-flow reactors conventionally used to measure mineral dissolution. The mineral dissolution regime (surface vs transport-controlled) can be readily established prior to conducting dissolution experiments, which is important if the goal of the experiment is to determine dissolution rate parameters. Because of the small volume (25 μL) of the flow-through reactor, the time to reach steady state concentration in the effluent is shorter and is limited by the intrinsic properties of the mineral, instead of the residence time of the effluent in the reactor. For minerals reaching steady-state dissolution rapidly, dissolution rate parameters (rate constant(s) and reaction order(s)) are established in a fewhours, allowing for replications, statistical analysis of the results, and investigation of the underlying causes of variability. The experimental set-up can be adapted for minerals that require longer periods of time to reach steady-state dissolution. In addition, FTTRA lends itself particularlywell for detailed monitoring of dissolution rates and dissolution stoichiometry under transient conditions. For forsterite dissolution under acidic conditions, preferential release ofMg when pH transits to lower values, and preferential release of Siwhen pH transits to higher values is clearly documented and can be interpreted as indicating changes in the mean depth of the Si-rich surface layer in response to changes in eluent acidity. Episodes of exfoliation of the Si-rich surface layer can also be identified, providing a means to study one of the potential rate limiting steps for CO2 sequestration by carbonation of olivine. The results presented here indicate that FT-TRAwith online ICP–MS analysis could be a useful andmultifaceted addition to the toolbox available to study mineral dissolution.
ngs07 MReceived in revised form 22 August 2015Accepted 26 August 2015Available online 2 September 2015Keywords:Mineral dissolutionDissolution rateForsteriteFlow-through dissolutionStoichiometryExfoliationtransient eluent con-ion kinetics have beenudies (Rimstidt et al.,s the results obtainedChemical Geology 413 (2015) 107–118Contents lists available at ScienceDirectChemicall seble of rapidly generating data on mineral dissolution rates would bebeneficial to study the factors underpinning the variability of this pro-cess and to better constrain random errors. Likewise, methods provid-with the new approach. In addition, its dissolution rate below pH 6 isrelatively rapid and controlled by the activity of protons, resulting in asimple linear relationship between the logarithm of the surface normal-solution rates measured in different laboratories can differ by severalorders of magnitude (e.g. Rimstidt et al., 2012), and this problem iscompounded by the fact thatmethods used tomeasuremineral dissolu-tion rates tend to be labor intensive and time consuming.Methods capa-lution rate and stoichiometry under constant andditions. Forsteritewas chosen because its dissolutwell characterized in a number of laboratory st2012), providing a robust benchmark to assesAccurate determination of mineral dissolution rates over a widerange of conditions (pH, temperature, pCO2, etc.) is essential to investi-gate a wide variety of environmental processes. However, mineral dis-controlling mineral dissolution. This study uses forsterite to explorethe applicability of “flow-through time resolved analysis” (FT-TRA)with on-line measurement of dissolution products by inductivelycoupled plasmamass spectrometry (ICP–MS) tomeasuremineral disso-ing information on dissolution rate and sto⁎ Corresponding author.E-mail addresses: b.debaere@alumni.ubc.ca (B. De Bae(R. François), umayer@eos.ubc.ca (K.U. Mayer).http://dx.doi.org/10.1016/j.chemgeo.2015.08.0240009-2541/© 2015 Elsevier B.V. All rights reserved.steady-state or transient conditions would help elucidate the factors1. IntroductionLeached layerlution rates, determine dissolution rate parameters, and monitor dissolution stoichiometry under both constantand transient eluent conditions. A custom-built automated flow-through system is used to subject mineral sam-ples to controlled eluentflows of constant or varying composition, and thedissolution products aremeasured on-linewith a quadrupole ICP–MS. Because forsterite dissolution has been extensively studied, thismineral providesan ideal benchmark to test the approach.FT-TRA has several advantages compared to the mixed-flow reactors conventionally used to measure mineraldissolution. The mineral dissolution regime (surface vs transport-controlled) can be readily established priorto conducting dissolution experiments, which is important if the goal of the experiment is to determine dissolu-tion rate parameters. Because of the small volume (25 μL) of the flow-through reactor, the time to reach steadystate concentration in the effluent is shorter and is limited by the intrinsic properties of themineral, instead of theresidence time of the effluent in the reactor. For minerals reaching steady-state dissolution rapidly, dissolutionrate parameters (rate constant(s) and reaction order(s)) are established in a few hours, allowing for replications,statistical analysis of the results, and investigation of the underlying causes of variability. The experimental set-upcan be adapted for minerals that require longer periods of time to reach steady-state dissolution. In addition, FT-TRA lends itself particularly well for detailedmonitoring of dissolution rates and dissolution stoichiometry undertransient conditions. For forsterite dissolution under acidic conditions, preferential release of Mg when pH tran-sits to lower values, and preferential release of Siwhen pH transits to higher values is clearly documented and canbe interpreted as indicating changes in the mean depth of the Si-rich surface layer in response to changes in el-uent acidity. Episodes of exfoliation of the Si-rich surface layer can also be identified, providing a means to studyone of the potential rate limiting steps for CO2 sequestration by carbonation of olivine. The results presented hereindicate that FT-TRAwith online ICP–MSanalysis could be a useful andmultifaceted addition to the toolbox avail-able to study mineral dissolution.© 2015 Elsevier B.V. All rights reserved.Article history:Received 17 March 2015We explore the applicability of on-line flow-through time-resolved analysis (FT-TRA) to measuremineral disso-a b s t r a c ta r t i c l e i n f oMeasuring mineral dissolution kinetics usiresolved analysis (FT-TRA): an exploratoryBart De Baere ⁎, Roger François, K. Ulrich MayerDepartment of Earth, Ocean and Atmospheric Sciences, University of British Columbia, 2020-22j ourna l homepage: www.eichiometry under non-re), rfrancoi@eos.ubc.caon-line flow-through timetudy with forsteriteain Mall, Vancouver, BC V6T 1Z4, CanadaGeologyv ie r .com/ locate /chemgeoized dissolution rate and pH (e.g. Chen and Brantley, 2000).In the proposed flow-through system, the amount of mineral sub-jected to dissolution (10–20 mg) and the volume of the reactor(25 μL) are much smaller than for the mixed flow reactors commonlyused to estimate mineral dissolution rate parameters, and the resultingthat precipitation of secondary minerals can be avoided by removingthe dissolution products before they reach saturation in the reactor.Hence, mixed flow reactors have generally been the preferred tech-nique for measuring mineral dissolution rates.Both batch and mixed flow reactors require a considerable amountof time to conduct the necessary measurements and calculate dissolu-tion rate constants, from a few to 1000s of hours per experiment cover-ing a single experimental condition (e.g. Brantley and Chen, 1995).Dissolution is typically monitored ex-situ, and a series of experimentsneeds to be carried out to cover a range in experimental conditions be-fore dissolution rate constants can be calculated. Furthermore, aftercompiling all available data on forsterite dissolution rate as a functionof pH and temperature, Rimstidt et al. (2012) concluded that the stan-dard deviation of dissolution rates measured in different studies is300-fold, i.e. more than ten times larger than expected from analyticaluncertainties alone (Rosso and Rimstidt, 2000). Discrepancies betweenstudies have been mostly attributed to surface normalization, which isgenerally done using “geometric” surfaces, calculated from mineralgrain diameter, or “BET” surface, measured by gas adsorption. These op-erationally defined surface areas are not necessarily proportional to thedown to a 63–150 μm size fraction. Sample treatment was limited to ul-108 B. De Baere et al. / Chemical Geology 413 (2015) 107–118ratio of mineral surface area to reactor volume (A/V) much higher. Be-cause of its very small volume, much shorter eluent residence timescan be achieved in the reactor (seconds vs. hours), which is key to re-ducing the time needed to reach steady state dissolution. On-line anal-ysis of the dissolution products by ICP–MS provides real-timeinformation on the evolution of the mineral dissolution conditions(steady-state or not) and stoichiometry (congruent vs incongruent dis-solution). In addition, ICP–MS low detection limits and wide dynamicrange allow for the simultaneous measurement of major and minor el-ements released during dissolution. Low detection limits could also fa-cilitate the study of minerals dissolving very slowly. The goals of thisstudy are to establish whether this approach can provide a means tomeasure mineral dissolution rates under a range of conditions morerapidly than with mixed flow reactors, whilst also providing insightsinto mineral dissolution under transient eluent and non-steady-statemineral surface conditions.2. BackgroundMost dissolution rate studies (including the present study) are con-ducted under “far-from-equilibrium” conditions. Under these condi-tions, mineral dissolution is affected by a number of intrinsic andextrinsic parameters (e.g. Fischer et al., 2014). Intrinsic parametersinclude mineral composition, crystal structure and surface nanoscalefeatures (terraces, step edges, kinks, screw dislocations). Extrinsic pa-rameters consist of temperature, the composition of the fluid in whichthemineral is dissolving (pH, degree of undersaturation, ionic strength,pCO2, etc.) and thedissolution regime (surface vs. transport-controlled).Rate laws most commonly used to describe the dissolution rate of min-erals under far-from-equilibrium, surface controlled conditions can begeneralized by Eq. (1) (e.g. Lasaga, 1984):Rf ¼mm0 nAXNpi¼1ki aini ð1ÞwhereRf overall dissolution rate (moles s−1)m moles of mineral at a given timem0 initial moles of mineral presentn factor that accounts for changes in surface area during disso-lution (n = 2/3 for single uniformly dissolving spheres andcubes, Appelo and Postma, 2005).A surface area (m2).Np number of parallel reaction pathways leading to dissolutionki rate constant associated with aqueous species i (molesm−2 s−1)*ai activity of aqueous species ini reaction order*Assuming that aini is treated as a dimensionless term.For a given mineral, its surface-normalized rate of dissolution (Rf/A;moles m−2 s−1) depends on its intrinsic properties, which dictate therate constants (ki's) and reaction orders (ni's), and the activity of aque-ous species that control dissolution (ai's).Mineral dissolution rates are most commonly measured in batch re-actors or mixed flow reactors. Batch reactors are closed systems inwhich mineral dissolution is allowed to proceed towards equilibrium.The concentrations of elements of interest are measured as a functionof time and fitted to a presumed rate law. In contrast, mixed-flow reac-tors are open systems in which the solvent and dissolution productscontinuously flow in and out of the reactor. Measurements are typicallymade after the reactor has reached steady-state, i.e. when the eluentcomposition is constant, which is achievedwhen the rate of element re-lease from mineral dissolution is equal to its rate of removal from thesystem with the effluent. A key benefit of the mixed flow reactors istrasonic cleaning with acetone until a clear supernatant was obtained.The sample was dried overnight in an oven at 60 °C. The mineral grainswere examined by scanning electron microscopy (SEM), which revealedthat they were generally free of adhering fine particles (Fig. 1). The sam-ple had a purity of 98.8% forsterite (quartz=0.9% and pyrite=0.3%), de-termined by quantitative XRD. Forsterite stoichiometry was establishedby total digestion and elemental analysis (Mg1.81Fe0.18Ni0.01SiO4; Fo91).Surface area was measured using multi-point BET (Brunauer et al.,Fig. 1. SEM image at low magnification ×180 of the forsterite sample used in this study,“reactive” surface area (White and Peterson, 1990) or the concentrationof reactive surface sites that controls the rate of dissolution. The concen-tration of reactive surface sites may not be uniformly distributed onmineral surfaces and may vary as mineral dissolution proceeds (e.g.Lüttge et al., 2013). Sample preparation (e.g. grinding methods) is an-other uncontrolled factor that could affect reactive site density and dis-tribution and contribute to the variability in dissolution rate constantsestimated in different laboratories.3. Materials and methods3.1. MaterialsForsterite grains were obtained from Ward's Natural Science (item#491,557). Transparent mineral grains were handpicked, and groundafter acetone cleaning.1938)with N2 adsorption using a Quantachrome Autosorb-1 surface areaanalyzer.3.2. Flow-through dissolution moduleA flow-through dissolution module was built by simplifying theoriginal design developed by Haley and Klinkhammer (2002). A sche-matic of the FT-TRA module is shown in Fig. 2. Eluents are pumpedfrom individual bottles (E1–E4) by a Dionex ICS-3000 dual pump(designed using an entirely metal-free (PEEK) flow-path) equippedwith time-programmable proportioning valves. The gradient pumpwas programmed to control the time-dependent composition of the el-uent (for the experiment) or standard (for calibration). The isocraticpump continuously supplies an internal standard (indium, in bottleE5) to correct for instrumental drift associated with the on-line mea-surement of effluent concentration by Inductively Coupled PlasmaMass Spectrometry (Agilent 7700× quadrupole ICP–MS). Programmingof the gradient pump is done using the Chromeleon® ChromatographyData System. The generated eluent either directly joins the internalstandard stream (when running standards) or passes through a flow-through cell (when running samples) before merging with the internalstandard stream. Here, the flow-through cell containing the sampleconsists of a 13 mm diameter Millex® syringe filter with a PTFEmembrane (0.2 μm, Millipore catalog #SLLGC13NL) mounted betweentwo computer controlled parallel solenoid valves (NResearch, Inc.,#225T092C). Effluent pH measurement with a Bio-Rad DuoFlow in-line pH electrode (Catalog number 760–2040) is optional for dissolutionexperiments expected to result in measureable pH changes (N0.1 pHhercomvalcons109B. De Baere et al. / Chemical Geology 413 (2015) 107–118Fig. 2. Schematic of the flow-through dissolutionmodule. E1–E5 represent eluent bottles, winternal standard. Eluent flows top to bottom of figure. The use of 2 parallel multi-positionblanks and samples over the course of a day. When running standards, the multi-positionthrough module allows for time-resolved control of incoming eluent composition, and athe effluent stream by quadrupole ICP–MS. (For interpretation of the references to color in thise E1–E4 are used to generate eluents or standards and E5 is used to continuously supply anputer controlled solenoid valves with 6 sample positions allow for the efficient analysis ofves (holding the flow-through cell) is bypassed (as indicated by the red line). This flow-tant, reproducible flow rate through the flow-through cell, for time-resolved analysis offigure legend, the reader is referred to the web version of this article.)unit). When dissolving forsterite in our experiments, pH changes were≪0.1 pH unit and thus impossible to record with the present system.The pH reported in our experiments is the pH of the incoming solutions.Forsterite subsamples were weighed on a Mettler Toledo XP6 mi-crobalance, inserted into the upstream side of the filter and continu-ously exposed to a pre-programmed eluent sequence at roomtemperature. The eluent was in contact with ambient atmosphericpCO2. The flow rate used in all experiments was 0.7 mL min−1(±1.6%; 95% CI), resulting in an eluent residence time of ~2.1 s inthe reactor, based on a syringe filter internal volume of 25 μL. The ef-fluent combined with the internal standard was then introduced di-rectly into the plasma of an ICP–MS for time-resolved measurementHNO3) for calibration. The range of concentrations measured in thismeasured every 1.8 s and the eluent residence time was 2.1 s, effluentconcentration data was smoothed using a 5-point running average toreflect the renewal time of the eluent in the reactor.3.4. Flow-through dissolution experiment designSeveral experiments were conducted to explore the potential appli-cations of the FT-TRA experimental set up.3.4.1. Dissolution rate parametersTo provide a comparison with previous studies, a dissolution exper-iment was specifically designed to calculate the dissolution rate param-amprfact.ple7 ×4 ×1 ×8 ×8 ×5 ×7 ×8 ×110 B. De Baere et al. / Chemical Geology 413 (2015) 107–118study was 0.6×10−6 moles L−1 to 3.5×10−6 moles L−1 for Mg and0.3×10−6 moles L−1 to 1.8×10−6 moles L−1 for Si. Relative error onconcentrations (95% confidence interval) ranged from 2.6% to 4.6% forMg and from 4.9% to 14.4% for Si, from high to low concentration. Thelower precision for Si measurements is attributed to higher blanksresulting from the use of a glass spray-chamber with the ICP–MS.Blank filters were run using identical eluents as used in sample runs.Blank corrections were 0.014±0.002×10−6 moles L−1 for Mg and0.19±0.02×10−6 moles L−1 for Si. Although high, the Si blank wasvery stable, allowing measurements of blank-corrected Si concentra-tions as low as 0.2×10−6 moles L−1. Although the glass spray chamberis not prohibitive, in future studies it will be preferable to replace it witha Teflon spray chamber. As blank-corrected concentrations wereTable 1Weight (g) and surface area (m2) of forsterite used in the “dissolution regime” experiment (sexperiments (samples 4–8). Surface areas are calculated from the sample weight and BET suSample loss is estimated by integrating the total moles of Mg released during each experimenSample Experimental pH Sam1 2.3 (constant) 8.12 5.6–4.0–3.5–3.0–2.3 (step-wise decrease) 20.23 5.6 (constant) 22.04 2.3–5.6 (transient/constant) 17.75 2.3–5.6 (transient/constant) 13.56 2.3–5.6 (transient/constant) 12.87 2.3–5.6 (transient/constant) 20.28 2.3–5.6 (transient/constant) 17.7of 24Mg, 28Si and 115In.The main difference between this experimental set-up and mixedflow reactors is the very small size of the reactor and mineral samples,the short residence time of the eluent in the reactor and the shorttime of contact between eluent and mineral. Mixed flow reactors haveto be well mixed because concentration measurements are conductedon a small subsample of the entire volume of the reactor. FT-TRA isnot a mixed flow reactor in the sense that the reactor does not need tobe well mixed, because the volume of the cell is renewed entirelyevery 10 s (5 × 2.1 s). On this time scale, mass balance dictates thatthe elemental concentration of the eluent times flow rate must beequal to the rate at which the element is released by dissolution of themineral (assuming full exposure of the mineral to the eluent).3.3. Measurements ofmagnesium and silicon concentration in the eluent byon-line quadrupole ICP–MS24Mg, 28Si, and 115In counts per second (cps) were recorded usingthe time resolved analysis setting on an Agilent 7700× quadrupoleICP–MS in He-mode. Counts per second obtained were corrected for di-lution caused bymerging eluent and internal standard streams (eluentsand standards had a flow rate of 0.7 mL min−1 while the internal stan-dard flow ratewas 0.1mLmin−1). Dilution corrected counts per secondwere 115In normalized to correct for instrumental drift over the courseof an experiment. A high concentration standard in 1% HNO3 was dilut-ed in known time-resolved proportions with the standard matrix (1%eters of forsterite (kH+ and n). For that purpose, dissolution ratesmust bemeasured at steady-state and under surface-controlled conditions. Toestablish whether the latter condition is met in our experimental de-sign, a series of dissolution experiments was carried out using aforsterite subsample (sample 1, Table 1), which was exposed to a nitricacid solution at pH 2.3 under different flow rates ranging from 0.01 to0.7 mL min−1, and maintained until steady-state [Mg, Si] concentra-tions were reached.Once surface-controlled conditionswere confirmed, another forsteritesubsample (sample 2: BET surface area of 3.39 × 10−2 m2 g−1; Table 1)was subjected to eluents with pH decreasing stepwise (5.6, 4.0, 3.5, 3.0,2.3), and the durations of the pH plateaus were maintained until theon-line ICP–MSmeasurements indicated steady-state Mg and Si concen-trations. The dissolution experiment on sample 2 lasted approximately234 min to cover all 5 pH steps. Because steady-state dissolution couldnot be achieved at pH 5.6, another experiment was conducted by expos-ing a third forsterite subsample (sample 3; Table 1) to deionized water(DIW) only for a longer period of time (224 min).3.4.2. Dissolution under transient conditions and replicationReplicate analyses were conducted with five subsamples from thesame forsterite sample. In each of the five experiments, a sample wasweighed (samples 4–8, Table 1) and subjected first to a continuousflow of distilled, de-ionized water (DIW; pH = 5.6) for ~1950 s(32.5 min). Eluent acidity was then gradually ramped up by mixingHNO3 (1%) to decrease eluent pH to 3.3, which was maintained for1200 s (20 min). Afterwards, eluent acidity was ramped up further todecrease eluent pH to 2.3, which was maintained for ~1400 s(23 min) before raising the eluent pH back to pH= 5.6 (DIW). EffluentMg and Si concentrations were continuously measured, providing dis-solution rate data over a range of pH (5.6 to 2.3) in less than 9000 s(150min). The goals of this experiment are to assess reproducibility be-tween subsamples and to document transient dissolution patterns.3.5. Calculation of surface normalized dissolution rates and dissolution rateparameters (kH+, nH+)Surface area normalized forsterite dissolution rates (molesm−2 s−1) as a function of pH are calculated by multiplying the time re-solved concentrations (moles L−1) of Mg or Si by the eluent flow ratele 1), the “rate parameters” experiment (samples 2, 3) and the “replication” and “transient”e measurements (samples 1, 4–8: 2.57 × 10−2 m2 g−1; samples 2, 3: 3.39 × 10−2 m2 g−1).weight g A (× 10−4 m2) Experimental sample loss %10−3 2.10 0.3010−3 6.88 0.2810−3 7.48 0.2010−3 4.58 0.3210−3 3.49 0.3310−3 3.31 0.2110−3 5.21 0.2210−3 4.58 0.26stepwhenpHdecreases, and continue to increasemore gradually there-after, suggesting a gradual increase in active surface area (consistentwith the increase in surface area when forsterite is immersed in acidicsolutions for 24 h; Pokrovsky and Schott, 2000b). Concentrations even-tually plateau at each pH step.To calculate dissolution rate parameters, we used the on-line ICP–MS data to monitor the time needed to reach or approach steady-statedissolution before changing the pH of the eluent. Time segments withconstant Mg and Si concentrations were then selected on each plateau(Fig. 4A) and averaged to quantify kH+ and nH+ by weighted linear re-gression (Fig. 4B), following Eq. (4). Weights were allocated accordingto the number of data points collected at constant Mg and Si concentra-tions. Since steady state dissolution could not be reached in DIW, onlydata obtained at pHs 4.0, 3.5, 3.0 and 2.3 were considered.Dissolution rate parameters obtained in this experiment are in rea-sonable agreement with previous studies, and fit best with the resultsfrom Pokrovsky and Schott (2000a) (Table 2; Fig. 5). The dissolutionrate measured at pH 4.0 deviates slightly from the linear trend, particu-larly when calculating forsterite dissolution rates fromMg release rates(Fig. 4B). This may indicate that at this pH, although Mg concentrationsappeared to have reached a plateau (Fig. 4A), these concentrations maystill have been decreasing very slowly. This is further supported by therelatively high Mg/Si also obtained at pH 4.0 (2.13 ± 0.16) comparedto forsterite stoichiometry (1.81± 0.07), indicating that the Si-rich sur-Fig. 3.Average steady stateMg (A) and Si (B) concentrations (sample 1) versus eluent res-idence time (calculated by dividing flow cell volume (25 μL) by varying eluent flow rates).111B. De Baere et al. / Chemical Geology 413 (2015) 107–118(Q; L s−1) and dividing by the sample surface area (A.; m2), taking intoaccount the stoichiometry of the forsterite used in the experiment(Mg1.81Fe0.18Ni0.01SiO4; Fo91):Surface normalized dissolution rates (moles forsterite m−2 s−1) =Mg½ =1:81 moles L−1  Q L s−1  =A m2  ð2aÞSi½  moles L−1  Q L s−1  =A m2 : ð2bÞTo describe forsterite dissolution in our experimental set up, Eq. (1)can be simplified. It has been previously determined that forsterite dis-solution between pH 1 and 6 only depends on the activity of H+ (Np =1). In addition, since only a very small fraction of the sample is dissolvedduring the experiments (Table 1),m/m0≈ 1. Thus, Eq. (1) can be simpli-fied to:Rf moles s−1 ¼ A kHþ  aHþ n ð3Þwhich results in a simple linear relationship between the logarithm ofthe surface normalized forsterite dissolution rate (r= Rf/A) and pH:log rð Þ ¼ logkHþ−npH: ð4Þ4. Results and discussion4.1. Determination of forsterite dissolution rate parameters4.1.1. Forsterite dissolution regimeDissolution under surface-controlled conditions, as opposed totransport-controlled conditions, is a pre-requisite to obtain dissolutionrate constants that are intrinsic to themineral studied and independentof experimental conditions during measurement (e.g. Colombani, 2008and references therein). Sample 1 (Table 1) was dedicated to evaluatingthe dissolution regime of forsterite in our experimental set up at pH 2.3.Steady state [Mg, Si] concentrations reached at constant eluent pH of 2.3but at differentflow rates increase linearlywith the residence timeof el-uent in the reactor, indicating that the forsterite dissolution rate is con-stant and independent of flow rate (Mg: Fig. 3A; Si: Fig. 3B). This is takenas an indication that dissolution in our experimental set up at pH 2.3 issurface-controlled, i.e. the rate of detachment of dissolving species fromthe mineral surface is slower than the rate at which dissolved productsdiffuse to the bulk solution, and the rate of diffusion of H+ from the bulksolution to the mineral surface is faster than the rate of consumption ofprotons by the surface reaction. A telltale sign of transport controlwould be a decrease in dissolution rates with decreasing flow rate, indi-cating that transport through the widening boundary layer at the inter-face between solution and grain surface limits, or at least contributes tolimiting the dissolution rate (transport or mixed controlled regimes).We thus conclude that forsterite dissolution is surface-controlled atpH 2.3. A more complete investigation of dissolution regime using FT-TRA is presented in a companion paper (De Baere et al., submitted forpublication).4.1.2. Forsterite dissolution under acidic conditionsTo validate our proposedmethodology for the determination of dis-solution rate parameters, the time-resolved [Mg, Si] concentrations andMg/Si molar ratios measured during the dissolution of sample 2(Fig. 4A) were used for comparison with previous studies. Mg and Siconcentrations are initially high and decreased sharply during the firstdissolution step in DIW at pH 5.6 without reaching steady-state afternearly 90min of dissolution. Such a dissolution pattern (parabolic kinet-ics) is attributed to the faster dissolution of high surface free energy sitesthat have been produced during sample preparation (Chou andWollast,1984). Subsequently, Mg and Si concentrations increase sharply at each face leached layerwas still deepening. Si-based dissolution rates deviateFig. 4. (A) [Mg] (5-point running average in black), [Si] (5-point running average in gray) andMg/Simolar ratio (red) in the eluent resulting from thedissolution of sample 2. Forsteritewassubjected to acidic solutions (DIW and HNO3) of decreasing pH (5.6, 4.0, 3.5, 3.0, 2.3) maintained until steady state dissolution was reached or approached. Time step for Mg and Si mea-surements by ICP–MS is 1.8 s, hence the 5-point average is shown to represent the eluent reactor renewal time. Thedashed lines indicate the stoichiometricMg/Si ratio of forsterite (1.81±0.07). (B) Forsterite dissolution rates estimated from average [Mg] (filled circles), and average [Si] (open diamonds) concentration plateaus at each pH. [Mg]were divided by 1.81 to takeinto account forsterite stoichiometry. Average [Mg, Si] weremultiplied by the effluentflow rate (0.70±0.01mLmin−1) and divided by BET surface area (Table 1).Weighted (according tothenumber of data points collected at eachplateau) linear regression provides the reaction order (slope) and rate constant (intercept at pH=0). 95% confidence intervals shown arebasedon the weighted linear regression. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)Table 2Dissolution rate constant kH+ and reaction order nH+quantified in this study (based on [Mg] and [Si]), compared to other studies compiled by Rimstidt et al., 2012 (pH ≤ 6, log r BET surfacearea normalized Mg, Si data).Study Rate constant kH+(×10−7 moles m−2 s−1) Reaction order nH+ Rate constant kH+(×10−7 moles m−2 s−1) Reaction order nH+Based on [Mg] Based on [Si]This study (sample 2) 2.15−2.48(a) 0.46 ± 0.01(b) 2.40−2.73(a) 0.49 ± 0.01(b)Blum and Lasaga (1988) 0.52−1.78(c) 0.50 ± 0.08(d)Wogelius and Walther (1991) 0.19−5.09(c) 0.53 ± 0.16(d) 0.26−2.43(c) 0.53 ± 0.12(d)Pokrovsky and Schott (2000a) 1.28−2.90(c) 0.51 ± 0.04(d) 1.97−3.91(c) 0.53 ± 0.04(d)Rosso and Rimstidt (2000) 0.93−1.22(c) 0.50 ± 0.02(d) 0.78−1.03(c) 0.44 ± 0.02(d)Olsen (2007) 0.70−3.11(c) 0.53 ± 0.10(d)Olsen and Rimstidt (2008) 0.46−1.39(c) 0.44 ± 0.09(d) 0.86−1.39(c) 0.48 ± 0.04(d)Luce et al. (1972) 8.29−42.92(c) 0.32 ± 0.10(d) 8.94−102.05(c) 0.64 ± 0.45(d)Grandstaff (1986) 0.13−60.97(c) 1.09 ± 0.35(d) 0.12−64.36(c) 1.10 ± 0.35(d)Golubev et al. (2005) 0.12−0.34(c) 0.16 ± 0.06(d) 0.16−0.41(c) 0.19 ± 0.05(d)a Range associatedwith 95% confidence interval (2σ) ofweighted linear regression intercept.Weighted linear regression is based onnumber of data points associatedwith each [Mg, Si]steady state plateau (npH=4.0=241;npH=3.5=451;npH=3.0=644;npH=2.3=491).b Error = 95% confidence interval (2σ) associated with weighted linear regression slope.c Range associated with 95% confidence interval (2σ) of linear regression intercept.d Error = 95% confidence interval (2σ) associated with linear regression slope.112 B. De Baere et al. / Chemical Geology 413 (2015) 107–118113B. De Baere et al. / Chemical Geology 413 (2015) 107–118less (Fig. 4B), suggesting that under acidic conditions and when pH isdecreasing Si release rates reach or approach steady state faster thanMg release rates. Nonetheless, these results confirm the suitability of FT-TRA and on-line ICP–MS to generatemeaningful dissolution rate data rel-atively quickly (approximately 4 h (240min) for 4 pH steps and includingthe initial DIW step), which would allow, at least for minerals reachingsteady state dissolution rapidly, replicate analyses, dissolution processstudies, and the generation of a database suitable for statistical analysis.4.1.3. Forsterite dissolution in DIW (pH 5.6)Because steady state concentrations could not be reached at pH=5.6after ~90 min, an additional dissolution experiment with DIW only wasconducted for 224min (sample 3, Fig. 6). Even with this extended periodof exposure, Mg and Si release rates at the end of this experiment werestill decreasing, although Mg/Si reached forsterite stoichiometry, indicat-ing congruent dissolution, after approximately 6000 s (100 min). Unlikethe gradual increase in dissolution rates occurring when pH decreases(Fig. 4A), which could be attributed to a gradual increase in surface–active area with the gradual deepening of the Si-rich surface layer, thegradual decrease in the dissolution rate observed in DIWmay be, instead,an indication of gradual surface passivation once stoichiometric dissolu-tion is achieved and the depth of the Si-rich surface layer has stabilized.Fig. 5. Logarithm of the surface normalized forsterite dissolution rate (moles m−2 s−1) based o95% confidence interval based on the uncertainties of the rate parameters (slope and intercept)from previous studies compiled in Rimstidt et al. (2012) are shown for comparison. Color-codindicate studies yielding reaction orders very different from0.5 (Luce et al., 1972; Grandstaff, 19legend, the reader is referred to the web version of this article.)This could be a result of the gradual polymerization of silica tetrahedrain the leached layer (Pokrovsky and Schott, 2000a). Once the silica-richlayer depth has reached steady-state, the rate limiting step for forsteritedissolution is the release of silica from the surface altered layer (Liuet al., 2006), accounting for the gradual decrease in Mg concentration.Notwithstanding stoichiometric dissolution, the rates ofMg and Si releaseat the end of this experiment are still significantly higher (log r=−8.5)than predicted with the dissolution rate parameters derived at lower pH(Fig. 4B) and in previous studies (Fig. 5). This observation indicates thatit takes more than 224 min to reach steady state dissolution of forsteriteat pH 5.6. It is well established that reaching steady state dissolution offorsterite at higher pH takes much longer than under more acidic condi-tions (Pokrovsky and Schott, 2000a). This may be because of slow surfacepassivation, or because forsterite dissolution is not surface-controlled atthis pH (Rimstidt, 2015). In fact, Rimstidt et al. (2012) document a changein dissolution reactionmechanismgoing from low tohigh pHat 25 °C andsplit their dataset at pH 5.6. Regardless of themechanism responsible, forforsterite dissolution, the use of FT-TRA and on-line ICP–MS measure-ments, as applied in this experiment, may be limited to lower pH condi-tions (Section 4.1.2). Indeed, if the time needed to reach steady statedissolution exceeds 12 h (720min), it may be too costly to study mineraldissolution with our set-up by direct on-line ICP–MS analysis.n theMg (A) and Si (B) release rates versus pH (sample 2). The dashed lines represent theobtained from theweighted linear regression (Table 2) and extrapolated to pH1–6. Resultsed lines are obtained by linear regressions on Mg, Si data obtained at pH ≤ 6. Gray circles86;Golubev et al., 2005; Table 2). (For interpretation of the references to color in this figurege iaverto c114 B. De Baere et al. / Chemical Geology 413 (2015) 107–1184.1.4. General applicability of FT-TRA to estimate mineral dissolutionparametersThe last conclusion in the previous section raises questions about thebroader applicability of the proposed approach. One of themain advan-tages of FT-TRA over conventional flow-through reactors for measuringmineral dissolution parameters is the shorter time required to reachsteady-state concentrations of dissolved products. In our experiment,quasi steady-state concentrations are reached in less than one hour atpH ≤ 4 (Fig. 4A), while it took 8 to 75 h (480 to 4500min) during the ex-tensive forsterite dissolution experiments conducted by Pokrovsky andSchott (2000a) under similar pH conditions, but using a conventionalmixed flow reactor. The main differences between the two experimen-tal designs are the larger surface area to volume ratio (A/V) and themuch smaller volume of the reactor in our set up (25 μL vs 250 mL).While there are no a priori reasons to expect that higher A/V would de-crease the time needed to reach steady state concentrations, the muchsmaller volume of the reactor is an important characteristic which canFig. 6. Concentrations of [Mg] (5-point running average in black), [Si] (5-point running averain DIW. The time step for Mg and Si measurements by ICP–MS is 1.8 s, hence the 5-pointstoichiometric Mg/Si ratio of forsterite (1.81 ± 0.07). (For interpretation of the referenceslargely explain this observation. The time necessary to reach steady-state concentrations in a flow reactor depends on both the times ittakes for the mineral surface to reach steady dissolution (Tdiss), andthe time it takes to renew the solution within the reactor (Tflush). Withtheir comparatively large volumes, when mixed flow reactors are usedto measure dissolution rates of forsterite or other minerals reachingsteady state dissolution relatively quickly, Tflush N N Tdiss and the timeneeded for the dissolution experiment to reach steady-state concentra-tions is largely dictated by the residence timeof the eluent in the reactor(e.g. 6–50 h (360–3000 min) in the pH b 4 experiments conducted byPokrovsky and Schott, 2000a). The eluent residence time in our flow-through cell is only 2.1 s (i.e. Tflush b b Tdiss); therefore the time neededfor dissolution experiments to reach steady-state concentrations is en-tirely dictated by the properties of the mineral surface.The time advantage of FT-TRA is clearly apparent in our study becauseforsterite reaches steady-state dissolution rapidly, at least at pH ≤ 4. Ifother minerals or conditions (e.g. forsterite dissolution in DIW) requirelonger time periods (more than 720 min) to reach steady-state dissolu-tion, on-line ICP–MS analysis may become prohibitively expensive. Inthis case, we suggest two possible alternatives: (1) pre-conditioning themineral off line prior to on-line ICP–MS effluent measurement or (2) col-lection of time-series samples over a much longer period using anautomated fraction collector, followed by off-line ICP–MS analysis. Thechoice between these two alternative approaches would depend on thegoal of the experiment, and both approaches could be combined. If thegoal is to determine dissolution rate parameters, fraction collectionwould be particularly suited, since the experiment could be continuedover much longer periods of time with minimal attendance. The advan-tage of high analytical time resolution would be lost but this is of no con-sequence for this particular application. Of course, for minerals withTdiss≫ Tflush, mixedflow reactorsmay be equally suited tomeasure disso-lution rate parameters, but the automation of our set-up would still facil-itate this task. On the other hand, if the goal of the experiment is to studyrapidly evolving transient dissolution events, the high time resolutionaffordedby thepresent approach is needed, andneither FT-TRAwith frac-tion collector nor conventional mixed flow reactor could be used effec-tively. In this case, FT-TRA and on-line ICP–MS would be the tool ofchoice to document transient dissolution of minerals or minerals havingbeen subjected to various pre-treatments. For instance, off-line precondi-tioning of minerals under varying conditions prior to on-line ICP–MSmeasurements could prove particularly useful to study the factors con-trolling surface passivation or exfoliation, two important processesn gray) andMg/Simolar ratio (red) in the eluent resulting from the dissolution of sample 3age is shown to represent the eluent reactor renewal time. The dashed lines indicate theolor in this figure legend, the reader is referred to the web version of this article.)which regulate weathering and carbonation of minerals (e.g. Olssonet al., 2012).4.2. Replicate analyses and dissolution under transient conditions4.2.1. Reproducibility of forsterite dissolution under identical conditionsThe shorter experimental durations afforded by our small volumeflow-through cell facilitate replicate experiments to assess the inherentvariability of forsterite dissolution between closely related subsamples.Results obtained with one of the five replicate subsamples (sample6) subjected to the same dissolution sequence are illustrated in Fig. 7A(results from the other replicates are reported in the supplementarymaterial). Mg and Si concentrations follow a similar pattern as in theprevious experiment. They start high and sharply decrease in DIW, in-crease as incoming effluent pH decreases and drop when pH increases.pH changes associated with forsterite dissolution calculated from theconcentration ofMg2+ in the effluent are b0.004 pH units and thereforenegligible. The pH values reported in our experiments (Fig. 7B) are thusthe pH of the incoming solutions.Multiplying the time-resolved concentrations obtained with the fivereplicates by the effluent flow rate, which was identical for the five ex-periments, and dividing by the surface area of each subsample (Table 1)reveal a near 2-fold variability in the surface normalized rate of dissolu-tion of the replicates (Fig. 8). In addition, not only are the surface-normalized dissolution rates generated during the 5 experimentsave115B. De Baere et al. / Chemical Geology 413 (2015) 107–118Fig. 7. (A) Concentrations of [Mg] (5-point running average in black), [Si] (5-point runningdifferent, but the rate at which steady-state dissolution is approachedalso varies between subsamples. Differences in surface-normalized dis-solution rates between subsamples may reflect variations in reactivesurface area, while the gradual increase in dissolution rate at constantpH of 2.3 and/or pH of 3.3may reflect a gradual increase in reactive sur-face area with time in 4 of the 5 subsamples. The variability observed inthis experiment is surprising considering that the subsamples weretreated and dissolved under the same conditions, and further points tothe importance of replicating dissolution experiments (Rosso andRimstidt, 2000) and the continuing need to fully understand the under-lying reasons for this variability.4.2.2. Forsterite dissolution stoichiometry under transient eluent conditionsFT-TRA analysis reveals that the stoichiometry of forsterite disso-lution displays a striking variability associated with eluent pHchanges (Figs. 4A; 7A). Mg/Si molar ratio of the eluent is initiallymuch higher and gradually decreases towards the stoichiometricratio of the forsterite sample (1.81 ± 0.07). When the pH of the elu-ent gradually decreases, Mg/Si often increases sharply and relaxesback towards the forsterite stoichiometric ratio. In contrast, whenthe pH of the eluent increases (at t = 7500 s (125 min); Fig. 7A;supplementary material), invariably, Mg/Si drops below thestoichiometric ratio and gradually rises thereafter. In addition, thetime resolved concentrations generated at pH 3.3 with sample 6(Fig. 7A) document a large and sudden change in Si concentrations,which is clearly reflected in the Mg/Si time series data. Likewise,smaller but significant and rapid changes in Mg concentration areobserved during the first dissolution step in DIW. These peaks indi-cate that mineral dissolution is not necessarily a continuous process,but may be punctuated by abrupt events, which require the temporalresolution afforded by our approach to be documented.solution of sample 6. The dashed lines indicate the stoichiometric Mg /Si ratio of forsterite ((B) Changes in incoming eluent pH (≈pH in flow-through reactor, as changes in pH resultingof the references to color in this figure legend, the reader is referred to the web version of thisrage in gray) and Mg/Si molar ratio (red) measured in the effluent resulting from the dis-4.2.2.1. Monitoring the surface leached layer thickness during transient el-uent conditions. The preferential release of Mg during the early stage offorsterite dissolution at low pH has been widely reported (e.g. Luceet al., 1972; Wogelius and Walther, 1991; Pokrovsky and Schott,2000a; Rosso and Rimstidt, 2000), and attributed to the formation of aSi-rich leached layer due to exchange reaction between Mg2+ and H+(e.g. Pokrovsky and Schott, 2000a). Higher Mg/Si ratios of the dissolvedproducts, compared to the Mg/Si ratio of the dissolving forsterite, indi-cate preferential release of Mg and deepening of the Si-rich surfacelayer. Quantum mechanical simulations by Liu et al. (2006) suggestthat under acidic conditions, oxygen atoms at a specific lattice position(μ3-O) become protonated, which lengthens and weakens the bondsholding Mg. The rate of release of Mg by this reaction is faster at kinksor edges. Thismechanism could account for the observed highMg/Si re-leased when forsterite is first exposed to more acidic solutions. On theother hand, eluent ratios lower than forsterite stoichiometry indicatepreferential dissolution of Si and partial erosion of the Si-rich layer.Changes in themean thickness of the Si-rich leached surface layer asdissolution proceeds are calculated following Chou andWollast (1984):ΣMg tð Þ ¼ Σ Mg½ i  Q  Δt ð5aÞΣSi tð Þ ¼ Σ Si½ i  Q  Δt ð5bÞwhere ΣMg(t) and ΣSi(t) are the moles of Mg and Si dissolved sincethe beginning of the experiment to time t, [Mg]i and [Si]i are the concen-trations (moles L−1) measured at time i, Δt is the time step of ICP–MSanalysis (1.8 s) and Q is the effluent flow rate (L s−1)VMg tð Þ ¼ 1:81 ΣMg tð Þ MVforsterite ð6aÞ1.81 ± 0.07). Figures for samples 4, 5, 7 and 8 are supplied in supplementary material.from forsterite dissolution in the flow cell are below detection limits). (For interpretationarticle.)116 B. De Baere et al. / Chemical Geology 413 (2015) 107–118VSi tð Þ ¼ ΣSi tð Þ MVforsterite ð6bÞwhere MVforsterite is the molar volume of forsterite (43.79 cm3 mol−1;Cemič, 2005), VMg (t) and VSi (t) are the volumes of forsterite dissolvedas a result of Mg and Si release, respectively (taking into accountforsterite stoichiometry)ZMg tð Þ ¼ VMg tð Þ=A ð7aÞZSi tð Þ ¼ VSi tð Þ=A ð7bÞwhere A is the surface area of the sample, ZMg(t) and ZSi(t) are the thick-ness of the layer of forsterite dissolved by releasing Mg and Sirespectively.If the Mg/Si ratio of the eluent is higher than the stoichiometry offorsterite, ZMg(t)NZSi(t), and ZMg(t)−ZSi(t) is the thickness of the Mg-leached surface layer at time t (Fig. 9, assuming that the leached layerhas lost 100% of its Mg and the molar volume of the silica layer hasretained themolar volume of forsterite). If we assume that there is a lin-earMg/Si gradient in the leached layer, from zero at the top to forsteritestoichiometry at the bottom, estimated leached layer thicknesseswouldhave to be doubled (Chou and Wollast, 1984). Although the calculatedthickness is only an average over the entire surface area of the mineraland the assumption that the silica leached layer retains the molar vol-ume of forsterite may not be correct (e.g. Kim et al., 2005), this simplecalculation provides a useful visualization of the formation process ofthe leached layer (Fig. 9) and should estimate the true average thicknesswithin a factor of ~2.Fig. 8. Forsterite dissolution rates under varying pH estimated from time-resolved Mg(upper panel A, calculated using the 5-point running [Mg] average, divided by 1.81 totake into account forsterite stoichiometry) and Si (lower panel B, calculated using the5-point running [Si] average) concentration measured by on-line ICP–MS, multiplied bythe eluent flow rate (0.70 ± 0.01 mLmin−1) and divided by the BET surface area for sam-ple 4–8 (Table 2). Time-resolved eluent pH provided in Fig. 7B.The evolution of the leached layer thickness depends both on Mg/Siand the rate of dissolution. The sample reported on Fig. 9 never reachedstoichiometric dissolution (Mg/Si = 1.81) during the first 7000 s(117 min) of the experiment, therefore the thickness of the leachedlayer continuously increased over that time period. If we assume thatit lost all its Mg and remained isovolumetric, the Si-rich layer reachedan apparentmean thickness of 2 ångströmswithin thefirst fewminutesof dissolution inDIWand then deepenedmuchmore gradually to 3 ång-ströms during the following 30 min (Fig. 9; similar figures for the fourother replicates are provided in the supplementary material). Therapid initial increase in thickness was due to the initially high Mg/Siand dissolution rate, and the more gradual deepening that followed re-flects near congruent dissolution and slower dissolution rates (Fig. 7A).At pH 3.3, the leached layer deepened faster because of higher dissolu-tion rates and higher (but gradually decreasing) Mg/Si. At pH 2.3, Mg/Siwas closer to congruency but the much higher dissolution rates (Fig. 8)still resulted in a rapid increase in thickness, reaching amaximum of 10ångströms at the end of the pH 2.3 plateau. When reverting to DIW atthe end of the dissolution sequence, the thickness of the leached layerFig. 9. Changes in the thickness of theMg leached surface layer (solid red line) in sample 6(thicknesses for samples 4, 5, 7, 8 are reported in suppl. Material). The dashed red linesrepresent range in Mg–Si leached layer thickness calculated using the 95% confidence in-terval of the forsterite stoichiometry (Mg/Si= 1.81± 0.07). Mg/Si molar ratio (calculatedusing the 5-point running [Mg, Si] average) is shown in black. Time resolved eluent pH isreported in Fig. 7B. (For interpretation of the references to color in this figure legend, thereader is referred to the web version of this article.)decreased a little and stabilized, indicating a very slight erosion of Si-rich layer, corresponding to eluent Mg/Si below forsterite stoichiome-try. This erosion was very small because the dissolution stoichiometryremained below that of forsterite for a short period only, at a timewhen the rate of dissolution was slow.4.2.2.2. Sporadic exfoliation of the Si-rich layer. Brief but pronounced epi-sodes of rapid Si release are observed during the dissolution of forsterite(Fig. 8B). The most prominent of these events was observed during thedissolution of sample 6, resulting in a sharp decrease in Mg/Si (Fig. 9:t = 3420 s (57 min)). These features are tentatively interpreted as spo-radic exfoliations of a section of the Si-rich layer from which all the Mghad been previously stripped. The high temporal resolution afforded bythe short eluent residence time in the reactor (2.1 s) and time-resolvedICP–MS analysis (1.8 s) provides interesting details on the mostprominent exfoliation episode illustrated in Fig. 9, which lasted ~20 s,and is thus well documented by about 12 consecutive ICP–MS datapoints (Fig. 10). In particular, while Mg was not released above back-ground during the peak of the exfoliation, a small Mg peak followed(Fig. 10B), possibly reflecting exposure of the new unaltered forsteritesurface, which released Mg at a faster rate for a brief period.FT-TRA data also provide a means of estimating the extent of exfoli-ation, within the constraints of a few simplifying assumptions. Fig. 10indicates that the section exfoliated during this episode consistedcilitating investigations of the influence of multiple variables; (2) high-analysis over a wide range of concentrations facilitates the measure-steps, kinks and screw dislocations, which act as active surface sites117B. De Baere et al. / Chemical Geology 413 (2015) 107–118exclusively of silica. Integrating the amount of silicon released abovebackground during this event 2.8 × 10−10 moles and assuming thatthe leached layer kept the molar volume of forsterite, we can calculatethe volume of silica exfoliated 1.24 × 10−8 cm3. Since we know the av-erage thickness of the leached layer at the time of the exfoliation4.5 × 10−8 cm, Fig. 9), the surface area of exfoliation can be calculatedFig. 10. A: Exfoliation event observed in sample 6 as an abrupt increase in [Si]. B: Sameevent on an expanded time scale showing the temporal sequence of changes in [Si] (y-axis on right) preceding a smaller [Mg] peak (y-axis on left).(0.275 cm2), which represents 8% of the total surface area of the sample.Exfoliation is triggered when the Si-enriched layer reaches a criticalthickness (e.g. Jarvis et al., 2009) and has been attributed to molar vol-ume differences between the forsterite crystal and the Si-enrichedlayer (e.g. Kim et al., 2005). Interestingly, the eluent generated bysample 6 also had the highest Mg/Si molar ratio over the entire run, in-dicating the formation of a more extensive silica rich layer, which alsoresulted in a more pronounced decrease in Mg/Si when raising theeluent pH back to 5.6. In contrast, sample 7 had the lowestMg/Si and re-leased relatively little Si in the last transition to DIW (see supplementa-ry information). This seems to indicate that the development of thesurface Si-enriched layer differed among samples 4–8, even thoughthey were treated under identical conditions. FT-TRA could thus alsoprove very useful to study the factors controlling exfoliation, which isa major process exposing fresh mineral surfaces necessary to optimizemineral carbonation and carbon sequestration (e.g. Béarat et al., 2006).5. Summary and future prospectsThe results from this exploratory study validate FT-TRA and on-lineICP–MS as a meaningful and versatile new experimental method tostudy mineral dissolution. We have identified a number of advantages,and several applications which could benefit from using this approach.The advantages are (1) faster attainment of steady state eluent concen-tration,which stems from the small reactor volume and extremely shortresidence time of the eluent in the reactor; (2) high temporal resolutionresulting from the small volume of the reactor and on-line time-resolved ICP–MS analysis; and (3) simultaneous analysis of multiple el-ements occurring over a very wide range of concentrations (ppm toppb). Several aspects relevant to mineral dissolution studies can benefit(e.g. Ruiz-Agudo and Putnis, 2012). This insight lead to rationalizingthe large range of dissolution rate constants, which have been carefullymeasured from bulk solution measurements, as reflecting stochasticchanges in the surface density of these active sites. For more accuratedescriptions, dissolution ratesmust therefore be adjusted to thenumberand reactivity of active surface sites. The solution proposed by Lüttgeet al. (2013) is to replace dissolution rate constants by spectra of rateconstants which would capture the variability in the energy level anddensity of active surface sites. If the density and types of active surfacesites were amenable to predictive modeling and anchored to a bulkmineral property that can be measured to determine ab-initio condi-tions, this information could then be applied to any conditions in thelaboratory or in the field. Progress will require combining differentmodeling andmeasurement techniques, inwhich FT-TRA could contrib-ute significantly. As already demonstrated by Duckworth and Martin(2003), AFM can be combinedwith chemical analysis to simultaneouslydocument changes in surface topography and bulk solution composi-tion during mineral dissolution. The FT-TRA module presented herecould be a perfect complement to surface imaging. The flow cell usedin this study could be replaced by the flow-through cell used withAFM (Duckworth and Martin, 2003). The multiple data sets producedby this approach could help assess whether the evolution of reactivesurface sites during mineral dissolution can be predicted and detectedwith the high temporal resolution and sensitivity afforded by FT-TRA/ICP–MS to yield intrinsic dissolution rate constants normalized to activesite distribution, possibly resolving the present surface normalizationconundrum.AcknowledgmentsWe acknowledge the very constructive input of two anonymous re-viewers. Method development was made possible using a NSERC Re-search Tools and Instrumentation grant. The authors would like toacknowledge ongoing collaboration with the Pacific Centre for Isotopicand Geochemical Research (PCIGR) at the University of British Colum-bia, which allows for continuous method development.Appendix A. 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Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivs 2.5 Canada
Faculty
Mineral dissolution
Dissolution rate
Forsterite
Flow-through dissolution
Stoichiometry
Exfoliation
Leached layer
Measuring mineral dissolution kinetics using on-line flow-through time resolved analysis (FT-TRA) : an exploratory study with forsterite
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