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Antibacterial capability characterization of polymer-nanoparticle composites using high-throughput microfluidic… Kheiri, Sina 2017

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Antibacterial Capability Characterization of Polymer-Nanoparticle Composites Using High-Throughput Microfluidic Platform   by  Sina Kheiri  B.A.Sc., In Mechanical Engineering, Sharif University of Technology, Iran, 2015  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF APPLIED SCIENCE  in THE COLLEGE OF GRADUATE STUDIES  (Mechanical Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan)  December 2017  © Sina Kheiri, 2017   ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled:  Antibacterial Capability Characterization of Polymer-Nanoparticle Composites Using High-Throughput Microfluidic Platform  submitted by     Sina Kheiri               in partial fulfillment of the requirements of   the degree of    Master of Applied Science .    Dr. Keekyoung Kim / Mechanical Engineering Supervisor Dr. Deborah Roberts / Civil Engineering Supervisory Committee Member Dr. Lukas Bichler / Mechanical Engineering Supervisory Committee Member Dr. Chen Feng / Electrical Engineering University Examiner       iii Abstract  Nanoparticles have been significantly employed in the number, variety, and function to create advanced materials with antibacterial capability. Despite considerable recent progress in the development of advanced material technology, the quest to fabricate optimized antibacterial materials remains a high research priority in biomedical and food packaging industries. This thesis presents a study to characterize and optimized antibacterial capability of liquid silicone rubber (LSR) and nanoparticle (NP) composites. Over the past decades, inorganic NPs, particularly metal oxide NPs, have attracted a great attention because of their capability of strong inhibitory and bactericidal effects. Three representative NPs (e.g., ZnO, TiO2, and Ag) with different concentrations capable of achieving antibacterial status were tested. To optimize various parameters such as types of materials, concentrations, and processing condition, a high-throughput platform using microsystems technology are desirable, which enables researchers to minimize the usage of materials and conduct multiple experiments at a time. The antibacterial efficiency of the fabricated LSR/NP nanocomposites were evaluated through the high-throughput microfluidic platforms and viable counts technique. LSR/TiO2 nanocomposites demonstrated the best antibacterial nanocomposite. Also, the viability of E. coli, which were exposed to LSR/NPs on the microfluidic platform, was assessed and studied using the live/dead assay method. It was also found from the both methods that the antibacterial capability of the nanocomposites was decreased after 15 wt%.     iv Table of Contents  Abstract ......................................................................................................................................... iii	Table of Contents ......................................................................................................................... iv	List of Tables .............................................................................................................................. viii	List of Figures ............................................................................................................................... ix	List of Symbols ........................................................................................................................... xvi	List of Abbreviations ............................................................................................................... xviii	Acknowledgements ......................................................................................................................xx	Dedication ................................................................................................................................... xxi	Chapter 1: Introduction ................................................................................................................1	1.1	 Bacteria and Material Interactions .................................................................................. 7	1.1.1	 Nanotopography and Surface Nanostructuring ....................................................... 7	1.1.2	 Cell and Surface Dynamics ..................................................................................... 8	1.2	 Fabrication Methods ..................................................................................................... 11	1.2.1	 Natural Antibacterial Surfaces .............................................................................. 11	1.2.2	 Artificial Antibacterial Surfaces ........................................................................... 12	1.2.2.1	 Surface Coating ................................................................................................. 13	1.2.2.2	 Layer-by-layer Assembly .................................................................................. 15	1.2.2.3	 Synthesis and Polymerization of Nanocomposites ........................................... 17	1.3	 Mechanisms of Antibacterial Surfaces ......................................................................... 18	1.4	 Biocompatibility of Nanoparticles ................................................................................ 19	1.5	 Research Objectives ...................................................................................................... 22	  v 1.6	 Thesis Outline ............................................................................................................... 23	Chapter 2: Fabrication and Characterizations of Nanocomposites ........................................24	2.1	 Overview on Nanocomposites ...................................................................................... 24	2.2	 Nanoparticle Characterization ...................................................................................... 26	2.2.1	 Methodology ......................................................................................................... 26	2.2.2	 Results and Discussion ......................................................................................... 27	2.3	 Nanocomposite Fabrication .......................................................................................... 28	2.3.1	 Surface Coating ..................................................................................................... 29	2.3.1.1	 Methodology ..................................................................................................... 30	2.3.1.2	 Results ............................................................................................................... 31	2.3.2	 Nanocomposite Polymerization ............................................................................ 32	2.3.2.1	 Methodology ..................................................................................................... 33	2.4	 Nanocomposite Characterization .................................................................................. 36	2.4.1	 Characterization of Mechanical Property ............................................................. 36	2.4.1.1	 Experimental Methods ...................................................................................... 37	2.4.1.1.1	 Statistical Analysis ...................................................................................... 41	2.4.2	 Characterization of Hydrophobic Properties ........................................................ 43	2.4.2.1	 Experimental Methods ...................................................................................... 45	2.4.3	 Characterization of Surface Morphology .............................................................. 48	2.5	 Chapter Summary ......................................................................................................... 51	Chapter 3: Design, Fabrication, and Simulation of High-Throughput Microfluidic Device 52	3.1	 Overview ....................................................................................................................... 52	3.2	 Design of Microfluidic Platform ................................................................................... 53	  vi 3.3	 Computational Simulation ............................................................................................ 56	3.3.1	 2D Simulation ....................................................................................................... 58	3.3.1.1	 Methodology ..................................................................................................... 59	3.3.1.2	 Results ............................................................................................................... 60	3.3.2	 3D Simulation ....................................................................................................... 61	3.3.2.1	 Modeling of Device Geometry ......................................................................... 61	3.3.2.2	 Boundary and Initial Conditions ....................................................................... 63	3.3.2.3	 Results and Discussion ..................................................................................... 65	3.4	 Microfluidic Device Fabrication ................................................................................... 71	3.4.1	 Mold Design.......................................................................................................... 72	3.4.2	 Casting and Assembling Device ........................................................................... 73	3.5	 Chapter Summary ......................................................................................................... 76	Chapter 4: Antibacterial Efficiency of NPs and Fabricated Nanocomposites .......................78	4.1	 Overview on Bacteria Growth and Antibacterial Efficiency ........................................ 78	4.2	 Disk Diffusion Method ................................................................................................. 79	4.2.1	 Materials and Methods .......................................................................................... 80	4.2.1.1	 Chemicals and Materials ................................................................................... 80	4.2.1.2	 Culturing Bacteria ............................................................................................. 80	4.2.1.3	 Mixing and Preparing Paper Disks ................................................................... 81	4.2.1.4	 Measurement of NP Size Distributions ............................................................. 82	4.2.2	 Experimental Results ............................................................................................ 83	4.2.2.1	 Characterization of Nanoparticles ..................................................................... 83	4.2.2.2	 Antibacterial Assay ........................................................................................... 83	  vii 4.2.2.3	 Discussion ......................................................................................................... 86	4.3	 Viable Counts Method .................................................................................................. 87	4.3.1	 Materials and Methods .......................................................................................... 87	4.3.1.1	 Microfluidic Platform Preparation .................................................................... 87	4.3.1.2	 Culturing Bacteria on Microfluidic Platform .................................................... 88	4.3.1.3	 Characterization of Bacteria Cell Viability ....................................................... 89	4.3.2	 Results and Discussion ......................................................................................... 90	4.4	 Live/Dead Assay Method ............................................................................................. 92	4.4.1	 Materials and Methods .......................................................................................... 92	4.4.2	 Results and Discussion ......................................................................................... 93	4.5	 Chapter Summary ......................................................................................................... 95	Chapter 5: Conclusion and Future Work ..................................................................................97	5.1	 Conclusion .................................................................................................................... 97	5.2	 Future Work ................................................................................................................ 100	Bibliography ...............................................................................................................................102	Appendices ..................................................................................................................................120	Appendix A ............................................................................................................................. 120	Appendix B ............................................................................................................................. 123	Appendix C ............................................................................................................................. 125	Appendix D ............................................................................................................................. 127	Appendix E ............................................................................................................................. 128	Appendix F.............................................................................................................................. 130	   viii List of Tables Table 1.1 Selected patterned-surfaces fabricated recently. ............................................................. 8	Table 2.1 Contact angle of different fabricated LSR/NPs. ........................................................... 46	Table 3.1 Summarized advantages of microfluidic devices over conventional systems. ............. 53	Table 3.2 Summary of mesh grid statistics in two configurations. ............................................... 63	Table 4.1 Mean zone of inhibition in diameter, (n=4) .................................................................. 85	Table 5.1  Summary of all experimental results. ........................................................................ 100	   ix List of Figures Figure 1.1 Schematic of biofilm formation stages on a substrate (Adapted from [12]). .............. 2	Figure 1.2 Schematic representation of transformation surface are to volume ratio. ................... 4	Figure 1.3 Perspective and top SEM images of the fabricated surface with the different architecture: (A,B) Cross pillars(C,D) Hexagonal pits, (E,F) Cross pillars, (I,J) Sharklet pattern (Adapted from [42]). ................................................................ 6	Figure 1.4 Illustration of Cell-Surface dynamics in Cicada wing: (A) The procedure of application of AFM tip. (B) the tip was lowered and the sharp drop indicating the time at which the cell membrane ruptured (Adapted from [21]) ....................... 10	Figure 1.5 Images of different super-hydrophobic plant and insect species and SEM images of topographic structures: (A) Lotus leaves, (B) Indian canna leave, (C) Rear face of purple Setcreasea leave, (D) Rear face of ramee leave, (E) Isoptera Nasutitermes, (F) Hemianax papuensis, (G) Psaltoda claripennis, and (H) Lepidoptera Papilio xuthus. (Adapted from [19]) ............................................. 12	Figure 1.6 Scheme of the surface coating antibacterial mechanism. (Adapted from [62]) ........ 14	Figure 1.7 Illustration of LBL fabrication method and three main approaches. (Adapted from [70]) ................................................................................................................. 16	Figure 1.8 Different mechanisms of antibacterial activity of metal nanoparticles. (A) Protein degradation due oxidation causing loss of catalytic activity. (B) DNA damage because of extra hydrogen peroxide (H2O2) or superoxide (O2•−). (C) Cell membrane disruption by the metal ions, allowing them entering into the intracellular region. (D) Damage and stop enzymes, (E) Disturbance with   x nutrient acceptance and membrane function. (F) Damage to storage granules because of reactive oxygen species (ROS). ............................................................. 19	Figure 2.1 Schematic of various approaches to encapsulate NPs into polymer structure. ......... 24	Figure 2.2 Schematic of aggregations and agglomerations formations. ..................................... 25	Figure 2.3 Particles sizing results for mechanical vortex, ultrasonicator bath, and ultrasonicator probe. ................................................................................................. 27	Figure 2.4 LSR fabrication procedure. ....................................................................................... 29	Figure 2.5 Fundamental steps of dip coating technique: A) Immersion, B) Deposition, C) Drainage, and D) Evaporation. ................................................................................ 30	Figure 2.6 LSR/NP cube images. (A) simple LSR, (B) LSR/TiO2, (C) LSR/Ag, and (D) LSR/ZnO. ................................................................................................................. 31	Figure 2.7 Illustration of LSR two components reaction: (A) Polymer chain end (B) Curing agent (C) LSR cured structure ..................................................................... 32	Figure 2.8 Schematic of polymerization procedure. (A) Aggregation of NPs inside polymer structure, and (B) Separation of NPs inside the polymer structure due to applied energy. ..................................................................................................... 33	Figure 2.9 Schematic of nanocomposite polymerization fabrication setup. ............................... 35	Figure 2.10  LSR/NPs with different conditions; (A-D) LSR/Ag NPs; (E-H) LSR/TiO2 NPs and; (I-L) LSR/ZnO NPs. The concentrations of nanocomposite are increasing 5-20 wt. % from left to right (Scale bar= 5mm). .................................... 35	Figure 2.11 Schematic diagram of the mechanical test system and its main components ......... 38	Figure 2.12 Schematic of sample size and velocity of the actuator ............................................ 39	  xi Figure 2.13 Mechanical properties graph. (A) Silver stress-strain curve (B) Zinc oxide stress-strain curve (C) Titanium dioxide stress-strain curve (D) Young’s modulus changes based on NP wt%. Red line shows the pure LSR Young’s modulus range (n=3, p>0.05, *p<0.05, **p<0.01). ............................................... 42	Figure 2.14 Bacteria adhesion forces based on the distance ....................................................... 43	 Figure 2.15 Fundamentals of contact angle and surface tension. .............................................. 45	Figure 2.16 (A) Schematic diagram of contact angle measurement setup. (B) Pure LSR contact angle image. ................................................................................................. 46	Figure 2.17 Measured contact angle for pure LSR and coated LSR with different NPs (n=3, p>0.05, *p<0.01). .......................................................................................... 47	Figure 2.18 Graph of contact angles changes with respect to NPs wt% (n=3). ......................... 48	Figure 2.19 SEM images and uncoated area measurements using Image J for LSR coated with different NPs: (A) Ag NPs and (B) area measurement uncoated with Ag NPs, (C) TiO2 NPs and (D) area measurement uncoated with of TiO2 NPs, and (E) ZnO NPs and (F) area measurement uncoated with ZnO NPs. ................... 49	Figure 2.20 LSR areas uncoated with different NPs (n=5, *p<0.05, **p<0.01). ...................... 50	Figure 2.21 Two models for describing contact in rough surfaces. (A) Cassie-Baxter model and; (B) Wenzel Model ................................................................................. 51	Figure 3.1  (A) Microfluidic design (in mm) and, (B) electrical circuit model of the microfluidic systems. ............................................................................................... 55	Figure 3.2  Proposed microfluidic designs. (A) Normal tree-like network and (B) enhanced tree-like network using C-shape microstructure array. ............................ 56	  xii Figure 3.3 Computational simulation results to compare with and without C-shape microstructure: (A) Simulation mesh grid; (B) C-shape configuration; (C) Chamber without the microstructure; (D) Chamber with microstructure. ............... 57	Figure 3.4 Boundary conditions and mesh grid for 2D simulations: (A) Inlet, (B) Outlet, (C) Outer wall, (D)Inner wall, and (E) Mesh grid. .................................................. 59	Figure 3.5 COMSOL Multiphysics simulation results: (A) Schematic of C-shape distance parameter, (B) d=2mm, (C) d=1.7mm, (D) d=1.5mm, (E) d=1.3mm, and (F) d=1mm ..................................................................................................................... 60	Figure 3.6 3D model of the platforms in COMSOL Multiphysics. ............................................ 61	Figure 3.7 Mesh grids in (A) with C-shape and, (B) without C-shape. ...................................... 62	Figure 3.8 COMSOL Multiphysics particle tracing without C-shape microstructure through time sequence. ............................................................................................ 65	Figure 3.9 COMSOL Multiphysics particle tracing with C-shape microstructure through time sequence. .......................................................................................................... 66	Figure 3.10 Diagram of defined intersection planes for particle trajectories. ............................ 67	Figure 3.11 Portrait map of the particles in “without C-shape microstructure”. ........................ 68	Figure 3.12 Portrait map of the particles in “with C-shape microstructure”. ............................. 69	Figure 3.13 Effects of aggregation of particles on covered area. ............................................... 70	Figure 3.14 Post processed result of the particle distribution. (n=5, **p<0.01) ........................ 70	Figure 3.15 Illustration of the molds: (A-B) Microfluidic rendered SolidWorks® part (C-D) Molds dimensions (E-F) 3D printed molds using the poly jet 3D printer. ......... 72	Figure 3.16 Schematic procedure of the softlithography technique for fabricating microfluidic chips (A-D). ......................................................................................... 74	  xiii Figure 3.17 Schematic of (A) Assembling procedure of the microfluidic device, (B) Fully assembled microfluidic chip .................................................................................... 75	Figure 3.18 Images of a fully assembled microfluidic platform. ................................................ 76	Figure 4.1 Typical microbial growth curve for bacteria population. (Four main phases are marked) .................................................................................................................... 78	Figure 4.2 The distinctive appearance of different nanoparticles in four concentrations: (A) Ag 100 mg/mL, (B) Ag 50 mg/mL, (C) Ag 10 mg/mL, (D) Ag 0.2 mg/mL, (E) TiO2 100 mg/mL, (F) TiO2 50 mg/mL, (G) TiO2 10 mg/mL, (H) TiO2 0.2 mg/mL, (I) ZnO 100 mg/mL, (J) ZnO 50 mg/mL, (K) ZnO 10 mg/mL, and (L) ZnO 0.2 mg/mL. ............................................................................ 81	Figure 4.3 Particle size distributions of (A) Ag, (B) TiO2 and (C) ZnO nanoparticles determined using a Mastersizer. ............................................................................... 83	Figure 4.4 Disk diffusion tests for different nanoparticles against the E. coli. The zone of inhibition (ZoI) is shown with a dashed circle representing a noticeable antibacterial influence. (1) TiO2 10 mg/mL; (2) TiO2 50 mg/mL; (3) ZnO 50 mg/mL; (4) ZnO 0.2 mg/mL; (5) ZnO 10 mg/mL; (6 and 8) Control; (7) TiO2 0.2 mg/mL; (9) TiO2 100 mg/mL; (10) Ag 100 mg/mL; (11) Ag 50 mg/mL; (12) Ag 10 mg/mL; (13) Ag 0.2 mg/mL; and (14) ZnO 100 mg/mL. ..................... 84	Figure 4.5 Bar graph of antibacterial activity of nanoparticles against E. coli in four concentrations (n=4, p>0.05, *p<0.05, **p<0.01). ................................................ 85	Figure 4.6 The microfluidic chips with and without the LSR/NP nanocomposites and the fully assembled microfluidic platform. .................................................................... 88	  xiv Figure 4.7 E. coli growth after 2, 4 and 8 hours on the surface of (A) LSR/Ag NPs; (B) LSR/TiO2 NPs; and (C) LSR/ZnO NPs. (n=3, p>0.05, *p < 0.05, **<0.01) ......... 91	Figure 4.8 Fluorescence images of live/dead assayed E. coli cultured on LSR without NPs as the control experiment. (A) 0 hour and (B) 8 hours culture of bacteria. Scale bar = 20 µm. ................................................................................................... 94	Figure 4.9 Fluorescence images of live/dead assayed E. coli after 8 hours culture on various LSR/NP nanocomposites. Scale bar = 20 µm. ............................................ 94	Figure 4.10 Antibacterial efficiency of LSR/NP nanocomposites after 8 hours ........................ 95	Figure 5.1 Schematic of the proposed microfluidic chip. ......................................................... 101	Figure S.1 SEM images and size measurements of three different NPs. (A) and (B) Ag NPs, (C) and (D) TiO2 NPs, and (E) and (F) ZnO NPs. ........................................ 121	Figure S.2 Processed images of NPs on the glass slides: (A)Ag NPs, (B) TiO2 NPs, and (C) ZnO NPs. ......................................................................................................... 122	Figure S.3 Measuring contact angle by using DropSnake Plugin: (A) Automatic obtained spline and, (B) Refined spline. ............................................................................... 124	Figure S.4 Screenshot of COMSOL Multiphysics 2D simulations. ......................................... 125	Figure S.5 Screenshot of COMSOL Multiphysics 3D simulations.  ........................................ 126	Figure S.6 An example of the obtained results by ImageJ. ...................................................... 127	 Figure S.7 Automatic colony counting using ImageJ; (A-E) The sequence of images processing from raw image to the counted is presented. ....................................... 129	Figure S.8 An example to show the accuracy of the automatic colony counting procedure. ... 129	Figure S.9 Required steps to post-process the captured fluorescence images; (A) Importing the images separately for each channel; (B) Converting the image   xv format to 8-bit or 16-bit; (C) adjusting the threshold to count the cells; (D) collecting and exporting the obtained cell counting results. .................................. 131	  xvi List of Symbols 𝐿 Channel Length 𝐼 Current De Dean Number ℎ Final Solution Film Thickness 𝑄 Flow Rate 𝜇 Fluid Dynamic Viscosity υ Fluid Kinematic Viscosity 𝑣 Fluid Velocity 𝜂 Fluid Viscosity F Force 𝐹, Force Exerted on The Particle 𝑅 Hydraulic Resistance Ao Initial Area Cross-Section Lo Initial Length A Instantaneous Cross-Section 𝐿. Instantaneous Length 𝜌 Liquid Density 𝜀 Mechanical Strain 𝜎 Mechanical Stress ρ3	 Particle Density   xvii d3 Particle Diameter 𝑚7 Particle Mass τ3 Particle Velocity Response Time 𝑅9 Radius of The Channel Curvature h Rectangular Channel Height 𝑤 Rectangular Channel Width 𝑅 Resistance 𝑅𝑒 Reynolds Number 𝜂 Solution Viscosity 𝛾 Surface Tension 𝛿 Total Elongation 𝑉 Voltage ∆𝑃 Volumetric Pressure Drops 𝑈 Withdrawal Speed    xviii List of Abbreviations AFM Atomic Force Microscope CFU  Colony-Forming Units CSH Cell Surface Hydrophobicity DI Deionized DMSO Dimethyl Sulfoxide DNA Deoxyribonucleic Acid DLS Dynamic Light Scattering E. coli Escherichia Coli LBL Layer-By-Layer LSR Liquid Silicone Rubber MEMS Micro-Electromechanical System NP Nanoparticle PBS Phosphate-Buffered Saline PDMS Poly (Dimethylsiloxane) PMMA Polymethyl Methacrylate PS Polystyrene rpm Revolutions Per Minute ROS Reactive Oxygen Species SEM Scanning Electron Microscope SERS Surface-Enhanced Raman Spectroscopy SPR Surface Plasmon Resonance   xix UV Ultra-Violet UV-Vis Ultraviolet–Visible Spectroscopy wt. %. Weight % ZoI Zone Of Inhibition            xx Acknowledgements  I owe my deepest gratitude to Dr. Keekyoung Kim, my supervisor, whose encouragement, patience and expertise enhanced significantly my graduate experience. This research project was impossible without his constant and kind supports and supervision.  I would also like to thank my committee members, Dr. Deborah Roberts and Dr. Lukas Bichler, for their insightful comments to guide my research and helping me enhance fundamental research backgrounds in microbiology, biochemistry, and materials sciences. Special thanks to Dr. Roberts, who taught me microbiology and provided me with essential materials for microbiology research. I also would like to thank Dr. Chen Feng for sharing his previous time to read my thesis and participate in the final defense exam.   This work has been greatly facilitated by continuous consultations, comments, and encouragements from my lab mates, Mohamed Gamal, Meitham Amereh, Kabilan Sakthivel, Towsif Hossain, Ali Sabanci and Saidul Islam in Integrated Bio-Micro/nanotechnology Laboratory at the University of British Columbia Okanagan.  Last but not least, my very special thanks to my parents, sisters, brother and Zahra, for their endless encouragements and helps throughout my academic career and my whole life.     xxi Dedication        This work is dedicated to my beloved family and Zahra, for all their support and encouragement.     1 Chapter 1: Introduction  Bacteria are one of the oldest living creatures on earth. They have evolved to develop versatile mechanisms for colonizing them on various surfaces for millions of years [1], [2]. Bacteria are found almost everywhere on earth [3] and can adhere to various surfaces and reproduce to form dense structures (i.e., biofilms) with thicknesses varying from micrometers to half a meter [4]. In 1943, Zobell and Allen [5] reported the first study focusing on bacterial adherence on a solid substrate. Since then, bacterial adherence on various natural and artificial substrates have been broadly studied [6], [7]. Biofilms can be generated by bacteria on various surfaces such as soil, surfaces under aquatic conditions, and tissues of organisms. A variety of conditions, which include nutrients, pH, surrounding temperature, and the existence of dissimilar bacteria on the substrate, can affect the biofilm generation. The lifecycle of a biofilm starts with the first bacteria adherent layer to a surface that is created by physical forces, such as thermal forces, van der Waals forces, electrostatic and hydrophobic interactions, steric hindrances and hydrodynamic forces [8]. These forces are commonly induced by the swimming motility part of bacteria (i.e., flagella)[9]. Then, the second layer is created by a bacterial adhesion mechanism that is induced by specific receptor ligands located on the bacterial cell. These adhesions, extracellular polymeric substance (EPS), facilitate the bacteria to create an irreversible matrix and grow additional biofilm on the surface [10], [11]. Biofilms commonly form mushroom-like structures [12]–[14]. There are various steps involved in the development of a biofilm. Three major stages are (I) attachment, (II) growth, and (III) detachment as shown in Figure 1.1.     2  Figure 1.1 Schematic of biofilm formation stages on a substrate (Adapted from [12]).  Bacterial cells in biofilms are less sensitive to antibiotics. Consequently, the formation of biofilms is a major concern in implantable biomedical devices [15], [16]. When the biofilm is formed, high chemical and mechanical resistance among the cells in the biofilm exist, which makes the bacteria cells extremely difficult to destroy or eliminate. The biofilm is considered as the main source of bacterial infection and almost 80% of bacterial contamination in medical devices is caused by the growth of biofilms as reported in the United States [7].  Various methods have been studied for many years to overcome the attachment of bacteria on substrates. Ancient Greeks, Egyptians, and Aztecs first studied the area of preventing bacteria from attachment or growth before a surface or substrate were infected by bacteria by using plants, molds, and soil [17]. Prior to the discovery of antibiotics (i.e., Penicillin), various antibacterial agents, copper-containing materials, silver and its alloys had been exploited for the sterilization of drinking water and wounded areas. However, bacteria can develop antibiotic resistance when antibiotics are used for a long time [18]. Therefore, the quest to produce functional surfaces, which exhibit antibacterial properties, have been comprehensively studied   3 [19]. There have been numerous efforts to develop antibacterial surfaces that are capable of preventing attachment of bacteria cells on the substrate. Theses surfaces can be categorized as antibiofouling (i.e., repelling) and bactericidal (i.e., killing) surfaces [3], [11]. Some antibacterial surfaces have both functions that are capable of repelling and killing bacteria cells simultaneously [1]. Researchers have reported various surfaces that are capable of stopping biofilm formation [20]–[22]. The mechanism of the antibiofouling and bactericidal surface are discussed in detail in the section 1.3. One of the promising fields to develop synesthetic antibacterial surfaces is nanotechnology that is able to generate nanoscale surfaces. Researchers demonstrated that fabricating antibacterial surface using nanoscale antibacterial materials (e.g., silver and gold) have several advantages over macroscale materials since the antibacterial materials have higher activity in nanoscale than macroscale [11]. Nanoparticles (NPs) are classified as particles that have a diameter less than 100 nm. Various classes of antibacterial NPs, which have been used for antibiotic delivery, have shown the potential ability for treating infectious diseases in vitro as well as in vivo [23]. The main benefit of using NPs for improving antibacterial properties is their high surface area to volume ratio that are different from their properties in bulk (e.g., magnetic, chemical, electrical, optical, mechanical, electro-optical, and magneto-optical) [24], [25]. Figure 1.2 shows the change in the surface area to volume ratio between bulk and nanoscale materials. The edge length of the cube is 20 cm. Therefore, the surface area of the cube is equal to 0.24 m2. If the edge length of the cube reduces to 1 mm, there are approximately 8×106 small cubes which are equivalent to a cube with 20 cm edge length and the surface area becomes 48 m2 which is 200 times greater than the 20 cm edge length cube. The further decrease to a cube with   4 10 nm edge length would lead to 8×1021 new cubes. Consequently, the total surface area of the cubes is equal to 4.8 km2 which is 200,000 time greater than the 20 cm edge length cube.         Figure 1.2 Schematic representation of transformation surface are to volume ratio.  Because of the material properties that can be achieved through nanomaterials, many researchers consider NPs as a promising material to fabricate antibacterial surfaces. Metal and metal oxide NPs as a NP that exhibits high antibacterial effect are being tested broadly in the field of medicine. Among them, silver, zinc oxide and titanium dioxide have been used extensively for fabricating antibacterial surfaces as they revealed greater efficiency to kill bacteria and/or stop bacteria growth. One of the main reason is that the size of NPs is similar to most biological molecules and structures. The size effect can also lead to consider the NPs as suitable candidates for various biomedical applications both in vivo and in vitro. Several combinations of NPs have been used for medical sensing, targeted drug delivery, and artificial implants [26]–[32]. Even though the research of antibacterial capability of NPs (metal oxide) continues to increase, one of the main challenges is the lack of information about the toxicity of L= 1 mm n=8×106 A= 48 m2 L=10 nm n=8×1021 A= 4.8 km2 L= 20 cm n=1 A= 0.24 L= 20cm L= 1mm L= 10nm   5 metal oxide NPs for humans and to other organisms in the environment are still a major concern [33]. Hence, with respect to the rapid advancement of antibacterial surface research, the biocompatibility and toxicity of the present antibacterial surfaces is still a big question.  Over the past few decades, several surface modification or treatment methods using NPs have been developed for the fabrication of an efficient antibacterial surface. For the synthesis of artificial antibacterial surfaces, several traditional and advanced surface modification techniques have been used [34]–[37]. These fabrication methods can be widely classified as surface functionalization, derivatization, polymerization, or mechanical surface architecture modification [38], [39]. The first three fabrication techniques mostly focus on the chemical modification of the substrate. However, surface structuring and/or mechanical approaches are considered as physical and mechanical modifications of the substrate [1]. Some of the artificial surfaces have been shown to have bactericidal and/or antibiofouling effects. However, one of the major challenges in this area is to optimize fabrication techniques to create an efficient antibacterial surface that is durable and flexible to diverse humidity, temperature, and pH environments. Based on the previous studies, surface nanotopography is a promising solution to optimize fabrication techniques for antibacterial surface. Various nanotopography surfaces have been studied to create antibacterial surfaces [40], [41]. Based on the architecture of the surface, several shapes have been optimized for the efficiency based on the bacteria shape. In Figure 1.3, five designs have been discussed for charactering the antibacterial properties. The aim of this research study was to examine the effects of patterned topographies on bacterial cells attachment and it was found that cross type was the most efficient microstructure. However, this method requires extensive expertise and special equipment and is not applicable for fabricating larger areas.     6   Figure 1.3 Perspective and top SEM images of the fabricated surface with the different architecture: (A,B) Cross pillars(C,D) Hexagonal pits, (E,F) Cross pillars, (I,J) Sharklet pattern (Adapted from [42]).   C H G E F D B A I J   7 1.1 Bacteria and Material Interactions 1.1.1 Nanotopography and Surface Nanostructuring The main focus of previous studies was on the interactions between bacteria and material surfaces. The chemical reactions of the surfaces that repel the bacteria cells to form biofilm have been studied [12], [41]. However, few studies have reported the surface topography affecting the bacterial adhesion.  Inspired by the antibacterial capabilities of insect wings with the nanostructured pillar array, nanoscale topography concepts for novel anti-adhesion surfaces have recently emerged [18]. Researchers have designed and fabricated topography-based antibacterial surfaces that not only resist adhesion but also kill the bacterial cells [19]. The number of antibacterial surfaces based on the nanoscale topography is growing rapidly. Various fabrication methods, such as nanoimprint lithography (NIL) and deep reactive ion etching (DRIE), have been shown to be promising techniques for the fabrication of high aspect ratio nanostructures as antibacterial surfaces [40], [43]. A summary of research on fabricated nonopatterned surfaces and bacterial attachments are shown in Table 1.1 [12], [44].           8 Table 1.1 Selected patterned-surfaces fabricated recently.    1.1.2 Cell and Surface Dynamics Over the past decades, researchers made great progress in determines the mechanisms in cell-surface dynamics. However, there are still many unknown parameters. The shortage of Bacteria Incubation Time Surface Material Surface Features Height Width Spacing Observation Reference Staphylococcus aureus Incubated For 0.5, 5.5 and 24 Hours PEG microgel and salinized glass slide Circular pillars 90 (nm) α = 1, 2, 3, 5 (µm) β = α/2, α, 2α (µm) Attachment of an order of magnitude less than on the control [45] Staphylococcus aureus Incubated For 2 and 6 Hours Polystyrene Line-like 1.6 (µm) 1, 3, 5 (µm) - cells on lamella-like patterns were significantly reduced compared to control surfaces.  [46] Pillar-like 1.8 (µm) 1, 3, 5 (µm) - Complex lamella 0.471, 4.3 (µm) 2, 5 (µm) - Enterobacter cloacae Incubated For 48 Hours PDMS Cross pillars 23, 9 (µm) 21, 4 (µm) 5, 2 (µm) Confirmed less attachment than the smooth PDMS control. [42] Hexagonal pillars 11 (µm) 3 (µm) 2 (µm) Hexagonal pits 7 (µm) 3 (µm) 5 (µm) Sinusoidal Sharklet 3 (µm) 4, 8, 2, 16 (µm) 2 (µm) Escherichia coli Tested Under Real-Time Flow Conditions PDMS Wells 5 (µm) 10 (µm) 7 (µm) Dynamic stability of the bacterial cells depends on the surface topography and flow parameter [47]   9 nanometer and atomic scale measurement methods have caused discrepant between experimental and theoretical results. The recent development of nano and atomic scale measurement equipment has made it possible to investigate mechanical, biological, chemical, and physical parameters that affect cell–surface interface dynamics. It has been shown that cell behaviors, including their attachment to the surface, are particularly related to the properties of substrate materials. Additionally, several other parameters, such as fluid dynamics, and the specifications of the medium that segregates the bacteria cells and the substrate surface, have been reported to be effective on the dynamics of cell-surface [44], [48]. For example, the fluid dynamics as an active parameter can affect the bacteria cells attachment to the substrate. The probability of the bacterial cell detachment can be also dependent on the fluid flow condition. Various environmental factors of surrounding media, such as temperature, nutrient availability, the chemical combination and concentration of harmful substances (e.g., antibacterial components and metal ions), directly affect the cell–surface dynamics. The nearby medium can increase or decrease bacteria cell attachment not only by changing the characteristics of the surface but also by applying osmotic pressure on the bacterial cells [49]. Another parameter that can affect the dynamics of bacterial attachment is the acidity and ionic intensity of the surrounding solution which is a practical approach to stop bacteria from forming a biofilm on the substrate [50]. It was shown that in lower pH (less than 5.5) the biofilm formation for all Gram-negative and Gram-positive decreased. Due to electrostatic interactions among bacteria in biofilm structure, it has been found that the ionic strength and acidity of the surrounding solution significantly affect the strength of hydrophobicity of the bacterial cell and abiotic target surfaces [44]. Consequently, cell-surface dynamics influence on various biofilm formation parameters, such as initiation, development, and stability. Recently, researchers characterized the interactions between insect   10 wings and bacteria to describe the basic phenomenon how bacteria respond to nanostructured surfaces [51]. Figure 1.4 (A) illustrates the method to depict the bacteria cell rupture under a pressure from an atomic force microscopy (AFM) tip. The tip was placed on top of the bacteria cell, and a constant force was applied to the cell. As shown in Figure 1.4 (B), after the AFM tip pushed cells about 200 nm height from the surface for around 3 minutes the rapture (i.e., dramatic dropping point) happened and consequently bacteria cell will die.    Figure 1.4 Illustration of Cell-Surface dynamics in Cicada wing: (A) The procedure of application of AFM tip. (B) the tip was lowered and the sharp drop indicating the time at which the cell membrane ruptured (Adapted from [21])     11 1.2 Fabrication Methods This section classifies the antibacterial surfaces based on their existence into two main categories: natural and artificial antibacterial surfaces.   1.2.1 Natural Antibacterial Surfaces Bacteria cells, which could form biofilms on insects and plants, can be classified as foreign particles for them. Hence, it is essential for many insects and plants to minimize particle (i.e., biofilm) attachment on their wings for maintaining functionality. Insects and plants have developed diverse methods or mechanisms to avoid foreign particle attachment [52], [53]. Two effectual mechanisms against the bacteria are: 1) hydrophobicity to repel bacterial attachment and 2) nanopillar structure on the wings to disrupt bacteria membrane and consequently kill bacteria. There are several examples of natural antibacterial surfaces: lotus leaves (Nelumbo nucifera) [54], shark skin (Mako shark) [55], and geckos’ feet [56]. Additionally, insect wings, such as cicadae [20], [21], [40], [57], dragonflies,[21] and butterflies [58], also have super-hydrophobic surfaces with antibacterial capability. The best natural antibacterial surfaces that can wipe bacteria out is Clanger cicada (Psaltoda claripennis) wings [59]. Cicada wings demonstrate the high potential of nanopatterned topography as functional antibacterial surfaces resistant to bacterial adhesion. This mechanism not only affects the minimization of the weight and moisture on wings, but also provide self-cleaning effect, which prevents the insects from infections [51]. Figure 1.5 shows that droplets of water easily glide and fall from the insects’ wings (panels E,F,G, and H) and plants leaves (panels A,B,C, and D) to clean or wipe particles out [21].    12  Figure 1.5 Images of different super-hydrophobic plant and insect species and SEM images of topographic structures: (A) Lotus leaves, (B) Indian canna leave, (C) Rear face of purple Setcreasea leave, (D) Rear face of ramee leave, (E) Isoptera Nasutitermes, (F) Hemianax papuensis, (G) Psaltoda claripennis, and (H) Lepidoptera Papilio xuthus. (Adapted from [19])   1.2.2 Artificial Antibacterial Surfaces Although the majority of bacteria are harmless or useful to humans, some pathogenic bacteria can cause infectious diseases. Therefore, finding methods to design and synthesize artificial antibacterial surfaces is highly desirable to prevent human from the bacterial infection. This A BE C D F G H   13 section briefly categorizes three main techniques that are commonly used for the design and fabrication of antibacterial surfaces.  1.2.2.1 Surface Coating Surface coating methods including physical and chemical deposition, plasma-based coating, sol-gel coating, and anodization are among the most common methods for fabricating antibacterial surfaces [27], [60]–[63]. Antibacterial substances (e.g., antibiotics, antibacterial agents, NPs) can be coated and built-up onto the surface. There are two main properties of the surface antibacterial coatings: 1) being toxic to bacteria cells when they come into contact with the surface or 2) releasing an effective antibacterial agent from the surface [19]. These surface properties are highly important for implantable biomedical devices. It is essential for the surface of biomedical devices to possess the antibacterial property when it is considered to be integrated to complex tissue microenvironments [19], [61]. Silver-based coating is widely used in biomedical device applications because it is reported that silver ions are able to kill both Gram-positive and Gram-negative bacteria [64]. Also, researchers have reported that several polymeric coatings can decrease the adhesion of Staphylococcus aureus and Staphylococcus epidermidis bacteria [65]. Protein-resistant poly(ethylene glycol) and hydrophilic poly(methacrylic acid) on titanium implants were used to prevent surfaces from the biofilm formation. To make antibacterial surface on polymeric materials, one can coat inorganic particles on the surface. However, the surface of polymeric materials and inorganic particles are generally repellent each other due to the surface energy difference [66]. This problem is alleviated by NP coating because of the high specific surface area of NPs. However, using NPs for surface coating is not permanent, especially against washing [66]. So far, for stabilizing inorganic NPs on the   14 surface, the techniques require various steps, such as preparation, functionalization, final treatment and curing [63], [66], [67]. These approaches are expensive and time consuming for large scale industrial applications [68].  The main antibacterial mechanism of surface coating modification is releasing the agent slowly into the surrounding environments. Figure 1.6 represents the step-by-step mechanism of using silver NPs. It demonstrates that silver NPs are slowly released from the substrate and then diffused to the medium. The silver ions bind to bacteria membrane and cause the cell lysis. However, several shortcomings have been revealed during the use of the current surface coating techniques [63], [66]. One of the main problems of surface coating is that bacterial cells can become resistant to antibiotics and antibacterial agents over time [1]. Another problem is that the concentration of the released antibacterial agents may not be effective for reducing bacterial cell growth  [69]. Also, the stability of the antibacterial agents or antibiotics on the target surface may not be adequate to retain long-term antibacterial behavior [31].     Figure 1.6 Scheme of the surface coating antibacterial mechanism. (Adapted from [62])   15 1.2.2.2 Layer-by-layer Assembly The layer-by-layer (LbL) assembly technique is the new generation of coating methods. LbL assembly was first reported by Decher et al. in 1992 [11]. Generally, the LbL assembly principle is to deposit oppositely charged polyelectrolytes on a charged surface. There are two types of charged substrate surfaces: 1) naturally charged substrates such as silicones, glasses, and metals, and 2) modified substrates by employing procedures such as strong oxidation, silanation, and high energy electron irradiation [70]. In the LbL assembly process, the charged substrate surface is first soaked into a polyelectrolyte solution that has an opposite charge. Then, the loosely adsorbed polyelectrolyte chains are removed from the surface by rinsing the substrate surface with deionized water (DI water).  Because of depositing the opposite charged polyelectrolyte on top of the surface, the net charge of the surface is reversed. This procedure is repeated with other polyelectrolyte solution that has an opposite charge to the previous solution. Thus, the surface charge is reverted from the starting phase. After repeating the process, a dual polyelectrolyte layer (bilayer) is coated on the substrate surface. By regulating or adjusting the number of deposition cycles, the desired thicknesses and structures of the LbL films on the surface can be fabricated.  The functionality of LbL films is defined by the characterization of the deposited components [70]. These antibacterial LbL films can be categorized into three groups based on their mechanisms: 1) bactericidal, 2) non-adhesive, and 3) multifunctional LbL films as shown in Figure 1.7. Most of charged components, such as metal ions NPs, biological macromolecules, organic molecules, and viruses, can be built up on or combined into the LbL films because the dominant interaction force between LbL films and components is electrostatic force [70]. Consequently, a wide-range of substrates, components, and assembly methods can be used for   16 the LbL assembly technique. This provides a large number of choices to create antibacterial surfaces. A variety of attempts have been made to fabricate antibacterial surfaces using the LbL assembly technique. However, the current challenges of the LbL assembly technique are the synthesis and selection of the charged functional polyelectrolyte components [70].    Figure 1.7 Illustration of LBL fabrication method and three main approaches. (Adapted from [70])    17 1.2.2.3 Synthesis and Polymerization of Nanocomposites Metal/polymer nanocomposites have been widely used in environmental, electronics, optics, catalysts, and biotechnology areas due to their special properties including high mechanical strength, thermal stability, electrical conductivity, and chemical resistance. Several techniques, such as intercalation, in situ polymerization, sol-gel, direct mixing of polymer, and nanofiller, have been used to fabricate nanocomposite materials [26], [71]. Silver (Ag), copper (Cu) and gold (Au) have been most widely used to synthesis NPs with stable dispersion in the metal/polymer matrices [72]. These nanocomposites can be used in a variety of areas, such as biological labeling, optoelectronics and surface-enhanced Raman scattering (SERS) detection [26]. Notably, functionalized and biocompatible metal NPs in nanocomposites have remarkable enhanced cancer detection and therapeutics [73]. In the disease diagnostics and drug delivery, gold (Au) NPs have been widely used [74].  Metal NPs exhibit surface plasmon resonance (SPR) in the ultraviolet visible spectroscopy (UV-Vis). Hence, the synthesized metal NPs in particle shape, size, and inter-particle properties can be detected and measured by changing the absorbance of wavelengths [75]. Researchers have revealed that the size, stability, physical and chemical properties of the metal NPs are dependent upon various parameters such as experimental conditions and the interaction kinematics [72]. Therefore, several chemical and physical methods including electrochemical techniques, photochemical reduction and chemical reduction can be used to stabilize metal NPs [75], [76]. However, the development of proper synthesis methods to control various parameters (e.g., size, stability, and morphology) of metal NPs still remains a  challenge for many researchers [75].    18 1.3 Mechanisms of Antibacterial Surfaces Antibacterial surfaces can be classified into two main categories: 1) antibiofouling and 2) bactericidal surfaces. Antibiofouling generally represents the surfaces that resist or repel bacterial adherence due to undesirable physical or chemical surface conditions for the bacteria growth [52]. Bactericidal surfaces kill the cells in contact due to the chemical reactions between the surface and cell components [43]. The detail mechanisms how the antibacterial agent works against bacteria cells are not fully discovered. However, as NPs are broadly used to develop antibacterial surfaces, several possible mechanisms have been suggested based on their activities. There are three main suggested mechanisms attributed to NPs toxicity: 1) ions of reactive oxygen species (ROS) generated from metal/metal oxide NPs kill bacteria, 2) NPs are directly damage bacteria cell membrane, and 3) free NP ions are released to disrupt ATP production and DNA reproduction [34]. Figure 1.8 shows several mechanisms of NPs toxicity against bacteria.    19   Figure 1.8 Different mechanisms of antibacterial activity of metal nanoparticles. (A) Protein degradation due oxidation causing loss of catalytic activity. (B) DNA damage because of extra hydrogen peroxide (H2O2) or superoxide (O2•−). (C) Cell membrane disruption by the metal ions, allowing them entering into the intracellular region. (D) Damage and stop enzymes, (E) Disturbance with nutrient acceptance and membrane function. (F) Damage to storage granules because of reactive oxygen species (ROS).  1.4 Biocompatibility of Nanoparticles Most of the previous studies have focused on the antibacterial capability of materials. Accordingly, few studies have reported the toxicity of metal and metal oxide NPs against cells, e- Interruption in Transmembrane Enzyme Disruption DNA Damage Cell Membrane Disruption Storage Granule Protein Denaturation       Metal Nanoparticle F E A B C D e-   20 such as mammalian cells and higher-order cells [77]. Metal NPs used in medical fields and commercial products can be leaked to natural environments. NP contamination in soil and water have been previously found that not only has negative impacts on human health but also leading several beneficial microorganisms in the natural environments to be extinguished [24], [78], [79]. Some bacteria are beneficial for the ecosystem and the environment because they are crucial in element cycling, bioremediation and nitrogen fixation for plants [24]. Ammonium nitrogen is transformed to nitrite by ammonia-oxidizing bacteria and then to nitrate by nitrite-oxidizing bacteria particularly in the nitrification procedure. The nitrifying bacteria are effective in the places where a high amount of ammonia exists. However, Ag NPs are toxic to nitrifying bacteria because of the bacterial outer membrane, which contains ammonia-oxidation enzymes, interacts with silver NPs and silver ions. Then, the elimination of beneficial bacteria from the environments leads to decrease in nitrogen production or removal rate and could inhibit plant growth.  The distinctive desired physical and chemical properties of NPs make nanoengineered materials widely used in industrial applications. One of the main advantages is the specific surface area increment to make nanometer-sized particles highly reactive materials [80]. Thus, nanoscale particles are more harmful elements and easily diffuse into the environment of living organisms [33]. A broad range of parameters, such as production volume, industrial applications, and manufacturing settings, can affect the diffusion rate of harmful elements in the environment [81]. Under these conditions, researchers should consider the impacts of the metal NPs on human health and natural environment in spite of their useful features.  Three metal NPs, Ag, ZnO, and TiO2, which are used broadly in industries, are discussed in detail as follows. Silver has been used since 7th century BC as a medicine in ancient Greece and   21 Egypt [80]. Before introducing antibiotics, silver compounds were used to treat and prevent infections. Silver NPs have been extensively commercialized in a broad range of products as an antibacterial/antimicrobial agent. Silver NPs are more toxic than most of toxic silver compounds [82] and have shown a great ability to kill bacteria [75]. It is noted that the toxicity of silver NPs depends on the size and shape of NPs. The cell membrane can be penetrated by silver NPs with a diameter less than 10 nanometres. A recent study on the light-producing bacteria showed that silver NPs could breach a cell wall to cause cell deformation [77]. Also, several studies have claimed that silver NPs can damage the ability of DNA replication of various types of bacteria cells [83]. Silver NPs are also toxic to mammalian cells, such as rat liver cells as a model for human toxicity after inhalation and neuroendocrine cell lines as a specimen which is similar to human brain cells [84]. It has been also shown that silver NPs could significantly damage the male reproductive system [82] and be harmful when they were used and ingested with the implantable biomedical devices [85]. Titanium dioxide (TiO2) NPs are produced worldwide in large amounts for use in a wide range of applications such as, dyes, paints, plastics, and textiles [86]. Hence, the toxicity of TiO2 NPs is important for human health and environmental risk management. Although micro-sized materials are normally considered as harmless, recent studies have shown that continuous inhaling TiO2 NPs could be dangerous [82]. Due to the inhalation of TiO2 NPs, a variety of lung damages in mice, such as pulmonary fibrosis, inflammation, and lung tumors, have been detected [80], [82]. The in vitro experimental results have confirmed that TiO2 NPs could interrupt the function of immune cells.  Zinc oxide (ZnO) NPs are commonly used in cosmetic products such as sunscreens, toothpaste, and beauty products [80]. Therefore, these NPs can directly affect human health. A   22 previous study revealed that ZnO NPs could be toxic to mammalian cells even at low concentrations [87]. The experimental results with mice demonstrated that various reactions occurred, which range from kidney failure and liver damage to death. Researchers have also reported that ZnO NPs damaged different mice’s organs such as spleen, heart, pancreas, and liver [29] and caused several genetic disorders when applied to human skin [88].   1.5 Research Objectives Over the past few years, various NPs with the advancement of nanobiotechnology have improved antibacterial characteristics of the polymeric materials. However, there are too many parameters, type of materials, concentration, and fabrication methods to be optimized. The quest to optimize those parameters for fabricating materials with the enhanced antibacterial capability remains a challenge. In this research project, liquid silicone rubber (LSR) as used, which is the main material for fabricating the nipple of baby bottles, as a model of polymeric nanocomposite. Optimizing the antibacterial capability of LSR nanocomposites mixed with several NPs is the main goal of the research project. To optimize many parameters of LSR with NPs, a high-throughput method is needed. Therefore, microsystems technology is employed to build a miniaturized high-throughput microfluidic platform that enables us to evaluate the antibacterial capability from a variety of material specimens at a time.  Therefore, the overall objectives of this thesis briefly are,  I) Optimization of the parameters for fabricating nanocomposite materials using polymerization method II) Design and fabrication of platforms to characterize antibacterial properties of materials in a high-throughput way.   23 III) Evaluation of antibacterial capabilities of nanoparticles and nanocomposite materials using various methods.    1.6 Thesis Outline This thesis describes the development and characterization of the antibacterial surface nanocomposites. Chapter 1 deliberates backgrounds of the antibacterial surface and mechanisms. Several fabrication methods are reviewed and existing antibacterial surfaces are discussed in detail based on different parameters.  Chapter 2 explains the fabrication method and characterization of antibacterial nanocomposites. One of the main challenges for the fabrication of polymer-nanoparticle composites was the uniform distribution of the NPs inside the polymer structure. To overcome this challenge, several fabrication methods are developed. Also, the difference of the fabricated materials is discussed by the characterization of the nanocomposites. In Chapter 3, the design and development of the microfluidic device is discussed. The device design was optimized using computational simulation. The device was then fabricated in accordance with optimization results. Several microfabrication techniques, such as soft-lithography and 3D printing, are discussed to rapidly fabricate the cost-effective, reusable devices. Chapter 4 presents the completed results of the antibacterial efficiency of three NPs (Ag, TiO2, and ZnO). Disk diffusion, agar plate counting, and live/dead assay methods are discussed to investigate and study the optimal material and concentration.  Chapter 5 provides a short conclusion of the thesis and discusses potential future works for the antibacterial nanocomposite research.   24 Chapter 2: Fabrication and Characterizations of Nanocomposites 2.1 Overview on Nanocomposites Nanocomposite materials possess multi-functionality that is easily applicable to plastics, aerospace, automotive, electronics, packaging, and biomedical devices [89]. They are also a promising candidate for fabricating antibacterial surfaces [90]. Over the last two decades, nanocomposites have been widely used to improve polymeric materials as inorganic NPs can significantly affect physical and chemical properties of polymer-based nanocomposite [89]. There are several techniques to fabricate nanocomposites. Generally, the nanocomposites were synthesised either in the presence of a dissolved polymer (Figure 2.1 left side),  or the polymer was dissolved and mixed with NPs dispersion (Figure 2.1 right side) [89]. The nanocomposite results of the left side methods can produce a material which is totally in nanocomposite form. However, the right side method can only change a part of the polymer to a nanocomposite.   Figure 2.1 Schematic of various approaches to encapsulate NPs into polymer structure.   25 There are two main phenomena, such as aggregation and agglomeration, which are considered as obstacles in the fabrication of polymer-NP nanocomposites (Figure 2.2). A large portion of dried NP nanopowder contains aggregation and/or agglomeration of hundreds or thousands of individual NPs. Therefore, the surface area to volume ratio decreases, resulting in the alteration of physical/chemical properties of NPs. However, it is manageable by during dispersing NPs into a base polymer material by applying high shear force (e.g., ultrasonic forces) on the agglomerated NPs. By doing that, the attractive force among cluster of NPs is broken to make NPs separated from the cluster.    Figure 2.2 Schematic of aggregations and agglomerations formations.  Various parameters of NPs, such as size, shape, surface chemistry, and level of aggregation/agglomeration, directly affect the antibacterial capability of NPs [91]. Therefore, the characterization of NPs is an essential and important step to fabricate antibacterial polymer/NP nanocomposites. In this study, three different NPs (i.e., silver (Ag), titanium dioxide (TiO2), and zinc oxide (ZnO)) have been used for various experiments (SEM images in Appendix A). Single NP Agglomerates NPS Held by weak Wan der Waals Forces Aggregations NPs held by strong chemical bonding    26 2.2 Nanoparticle Characterization The NPs are mostly classified and characterized based on their morphology and particle size distribution [92]. Several methods and advanced microscope equipment have been used to characterize NP’s size and morphology, which include atomic force microscopy (AFM), transmission electron microscopy (TEM), and scanning electron microscopy (SEM). Electron microscopy enables us to not only determine the size of NPs but also the morphology of the NPs [92]. SEM based on electron beam scattering can provide us with the information to determine the mean size of NPs [93]. For SEM imaging, the solvent-NP suspension should be dried and converted into the dry form. Then, the sample is mounted on a sample holder, followed by covering a conductive material using a sputter coater. The sample is then placed in a vacuum chamber and analyzed by a focused electron beam.   2.2.1 Methodology In this research study, dimethyl sulfoxide (DMSO) and a focused ultrasonicator probe have been adopted to evenly disperse NPs. A previous report demonstrated that DMSO is a suitable solvent to disperse NPs with the least degree of aggregations and agglomerations [94]. DMSO is a polar solvent in which oxygen and sulfur atoms are rich, being able to control the monodispersing of NPs with satisfactory size distribution. Several techniques have been investigated to provide adequate forces, such as mechanical vortex, magnetic fields, ultrasonic bath and ultrasonic probe, to overcome attractive particle interactions [91]. To comparatively study these technique, the same concentration of Ag NPs (0.13 g) was dispersed in DMSO for all techniques. The particle size measurement using dynamic light scattering (DLS) showed that ultrasonicator probe is the most efficient technique to disperse NPs (Figure 2.3).   27 2.2.2 Results and Discussion Figure 2.3 illustrates the results of NPs dispersion using three techniques: mechanical vortex, ultrasonicator bath, and ultrasonicator probe. The results showed that the most efficient method to have satisfactory dispersion is ultrasonicator probe. Correspondingly, the shear forces generated from the concentrated ultrasonic probe is powerful to not only break down agglomerate but also be effective on the particle-particle interaction in solution [91]. As a matter of fact, considerable amount of forces in dissimilar directions should be applied to each NP to separate two agglomerated NPs. Predictably, it is unable to reinstate agglomerated NPs back to a well-dispersed suspension which only consists of individual NPs. The main reason may be that the applied shear forces cannot overcome the strength of the van der Waals forces to bind NPs together at nanoscale. Also, it is hardly possible to generate appropriate micro-turbulence at nanoscale, which can create a high force gradient to overcome the binding forces among NPs. Although the sonicator probe was used to apply high micro-turbulence and shear force to NPs, some agglomerations can still be observed.   Figure 2.3 Particles sizing results for mechanical vortex, ultrasonicator bath, and ultrasonicator probe.   28 2.3 Nanocomposite Fabrication  Over the last few decades, several surface treatment methods for the fabrication of antibacterial surfaces have been developed. The surface treatment process can be classified as modification and coating [1]. In this study, in situ polymerization and dip-coating were used as both modification and coating surface treatment methods. Liquid silicone rubber (LSR) was used as the primary material for the fabrication of nanocomposite surface. LSR is an odorless polymer which consists of silicone and oxygen atoms. The siloxane bonds (–Si–O–Si–), are the backbone of silicone, and are particularly stable and their binding energy (433 kJ/mol) is higher than carbon bonds (355 kJ/mol) (C–C). Thus, compared to other organic polymers, LSR have higher heat chemical stability and heat resistivity, vibration absorption, and electrical insulation [95], [96]. Therefore, the chemical and physical properties of LSR make it a perfect material for a wide range of fields such as electrical components, automobile parts, and food industry. Besides the advantages as mentioned above, the biocompatibility of LSR is excellent thus making it suitable for biomedical applications.  LSR is a two components-based polymer. Generally, in two components-based polymers one component is oligomers and the other one is cross-linker [97]. The uncured pre-polymer of LSR is highly viscous liquid and can be cured by heat. The curing procedure starts with mixing the two components with the ratio of 1:1 for 5 min, followed by degassing the mixture in a vacuum chamber to remove the generated bubbles. Afterwards, the mixture was placed in the oven at 65-70 °C for 6 hours to be cured. The summary of synthesizing LSR procedure is show in Figure 2.6.   29  Figure 2.4 LSR fabrication procedure. 2.3.1 Surface Coating  Using nanomaterials for coating provide a substantial prospective application over the conventional coating materials. Dip coating is one of the most popular methods which is broadly exploited in bulk manufacturing processes. Also, there has been increasing attention to this method in material research areas as this technique is regarded as a cost-efficient method [98], [99]. The fundamental idea of this method is to deposit a liquid film by extracting a substrate from a liquid suspension for coating. The dip coating technique consists of four main steps: 1) immersion, 2) deposition, 3) drainage, and 3) evaporation, as shown in Figure 2.7. The theoretical background of this technique is based on the equilibrium of mechanical forces between the withdrawing coating solution and the mounted film. A stagnation line divides the two parts: the top part of this line is the solution which is mounted to the substrate, and the bottom part is the withdrawing solution. The force balance is regulated by viscous drag, surface tension, inertial force, and gravity force. The final film thickness (ℎ) can be derived by the Landau-Levich equation:    𝒉 = 𝒄× (𝜼𝑼)𝟐𝟑𝜸𝟔 × 𝝆𝒈𝟐               (1-1) Mixing Two components 1:1Degassing to remove all bubblesCuring at 65-70 °C for 6h  30 Where c is equal to 0.994 for Newtonian liquids, 𝛾 the surface tension between the solution and air, 𝜌 the liquid density,	𝜂 the solution viscosity, and 𝑈 the withdrawal speed. Although several basic concepts of the dip coating film formation (e.g., evaporation) are ignored in this equation, it can still offer an acceptable idea of the basic dependencies of the film thickness. Nevertheless, these theoretical estimations even with more complex extensions are not mostly practical.    Figure 2.5 Fundamental steps of dip coating technique: A) Immersion, B) Deposition, C) Drainage, and D) Evaporation. 2.3.1.1 Methodology For the dip coating process, isopropyl alcohol (VWR, Radnor, PA, USA) was used as the solvent, followed by adding the same weight of Ag, TiO2 and, ZnO NP nanopowder (100 mg/mL). NPs were smaller than 100 nm and 99.99% trace metal obtained from Sigma-Aldrich Canada (Sigma Aldrich, St. Louis, MO, USA). B C D A   31 To prepare a well-dispersed medium, the nanopowder suspended in isopropyl alcohol was stirred by using a mechanical vortex and then the solution was mixed again using an ultrasonicator probe for 15 min. Afterward, the dip coating process started with the immersion of LSR cubes in three different NP-isopropyl alcohol suspensions. The immersed LSR cubes were placed in the oven at 75°C to evaporate the alcohol and deposit the NPs on the surfaces. This procedure was repeated again until the LSR surfaces were completely covered with the NPs.   2.3.1.2 Results  As shown in Figure 2.8, the coated LSR surface with Ag, TiO2, and ZnO and a LSR cube without coating have been depicted. In Section 2.4, the characterization of the surfaces has been discussed in detail, but it is noted that the physical and mechanical properties of all coated LSR cubes are assumed to be same. As the results showed that the Young’s modulus for all the cubes are equal. (1±0.1 MPa).  Figure 2.6 LSR/NP cube images. (A) simple LSR, (B) LSR/TiO2, (C) LSR/Ag, and (D) LSR/ZnO. A C D B   32 2.3.2 Nanocomposite Polymerization Polymerization is the procedure of chemical reactions by which the monomer subunits form a long molecular chains that is called as a polymer meaning the composition of many repeated subunits (i.e., monomers) [95]. The unique properties of polymers are precisely controlled by the configuration of the long molecular chains that can be categorized as linear, branched, or cross-linked chains. Based on the polymeric structure, they can be also classified as condensation or addition polymers. LSR is normally synthesized as a condensation polymer as well as an addition polymer [100]. In the condensation method, the polymer is synthesized by a series of condensation reactions where functional groups are assimilated together to form a large molecule chain by dropping a small molecule. In the condensation polymerization of LSR, the siloxane curing component is reacted with the hydroxyl group of the polymer. Figure 2.7 shows the schematic of the reaction of two LSR components.    Figure 2.7 Illustration of LSR two components reaction: (A) Polymer chain end (B) Curing agent (C) LSR cured structure A ABC  33 To embed NPs inside polymer chains, it is necessary to apply enough forces to uniformly disperse NPs (Figure 2.8). The difficulties to uniformly disperse the NPs are increased by increasing the viscosity of a base liquid. The force required to overcome the internal hydrodynamic force of highly viscous materials are escalated and thus the possibility to form aggregations/ agglomeration become higher.   Figure 2.8 Schematic of polymerization procedure. (A) Aggregation of NPs inside polymer structure, and (B) Separation of NPs inside the polymer structure due to applied energy.  2.3.2.1 Methodology In this research, the addition method has been used for fabricating LSR/NP nanocomposites. Before it was shown that the effective of wt% for NPs should be in the range of 0.1-50% based on different applications [101], [102]. Therefore, in this research study, 5-20 wt% of NPs was used to cover a different range of wt%. In order to have nanocomposites with different wt% (e.g., 5%, 10%, 15%, and 20%) following steps was performed: 1) 0.5 mL of components ‘A’ of LSR was poured into a 2mL centrifuge tubes 2) To reduce the viscosity of the mixture of LSR, which is around 120 Pa•s, heptane was mixed with the ratio 1:1 by using a vortex machine. This dilution method was previously A BPolymer Matrix Nanoparticles   34 described in IBMNL [103]. The reduction on viscosity may decrease probability of aggregation/agglomeration formations of NPs in a solution. 3) NPs were transferred to the tube and then dispersed by using an ultrasonic probe sonicator (SP Scientific, Gardiner, NY, USA) three times for 10 min with 2 min intervals to cool down the mixture. The use of ultrasonic probe enabled us to provide a better d NPs in the solution (as previously it was shown in Section 2.2.2 and [91], [104]) and evaporate heptane because of the heat produced by the probe.  4) The component ‘B’ was also diluted via the same process as the component ‘A’. Then, two component A and B solutions were mixed by using the ultrasonicator probe three times for 8min each (on) with 2 min intervals (rest).  5) The mixture was poured into a 24-well plate and then placed it in a vacuum chamber for 30 min for degassing.  6) Finally, the solution of NPs and uncured LSR were cured in an oven at 70 °C for 6 hours.   This process repeated for each concentration and material separately as time is critical in the polymerization method. By calculating the mass of the uncured LSR based on its density (1.25 g/cm3), the NP powder was weighed on a balance to measure 0.06g, 0.14g, 0.22g, and 0.31g of NPs to have 5%, 10%, 15%, and 20% wt.%. Also, it is important to locate the tip of the sonicator probe 2mm away from the bottom of the tubes to disperse the NPS nanopowder within the solutions, as the density of Ag, TiO2, and ZnO are higher than LSR (Figure 2.9).    35  Figure 2.9 Schematic of nanocomposite polymerization fabrication setup.  Figure 2.10 shows the fabricated LSR/NP nanocomposites in different fabrication conditions. Nanocomposites with specific NPs can be recognized by the color.    Figure 2.10  LSR/NPs with different conditions; (A-D) LSR/Ag NPs; (E-H) LSR/TiO2 NPs and; (I-L) LSR/ZnO NPs. The concentrations of nanocomposite are increasing 5-20 wt. % from left to right (Scale bar= 5mm).  A C B D E G F H I K J L PDMS LSR Ultrasonicator Probe LSR-heptane Mixture Nanoparticles   36  2.4 Nanocomposite Characterization Several properties such as strength, high-temperature resistivity, and superior thermo-mechanical property can be enhanced by adding NP into polymers [95]. The characterization of LSR/NP nanocomposites is essential to understand and study various effects of NPs within the polymer matrix. Some of the distinctive characteristics of nanocomposites to be characterized are:  a) Effect of NPs on the surface modification and mechanical and thermal properties of nanocomposites.  b) Dispersion uniformity of NPs in the polymer structure and the optimized wt% for the polymerization process. c) Chemical reaction and interaction between polymer chains and NPs and their effects on the physicochemical properties of nanocomposites.
 d) Changes in the morphology of polymer matrix due to the modification/coating of NPs. 
 To characterize various physical and chemical properties of LSR/NPs, a series of characterization methods were conducted. As the objective of this thesis is to fabricate an efficient antibacterial surface, the parameters which can be attributed to the antibacterial capability of surfaces, such as mechanical properties and surfaces hydrophobicity, were analyzed.   2.4.1 Characterization of Mechanical Property  Several material properties, such as stiffness, surface charge, and roughness, can influence the antibacterial effect of the surface [105]. The investigation of the stiffness effect of antibacterial surfaces is important to design antibiofouling surfaces that are potentially applicable to the dental   37 implantable medical devices [48]. It was showed before that by increasing the stiffness of the material the probability of biofilm formation will be deceased [106], [107]. In their experiments, they prepared PDMS with different Young’s modulus (0.1-2.6 MPa) and found that the bacterial cells attached on stiffer material were considerably smaller than on soft substrates. Therefore, the mechanical property characterization result of nanocomposites with different NPs and compositions can be used to elucidate the possibility of bacterial attachment and biofilm formation on the surface with different material stiffness. Herein, the mechanical properties, especially the stiffness of materials, have been investigated in order to evaluate the antibacterial effect of LSR/NP nanocomposites with different stiffness (i.e., Young’s modulus).   2.4.1.1 Experimental Methods A micromechanical tester (Mech-1, Biomomentum, Laval, QC, Canada) was used to characterize Young’s modulus of LSR/NP nanocomposites. This device is consisted of: single-axis load cell with amplification, sample holder, 2-DOF stage controllers, and hardware to software interface (Figure 2.11). The mechanical compression test function of the micromechanical tester was used to determine the Young’s modulus of nanocomposites. Compressive strength or compression strength is defined as the ability of materials or structures to endure loads by reducing the size.  Therefore, the same geometry for all samples is necessary to obtain reliable data. A 24-well plate was used to fabricate the same volume samples. Uncured LSR/NPs with different conditions were poured into each well and the well-plate was placed in the oven to cure the nanocomposite after degassing. The fabricated specimens were then compressed under various loads and data was recorded using an operation software (MACH-1 MOTION SOFTWARE).    38   Figure 2.11 Schematic diagram of the mechanical test system and its main components  The mechanical test was conducted using a cylindrical sample compressed between two parallel plates at a constant speed. Several mechanical properties (e.g., Young’s modulus: E and yield strength: 𝜎𝑦) can be obtained by the compression mechanical test. According to ASTM standard, the test results can be affected by the ratio of initial length to diameter (𝐿0/𝐷), requiring specimen size to be controlled accurately. ASTM D695-96 recommends the specimens with the cross-section of 2:1 (length/height) [108]. Also, the suggested uniform velocity was 1.3 mm/min. However, it was found that the most acceptable velocity for testing samples was 0.8 mm/min for our experiments (Figure 2.12).   2-DOF stage controllers   39    Figure 2.12 Schematic of sample size and velocity of the actuator   Based on our material applications, “Monotonic test” was found to be most proper compression test methods. If the load cell touches the sample with high velocity it may penetrates the surface of the sample. Therefore, the main reason for decreasing the uniform velocity was to prevents the damages in the sample. Stress and strain values are generally calculated by following equations:    𝝈 = 𝑭𝑨𝟎   (2-1)   𝜺 = ∆𝑳𝑳𝟎   (2-2)    40 where F is the applied load; Ao the initial cross-sectional area; and Lo the initial length of the sample.  However, because the initial dimension of the samples is constantly changing, it is essential to calculate engineering stress and strain by considering the changes. The equations for true stress and strain are (assuming sample volume remains unchanged):    𝐴Z𝐿Z = 𝐴	𝐿                            (2-3)   [\] = 	 ]]\ = 	 ^_]\]\ = (1 + 𝜀)   (2-4)            𝜎bcde = f[ = 	 f[ ∙ [\[\ = f[\ ∙ [\[ = 𝜎×(1 + 𝜀)    (2-5)            𝜀bcde = h]]]i]j = 	ln ]i]j 	= ln	(1 + 	𝜀)           (2-6)  , where 𝛿 is the total elongation; A the instantaneous cross-section area of samples; and
𝐿. the instantaneous length of samples. For our experiments, the micromechanical tester raw data were calculated by σnopq and εnopq to consider the changes in specimen (LSR/NPs nanocomposites) dimensions. LSR/NPs nanocomposite samples were prepared by the previously described method. The cylindrical LSR/NP samples were 16.26 mm diameter and 9 mm height. The stress-strain curve of five samples of each material condition was obtained as shown in Figure 2.13. The compressive Young’s modulus was calculated from the slope of the linear region between strains from 0% to 5% as previously suggested by literature [108]. The results show that by increasing the wt% of NPs, the compressive Young’s modulus was increased until 15wt% and after that it   41 decreased. Previously it was shown that increments of NP size within the polymer structure can reduce the stiffness of the nanocomposite [109]–[111]. From 15wt% to 20wt%, as the number of NPs increase, the probability of aggregation/agglomeration formation will increase. The aggregation/agglomerations may affect mechanical properties and the reduction in Young’s modulus may be associated to the formation of aggregated and/or agglomerated NPs in the polymer matrix (Figure 2.8). It has been previously shown that the Young’s modulus of pure LSR was in the range of 1-5 MPa based on the ratio of two components and the fabrication process either using injection molding or casting method [95]. The Young’s modulus of pure LSR with our fabrication procedure was 1± 0.05 MPa (red lines in Figure 2.13). In this research, the minimum Young’s modulus of 1.02	± 0.05 MPa for LSR/ZnO 5 wt% and the maximum Young’s modulus of 3.06 ± 0.12 MPa for LSR/TiO2 15 wt% were observed. Also, from 15% to 20% addition of TiO2 NPs resulted in small increase in Young’s modulus. However, from 15% to 20% addition of Ag and TiO2 did not increase Young’s modulus.  2.4.1.1.1 Statistical Analysis To verify all our experimental result in this research study, the one-way analysis of variance (ANOVA) in Excel (Microsoft, Redmond, WA, United States) was used. Each pair of data sets were individually subjected to one-way ANOVA analysis (single factor). The statistics results are shown in the graphs for all experiment results. The bars show the approach of the analysis between different groups of data. Similar data sets were grouped by horizontal lines. Vertical lines exhibit the tested groups by ANOVA-single factor. The significant different between data sets were shown by * or ** and the value of p is indicated in the figure captions.     42     Figure 2.13 Mechanical properties graph. (A) Silver stress-strain curve (B) Zinc oxide stress-strain curve (C) Titanium dioxide stress-strain curve (D) Young’s modulus changes based on NP wt%. Red line shows the pure LSR Young’s modulus range (n=3, p>0.05, *p<0.05, **p<0.01). A B C D   43 2.4.2 Characterization of Hydrophobic Properties The level and extent of biofilm formation are related to several factors of which the most important parameters are the presence of fimbriae and flagella in the bacteria structure, surface hydrophobicity, and ability to produce EPS. Therefore, bacteria cell surface hydrophobicity (CSH) plays a fundamental role in biofilm formation. Most bacteria are negatively charged [112]. However, bacteria cell can still contain hydrophobic components such as flagella and fimbriae. Fimbriae are the main component in bacteria cell for the attachment on a surface and the main mechanism is to overcome the initial electrostatic repulsions which happen between a cell and surface. The electrostatic force between the cell and substrate is the last repulsion force to stop bacteria from forming an irreversible biofilm [4], [113]. As Figure 2.14 demonstrates, there are two types of biofilm formation, reversible and irreversible [113]. To prevent biofilm formation, the forces which are applicable are hydrophobic and electrostatic interrelations between bacteria and surface. Therefore, altering the surface energy and/or hydrophobicity of the surface is the last opportunity to stop biofilm formation. Consequently, hydrophobicity properties of the surface perform a crucial capacity in the stoppage of bacteria growth on the substrate. Figure 2.14 Bacteria adhesion forces based on the distance    44 Hydrophobic surface properties are widely used in self-cleaning surface, micro/nanofluidics, and electrowetting research areas. The wettability of a surface is usually defined by the measurement of the contact angle of a liquid droplet on the surface of a solid substrate. The resultant contact angle is governed by the mechanical force equilibrium of three interfacial tensions. Shortly, the angle denotes an outline to the relative degree of interface of a liquid with a solid surface. The interface can be defined as the geometrical plane in which two immiscible fluid regions are divided. However, in practice, the interface definition is more complicated. The main reason is that the division of two immiscible fluids depends on the molecular interactions between the fluids (Figure 2.16). Theoretically, the value of the angle can be found from the Young equation that was first described by Thomas Young in 1805 [114].     𝛾]tcos 𝜃y =	 𝛾zt − 𝛾z]     (2-7)  , where 𝛾zt,	𝛾]t and 𝛾z] denote solid-vapor, liquid-vapor, and solid-liquid interfacial tensions and 𝜃y is the contact angle. Based on the Young angle, surfaces can be classified into three types: 1) hydrophilic in which	𝜃y < 90 º; 2) hydrophobic, 90 º ≤ 𝜃y < 150 º; and 3) super-hydrophobic surface, 𝜃y ≥ 130 º, as illustrated in Figure 2.15. For example, the contact angle for human skin is in the range of 75º-90º, for clean gold is less than 10º, and poly(propylene) is 108º.    45  Figure 2.15 Fundamentals of contact angle and surface tension.   2.4.2.1 Experimental Methods For measuring the contact angle of the fabricated surfaces, an established method, direct measurement by camera, has been used [115]. Based on the literature, four main steps were performed for the contact angle measurement: 1. Sample preparation: The specimens (LSR/NP nanocomposite and coated LSR) were prepared in advance and all the surfaces were correctly cleaned before the measurement. The cleaning was done using purified water to remove the dust followed by placing the specimen in the oven to dry the water. 2. Determination of measurement time: A droplet of Type-I water should be deployed on the surface of specimens (LSR/NP nanocomposite and coated LSR) using a needle. The base diameter of the droplet was at least more than 5-7mm. 3. Capturing live images: After dispensing the droplets and detaching the needle, the camera was positioned and adjusted in 3 º with respect to the surface. The camera starts to record the live images for 1-3 minutes. This step was repeated more than three times to eliminate possible errors. 4. Processing the images: The live images were converted to a sequence of images in order to be ready for image processing. ImageJ was used to post-process the images to find the Super-hydrophobic Hydrophobic Hydrophilic   46 contact angle. The Dropsnake plugin in ImageJ was used to determine the contact angles. [116]. The procedure for using this package is presented with detail in Appendix B.    Figure 2.16 (A) Schematic diagram of contact angle measurement setup. (B) Pure LSR contact angle image.   In Table 2.1, all the droplet images from the fabricated nanocomposites and coated surfaces (Section 2.3.1) were summarized.  Table 2.1 Contact angle of different fabricated LSR/NPs.  A B LSR/NP nanocomposites and coated LSR   47 The angles for the coated LSR in Section 2.3 have been measured three times by using ImageJ and the results are illustrated in Figure 2.17.    Figure 2.17 Measured contact angle for pure LSR and coated LSR with different NPs (n=3, p>0.05, *p<0.01).  The results in Figure 2.17 demonstrated that all the coated surface can be categorized as hydrophobic surface. The highest contact angle (148.91º± 5.45 º) was observed from LSR-TiO2 coated surface, which was considered as super-hydrophobic. Therefore, TiO2 was the most effective NPs to increase the surface energy of LSR by almost doubling the contact angle. Considering antibiofouling, all three coated LSR can be categorized as unfavorable surface for bacteria. The results in Figure 2.17 suggests that by increasing the wt% of NPs, the contact angles are increased linearly. The contact angles of Ag NPs were changed from 87.1º± 3.48 º to 117.91º± 5.27 º. The remarkable increment was achieved by TiO2 NPs, where it exhibited the minimum contact angle of 90.64º± 3.24 º and the maximum contact angle of 127.41º± 3.76 º. Contact Angle (°)   48 The results also show that the contact angle of LSR/TiO2 NPs has be increased dramatically when the amount of NPs was above 10 wt% of the LSR. The linear fit for hydrophobicity is shown in Figure 2.18. it can be concluded that addition of TiO2 can increase the contact angle faster than Ag and ZnO as the slope of the linear fit for TiO2 is greater.   Figure 2.18 Graph of contact angles changes with respect to NPs wt% (n=3).  2.4.3 Characterization of Surface Morphology  One of the most important properties to improve the antibacterial is the surface morphology of nanocomposites. In previous sections, the morphology of NPs itself has been investigated and discussed in detail. However, it is necessary to examine the surface morphology of coated LSR. SEM images was obtained to characterize the morphology of the NP which coated surfaces as shown in Figure 2.19. To study the morphology and NPs distribution on the coated LSR, image Linear Fit Ag Y= 1.15×X + 89.18 R2= 0.98 Linear Fit TiO2 Y= 2.50×X + 75.44 R2= 0.97 Linear Fit Ag Y= 1.93×X + 80.23 R2= 0.93   49 processing was performed to measure the area that is covered by NPs. The SEM images were imported to ImageJ. Next, to calibrate the calculation ImageJ scale was changed based on the SEM images scale bar (Analyze» Set Scale). Then, the distribution of NPs was studied via over/under threshold to determine the surface area that is covered by NPs (Image» Adjust» Threshold). Finally, the uncovered LSR area was calculate using Analyze Particles. (Analyze» Particles» Threshold). This experiment was performed in five different panels.    Figure 2.19 SEM images and uncoated area measurements using Image J for LSR coated with different NPs: (A) Ag NPs and (B) area measurement uncoated with Ag NPs, (C) TiO2 NPs and (D) area measurement uncoated with of TiO2 NPs, and (E) ZnO NPs and (F) area measurement uncoated with ZnO NPs.  Magnification: 1000x B A C D E F   50 The clear area (without NPs) in Figure 2.19 was calculated and plotted to find the distribution of NPs on the LSR surfaces. The summation of clear area for Ag, TiO2, and ZnO were equaled to 18108, 513, and 1633	𝜇𝑚. Figure 2.10 illustrates the distribution of the clear area on the coated LSR surfaces.   Figure 2.20 LSR areas uncoated with different NPs (n=5, *p<0.05, **p<0.01).  Fundamentally, the main parameters that play principal role in the wettability of the surface is its roughness and microtopography [117], [118]. Therefore, based on the distribution of the clear area on the coated LSR surfaces, it can be found that TiO2 were coated and dispersed more effectual. The topography and morphology of LSR-TiO2 coated was in the way that the air trapped inside the porosities and based on Cassie-Baxter model the wettability of the substrate have declined noticeably from 90.65±3.6º to 127.41±6.2 º. However, it can be observed that the coated surfaces by Ag and ZnO NPs are covered by aggregated/agglomerated NPs and based on ** Uncoated Area (µm2 )   51 Wenzel model the contact angle will decrease with respect to TiO2 coated LSR.  In Figure 2.21, the principle of two proposed models for rough surfaces has been illustrated.    Figure 2.21 Two models for describing contact in rough surfaces. (A) Cassie-Baxter model and; (B) Wenzel Model  2.5 Chapter Summary In this chapter, the fabrication method and procedure for both coating and polymerization techniques using LSR and NPs have been deliberated. The main challenge was to find a method to uniformly disperse NPs inside or on the LSR structure. An ultrasonicator method was developed and the uniform dispersion of NPs with the method was efficient. Various characterization methods such as mechanical test, contact angle measurement, and SEM micrograph were conducted to evaluate that the fabricated materials have potentials for the antibacterial capability. Mechanical test results showed that the stiffest material was LSR/TiO2 15 wt% with 3.0616 ± 0.12 MPa. The contact angle measurement resulted in the most hydrophobic surface was LSR/TiO2 20 wt% with the contact angle of 127.41º± 3.76 º. Finally, the surface morphology investigation indicated that LSR coated with TiO2 has the highest density of NPs which might increase the antibiofouling effectiveness of the substrate.       A B   52 Chapter 3: Design, Fabrication, and Simulation of High-Throughput Microfluidic Device  3.1 Overview  Over the past decade, microfluidic-based technologies have been rapidly grown and adopted into diverse areas including biology, chemistry, proteomics, drug delivery, and tissue engineering [119]. Microfluidic devices are well suited to the biotechnology research area because they can easily mimic biological systems in which biomolecules are usually transported by biofluids [120]. Generally, microfluidics devices enable to integrate sophisticated bulky equipment into a small size device and to conduct cost-effective and high-throughput research with lesser material consumption than conventional methods [121]. Table 3.1 summarizes the advantages of using microfluidic systems over conventional equipment [122]. Microfluidic platforms generally consist of four main components: 1) micro-channels and micro-chambers which are the main fluidic interconnection, 2) micropumps to transport the fluids through microchannels, 2) microvalves to switch on and off fluid delivery and change fluid directions as required, and 4) active sensing and actuating components combined with devices [123]. Conventional microfabrication techniques have been employed to fabricate microfluidic channel structures on a silicon wafer or glass slide. The first microfluidic device was fabricated on a silicon wafer in the 1960s at the Stanford University for the gas chromatography [93] and then inkjet printer nozzles were developed by IBM [94]. Polymer- or glass-based materials have been recently used for fabricating microfluidic platforms. Glass-based materials, such as soda lime, quartz, Pyrex and Foturan, are the most suitable materials for biological applications due to   53 the properties such as chemically inert, superb insulator, optically transparent, and low auto-fluorescence. In addition, polymer-based materials have been widely used due to advantages such as high transparency as glass, easy to handle, and high touch impact resistance at even low temperatures. Since George Whitesides’ group at Harvard have published the first article regarding the rapid prototyping of  microfluidic devices using poly(dimethylsiloxane) (PDMS) [124], PDMS have been extensively used for fabricating microfluidic devices.  Table 3.1 Summarized advantages of microfluidic devices over conventional systems.  3.2 Design of Microfluidic Platform  To design microfluidic devices, several parameters are necessarily considered. First, the connectivity of inlets and outlet of the devices as fluids flowed through a microchannel are mostly controlled by syringe pumps connected to inlets. Also, the dimensions of both inlet and outlet should be considered due to the availability of proper sized tubes and syringes. Second, appropriate aspect ratio of microchannel height and width should be considered as the channels are mostly created by soft lithography methods. The channels can be easily collapsed and sagged   54 because the deformability of PDMS. Generally, the acceptable aspect ratios (height: width) are in between 1:10-4:1.  One of the aims of this research project is to use the benefit of microfluidic systems for evaluating the antibacterial efficiency of the nanocomposites. A microfluidic platform was designed with the capability of culturing bacteria on multiple chambers in a parallel way and evaluating multiple antibacterial materials at a time. However, a challenge to design such a platform is how to equally deliver media with bacteria to the multiple bacterial culturing chambers. Various designs were previously reported to equally divide a fluid flowed from the inlet [125]. Among them, a tree-shaped network design is most widely used due its simplicity to design without complex calculations. The fluid stream of the initial phase is split by the nearby channel into the next phase. After continuous splitting, the fluid streams are delivered to the site of interest and then combined into the one outlet to exit to outside. Typically, the layout of the tree-shaped networks can be schematized as an electric circuit to simplify the complex networks of the microfluidic platform [126]. To understand flow rates of fluid in each channel, the volumetric pressure drop (∆𝑃) within the inlet and outlet can be obtained through Hagen- Poiseuille's law,                                 ∆𝑃 = 𝑅𝑄                                                      (3-1)  , where 𝑅 and 𝑄 are the hydraulic resistance and flow rate, respectively. The hydraulic resistance of the rectangular channel is:  𝑅€yh = ‚]ƒ€„ [1 − †€‡ˆƒ ‰ˆŠ‰‹,,Ž… tanh(‰‡ƒ€ )]“ ≈ ‚]“•.—(€ ƒ)	 ƒ€„ (3-2)   55 where ℎ and 𝑤 are the rectangular channel height and width, respectively; 𝐿 is the channel length; and 𝜂 is the fluid viscosity [127]. The proposed microfluidic design as shown in Figure 3.1 can be modeled as an electrical circuit to find the flow rate in different sections. It is noted that the size of the microchannels for each stage is maintained constant in order to divide the fluid flow equally and based on Ohm’s law (∆𝑉 = 𝐼𝑅), the flow rate in each channel can be calculated as:              𝑉 = ˜™ ×	𝑅 = 	 ˜™š ×𝑅             (3-3)  Figure 3.1  (A) Microfluidic design (in mm) and, (B) electrical circuit model of the microfluidic systems.  To evaluate the antibacterial surface of multiple nanocomposite specimens at a time, four chambers with 4 mm heights and diameters were designed on a microfluidic platform. Also, a C-shape dam adopted from [128] has been added into the chamber to improve bacteria distribution on the surface of LSR/NPs nanocomposites. The C-shape microstructure has been optimized using COMSOL Multiphysics software (COMSOL Inc., Burlington, MA, USA). Details are V A B   56 discussed in the simulation section. Figure 3.2 represents the final schematic of two proposed microfluidic platforms with or without the C-shape microstructure. Figure 3.2  Proposed microfluidic designs. (A) Normal tree-like network and (B) enhanced tree-like network using C-shape microstructure array.  3.3 Computational Simulation The computational simulations were performed in a 3D domain to analyze fluid dynamics of bacterial medium in different platform configurations. The objective of the simulation was to find the most optimized location of the C-shape microstructure for evenly distributing bacterial cells on the surface of nanocomposite specimens, while reducing the turbulence inside the chambers as shown in Figure 3.3. The C-shape microstructure was previously proven to eliminate vortex from the edges which will cause the leakage of fluids and cell damage [128].   A B Inlet Outlet Inlet Outlet   57   Figure 3.3 Computational simulation results to compare with and without C-shape microstructure: (A) Simulation mesh grid; (B) C-shape configuration; (C) Chamber without the microstructure; (D) Chamber with microstructure.  To begin with microscale fluid mechanics, it is necessary to consider some key features of microfluidic devices which usually can be defined by some dimensionless numbers. One of the dimensionless numbers frequently used in microscale fluid mechanics is Reynolds (Re) number which expresses the ratio of the inertial forces to viscous forces. In the microscale, Reynolds number is generally in the range of 1-20 which clarifies that the dominant force governing the fluid in microscale is viscous forces [122]. The Reynold’s number can be expressed as:    𝑅𝑒 = ›œž = œŸ    (3-4) C D A B   58 , where 𝜌 is the density of the fluid; 𝑣 the velocity of the fluid; 𝑙 the characteristics length (i.e., the hydraulic diameter for non-cylindrical channels); 𝜇 the dynamic viscosity of the fluid; and 𝜐 the kinematic viscosity of the fluid. For all simulations in this thesis, the flow is in the laminar regime and the Reynold number is almost equal to 2.  Another dimensionless number for the study of fluids in curved channels is Dean number (De). If a fluid is passing through a straight channel and then the curved channel, the curvature of the channel changes the directional motion of fluid molecules to cause the secondary movement within the fluid. This number is the product of the Reynolds number and the square root of the channel curvature:     𝐷𝑒 = 𝑅𝑒 ¢£¤           (3-5)  , where 𝑅𝑒 denotes the Reynolds number; 𝐷 equivalent diameter; and 𝑅9 the radius of the channel curvature. For our platform, De number range is 3.2-4.6 which means that the secondary movement of the fluid molecules is negligible.   3.3.1 2D Simulation The C-shape microstructure can affect the rate of cell trapping because its size and shape change the streamline fluidic flow. The microstructure also prevents cells from shear force disturbances. Therefore, using a microstructure can improve bacteria culturing efficiency. To optimize the location of C-shape microstructure, several simulations have been conducted. The most   59 important parameter for the optimization is the distance between the chamber entrance and the center of the C-shape microstructure.   3.3.1.1 Methodology To perform computational simulations in 2D in COMSOL Multiphysics, the geometry was imported from SolidWorks. The microfluidic fluid flow simulations were carried out using single-phase laminar flow package in COMSOL Multiphysics (Fluid flow» Single-phase » Laminar flow). The inlet boundary was defined as a normal inflow velocity which was equal to 0.03 m/s. The outlet boundary condition was chosen as a pressure (Po) which is equal to zero. No slip boundary condition was set for all domain walls. In C-shape microstructure, its boundaries were defined as the inner wall with the no-slip condition. Physics-controlled mesh grids were generated by COMSOL Multiphysics (Figure 3.4). More detail is presented in Appendix C.    Figure 3.4 Boundary conditions and mesh grid for 2D simulations: (A) Inlet, (B) Outlet, (C) Outer wall, (D)Inner wall, and (E) Mesh grid. A B C D D   60 3.3.1.2 Results Simulation results show that fluid velocity streamlines are changed significantly with respect to C-shape position (Figure 3.4). The results for the cases when d is equal to 1mm, 1.3 mm, 1.5mm, 1.7mm, and 2mm are presented. It is clearly observed that the uniformity and distribution of the streamlines is strongly related to the C-shape location. The simulation confirmed that without having the C-shape microstructure, the fluid velocity would be non-uniform distribution although the flow is laminar (Q=0.5mL/min).    Figure 3.5 COMSOL Multiphysics simulation results: (A) Schematic of C-shape distance parameter, (B) d=2mm, (C) d=1.7mm, (D) d=1.5mm, (E) d=1.3mm, and (F) d=1mm    d A D B E C F   61 3.3.2 3D Simulation 3.3.2.1 Modeling of Device Geometry Figure 3.9 shows the dimensions of the 3D model of the platform in two conditions with and without the C-shape microstructure. The 3D solid model was built using SolidWorks® (Dassault system, Vélizy-Villacoublay, France). The, the 3D model was imported to geometry section of the COMSOL Multiphysics® for the 3D computational simulation to consider the influence of all constraints accurately.   Figure 3.6 3D model of the platforms in COMSOL Multiphysics.      9.1m0.8m0.8m0.4m4mm 3.6m1.3m  62 Numerical mesh grids were generated after performing several grid dependence tests with different grid resolutions. The mesh was generated based on the Physics-controlled mesh feature in COMSOL. Figure 3.6 shows the mesh grids used in the two configuration simulations. The maximum and minimum size of the mesh was set to 1.89×10“Ž	𝑚 and 9.99×10“Ž	𝑚, respectively to meet the average element quality, where 0 represents the lowest quality and 1 represents the highest quality [129]. The mesh grid statistics also show that the quality of mesh grids used in this thesis was acceptable based on the physics that were used in this computational simulation [132]. Table 3.2 represents the average element quality for with and without C-shape microstructure.   Figure 3.7 Mesh grids in (A) with C-shape and, (B) without C-shape.  A B   63 Table 3.2 Summary of mesh grid statistics in two configurations.  3.3.2.2 Boundary and Initial Conditions  The microfluidic fluid flow simulations were carried out using single-phase laminar flow package in both designs with and without the C-shape microstructure. For the simulation, the inlet and outlet boundary conditions were set as fluid flow conditions at the inlet and outlet. The inlet boundary was defined as a normal inflow velocity which was equal to 0.03 m/s. The outlet boundary condition was chosen as a pressure (Po) which is equal to zero. No slip boundary condition was set for all domain walls. In C-shape design, its boundaries were defined as the inner wall with the no-slip condition. The material property of fluids was defined as water because water has near equivalent viscosity to the bacterial media as the media is composed of almost 98 wt% of water. The simulations were based on the Navier-Stokes equation: 𝜌 §d§b + 𝑢	. ∇𝑢 = −∇𝑝 + ∇. 𝜇 ∇𝑢 + ∇𝑢 , −  𝜇 ∇	. 𝑢 𝐼 + 𝐹                    (3-5)   , where u is the fluid velocity; p the fluid pressure; ρ the fluid density; µ the fluid dynamic viscosity; I the inertial forces; II the pressures forces; III the viscous forces; and IV the external forces [131]. Because water is assumed as an incompressible and inviscid, the term III is negligible. Term IV is equal to zero as there is no external force on the fluid.  I II III IV   64 The movement of the bacterial cell through the microchannels was implemented using the COMSOL Multiphysics Particle Tracing for Fluid Flow package. The particle properties were set as 2𝜇𝑚 in diameter and 1𝑝𝑔 mass as previously described in Godin et al. [122]. The same inlet and outlet boundary conditions were applied to both particles and fluids. The number of releasing particles was set to 100 per one release. To miniaturize the real case another boundary conditions of the outlet and walls for particles were defined as freezing and bouncing condition, respectively. The drag force was added to the domain to simulate the particle movement accurately. The principle of the particle tracing package in COMSOL is based on the following equation which is derived from Newton’s second law:   hhb (𝑚7v) = 𝐹,   (3-6)  , where 𝑚7is the particle mass; v the particle velocity; and 𝐹,the force exerted on the particle. Another equation which plays an important role in the particle tracing simulations is drag force equation:    𝐹 = °± 𝑚7(u-v)   (3-7)   𝜏7 = 𝜌𝑝𝑑𝑝2¶ž    (3-8) , where τ3is the particle velocity response time;	m3	the particle mass; u the velocity of the fluid; v the velocity of particle; µ the fluid viscosity;	ρ3	the particle density; and	d3the particle diameter [131].    65 3.3.2.3 Results and Discussion The simulation results were obtained from the same 3D geometry of the fabricated microfluidic platform and corresponding properties of the bacteria-medium solution. Particle tracing simulation results are depicted in Figures 3.7 and 3.8 for both with and without C-shape microstructures, respectively.   Figure 3.8 COMSOL Multiphysics particle tracing without C-shape microstructure through time sequence. t=5s t=10s t=15s t=20s t=30s   66   Figure 3.9 COMSOL Multiphysics particle tracing with C-shape microstructure through time sequence. t=30s t=5s t=10s t=15s t=20s   67 It is shown that the particles are spreading slower by adding the C-shape microstructure and consequently there will be sufficient time for bacteria to stick on the nanocomposite surface of the chamber. 10 intersection planes with the same distances by using cut plane feature have been created for both conditions as shown in Figure 3.9. Poincare map diagrams have been used to visualize the number of particles in the defined planes. Next, the summation of the defined planes was collected by using Phase Portrait graph in COMSOL (Figure 3.11 and 3.12).   Figure 3.10 Diagram of defined intersection planes for particle trajectories.  The image for each time step was exported, and by image processing, the results were compared to determine the efficiency in both configurations (details in Appendix D). The value of particles coverage indicates the distribution efficiency. As shown in Figure 3.13, as the covered area by particles reduces, the distribution efficiency of particles decreases. The images sequences were analyzed and the result is shown in Figure 3.14. The results show that adding C-shape microstructure significantly improved the particle distribution within the chamber.  Defined Intersections   68  Figure 3.11 Portrait map of the particles in “without C-shape microstructure”.  t=45s t=10s   69  Figure 3.12 Portrait map of the particles in “with C-shape microstructure”.   t=45s t=10s   70       Figure 3.13 Effects of aggregation of particles on covered area.   Figure 3.14 Post processed result of the particle distribution. (n=5, **p<0.01)  In summary, the computational simulation results confirmed that adding the C-shape microstructure might improve bacteria cell culturing efficiency. This microstructure will provide the consistent distribution of cells on the nanocomposite specimen surface. As previously A B A B C Total area= (A+B)-C Total area= (A+B)   71 described, the main reasons are attributed to the consistent fluid streamlines near the chamber edges and minimized vortices near the boundaries. 3.4 Microfluidic Device Fabrication Microfluidic devices can be fabricated by different methods and techniques. Recently, the softlithography microfabrication technique has been extensively used for rapid prototyping of microfluidic devices for various research applications because of its simplicity and flexibility. PDMS containing silicon and oxygen is most widely used materials in the softlithgraphy microfabrication technique. The PDMS is stable against moisture and temperature, low cost, non-hazardous, biocompatible, and chemically inert. These unique properties made PDMS as an ideal material to fabricate biomedical microfluidic devices. A wide range of methods in softlithography techniques, such as replica molding, micro-contact printing, and micro-transfer molding, have been used before [132]. Lately, three-dimensional (3D) printing technology has shown great improvement in accuracy and resolution, which enable us to print micrometer scale components [133]. Also, 3D printing fabrication process is rapid and cost-effective compared with conventional microfabrication methods. The procedure for this fabrication technique consists of: design replication molds, 3D print the molds, cast components, and assemble a device. All procedures with details are described in the following sections.        72 3.4.1 Mold Design The replica molds were designed using SolidWorks® software. The STL files of both molds are illustrated in Figure 3.12. Due to the high aspect ratio for the holes with the C-shape structure, the holes were designed with 5º angle for the easy removal of the casted PDMS. The molds were printed by a poly jet 3D printer (Object500 Connex, Stratasys Ltd., Eden Prairie, USA) with VeroClear-RGD720® (Stratasys Ltd., Eden Prairie, USA) material.  Figure 3.15 Illustration of the molds: (A-B) Microfluidic rendered SolidWorks® part (C-D) Molds dimensions (E-F) 3D printed molds using the poly jet 3D printer. A B C E F D   73 After printing, the 3D molds were baked at 50º C overnight to remove a residual stress. Residual stress is the internal stress which is locked into a material after production. It is necessary to do silanization process to ease the peel off process as described in the previous study [103]. The objective of the silanization process is to coat a passivation layer on the surface of 3D printed mold for easily seperating PDMS compontes (polymer base and curing agent) from the mold. In this research, Trichloro (1H,1H,2H,2H-perfluro-octyl) silane was used as described in following processes: a. Clean molds by isoprophanol and dry in air. b. Place a vacuum desiccator inside the fume hood. c. Place the molds and a petri dish in the vacuum desiccator. d. Put two drops of the silanizing agent on the petri dish beside the molds. e. Leave them in vacuum codition for 10-15 min to form a monolayer on the molds f. Place the molds on a hotplate in the fume hood at 50ºC for 20 mins to cure and evaporate excessive silane.   3.4.2 Casting and Assembling Device A replica molding method was used to fabricate the microfluidic channels from PDMS (SYLGARD 184, Dow Corning Co., Midland, MI, USA). As shown in Figure 3.13, the process begins with mixing the two components (elastomer and curing agent) with the ratio of 10:1 for 5 min. Then, the mixture was poured on top of the molds in a petri dish to entirely cover the molds with uncured PDMS. The petri dish was then placed under vacuum pressure for 60-90 minutes to remove all bubbles generated by mixing. The petri dish was placed in the oven at 45°C for four   74 hours to cure the PDMS. Lastly, the PDMS with replicated microchannels was peeled off from the mold and placed in the oven at 70°C for 30 min to hard bake the PDMS chip. The inlet and outlets of the chip were punched using a biopsy puncher for tube connection.   Figure 3.16 Schematic procedure of the softlithography technique for fabricating microfluidic chips (A-D).  As shown in Figure 3.14., the sandwiched PMMA plate bolting method was used to assemble the microfluidic platform with the aim to fabricate the reusable microfluidic chip. PMMA plates were used for the rigid base for the PDMS microfluidic chip due to its high A BD   75 mechanical strength, low moisture absorption, and high transparency. The layout of the PMMA plates for the microfluidic platform was designed using SolidWorks® and fabricated by a CO2 laser cutter (Full Spectrum Laser, Las Vegas, USA). The entire platform consists of the PDMS microchannel component, the PMMA base plates, and tubing.  To inspect the platform, it was connected to a syringe pump through tubes with a 2mm inner diameter (Cole-Parmer Canada Company, Montreal, Canada). The performance of the platform against leakage was tested with various flow rates: 400𝜇𝐿/𝑚𝑖𝑛, 800𝜇𝐿/𝑚𝑖𝑛,	 and 0.5𝑚𝐿/𝑚𝑖𝑛. A liquid mixed with food dye was injected at the flow rate of 0.5	𝑚𝐿/𝑚𝑖𝑛 to visualize fluid flow inside the platform as shown in Figure 3.15.  Figure 3.17 Schematic of (A) Assembling procedure of the microfluidic device, (B) Fully assembled microfluidic chip  A B   76  Figure 3.18 Images of a fully assembled microfluidic platform.  3.5 Chapter Summary In this chapter, theoretical background of microfluidics was discussed briefly. One of the main challenges in this study was the uniform distribution of the bacteria cells within the chambers. To address this, a C-shape microstructure was designed to increase the uniformity of bacteria culturing on the specimen surface. The comparison of the two configurations was discussed in detail. To study the distribution efficiency of bacteria cells, a computational simulation using COMSOL Multiphysics software was conducted. The simulation results were used to optimize   77 the location of the C-shape structure for the experiments. All steps for the simulations such as describing the geometry of chips, boundary condition, mesh grids statistics, and simulation results were rigorously explained. Finally, the fabrication process of the high-throughput microfluidic platform was described in detail. The microfluidic chip was fabricated by the replica molding technique using PDMS materials and the entire platform was fabricated by the sandwiched PMMA plate bolting method. As a result, an inexpensive (cost ≈5$) microfluidic was developed platform which can be used to culture different cell types.     78 Chapter 4: Antibacterial Efficiency of NPs and Fabricated Nanocomposites   4.1 Overview on Bacteria Growth and Antibacterial Efficiency Microbiology describes growth as the incremental increase in the cellular numbers [134]. It is essential to study microbial population growth because it is a prerequisite for designing the techniques to stop or control the microbial growth. Most of the bacterial species reproduce by binary fission [49]. To reproduce, fully-grown parent bacterial cell splits into two and generate two new daughter cells. In order to study bacteria population growth, studying and analyzing the microbial culture growth curve is important. Four main periods can be named in bacteria growth curve: (I) Lag phase; (II) Exponential phase (log) phase; (III) Stationary phase; and (IV) Death phase. Figure 4.1 represdents the four main phases of the growth curve.   Figure 4.1 Typical microbial growth curve for bacteria population. (Four main phases are marked)  (III) Stationary phase (II) Exponential phase (log) phase (I) Lag phase (IV) Death phase   79 Several techniques and procedures have been carried out to determine the antimicrobial activity of materials. These methods can be categorized as dilution techniques, diffusion tests, and time-to-result techniques. To investigate all the antibacterial properties of nanocomposites and NPs nanocomposites, three antibacterial efficiency tests have been performed: disk diffusion test, viable counts, and live/dead staining. The first test was performed to study the bacteria toxicity of NPs. Then, LSR/NPs nanocomposite efficiency was evaluated through viable counts and live/dead staining techniques. Escherichia coli or E. coli (ATCC 11775) was used for all experiments. E. coli is a Gram-negative, rod-shaped, and facultative anaerobic bacterium. E. coli strains are mostly harmless. However, some types can cause several serious problems such as kidney failure, urinary tract infections, and diarrhea [135], [136]. The main source of E. coli infections in humans is due to the food poisoning. One of the foods that can be infected with E. coli is raw or dairy milk. The main source of milk contamination is because of bacteria spreading from a cow's udders. If the pasteurization process was not perfectly performed, the risk of milk bacteria contamination would increase. This is one of the example that show the importance of bacterial contamination. Therefore, questing for a nontoxic and durable antibacterial surface/material can not only improve human health management but also be revolutionary in food packaging industry. This chapter describes the procedure, materials, methods, and analysis of the three efficiency examination results.   4.2 Disk Diffusion Method The agar diffusion test or Kirby–Bauer test is an examination of the antibacterial susceptibility of bacteria. This test is one of the oldest methods for antibacterial sensitivity test, and it is still one of the most common antibacterial testing techniques. In this method, paper disks (are   80 covered with antibacterial particles) are used to test the extent of the antibacterial elements onto several bacterial cultures. The paper disks are located on an agar plate where bacteria have been cultured before. If the coated paper disks kill the bacteria and/or stop their growth, a zone appears around the disks representing in which there are no bacteria. This area is called Zone of Inhibition or ZoI. ZoI size directly differs with respect to the antibacterial efficiency of the material. Obviously, a stronger bactericidal material will produce a larger inhibition zone.   4.2.1 Materials and Methods 4.2.1.1 Chemicals and Materials The sterile paper disks and nanopowder of Ag, ZnO and TiO2 NPs were obtained from Sigma-Aldrich Canada. According to the manufacturer's materials information, the size of particles is <100 nm and 99.99% trace metal basis. Dimethyl sulfoxide (DMSO) was purchased from VWR Canada (VWR, Radnor, PA, USA). Microbiology Media: lysogeny broth, Luria-Bertani (LB) and Oxoid Agar Bacteriological were obtained in powder form from Fisher Scientific Canada. The bactericidal activity experiments were carried out using Gram-negative bacteria, E. coli (ATCC 11775).   4.2.1.2 Culturing Bacteria E. coli was used as the representative of Gram-negative bacteria in all experiments. As per instruction of the supplier 25 gr/L, LB broth powder was dissolved and mixed in water and sterilize by autoclaving (15 min). The bacteria were grown in the medium for one day at 37 °C in an incubator shaker at 110 rpm. The bacterial suspension was diluted to 105 – 106 cells/mL for the toxicity measurements. The dilution was achieved by using phosphate-buffered saline (PBS)   81 and serial dilution technique. As the growth rate for mesophiles bacteria is slow at low temperatures, for all experiments the bacteria were maintained in LB Broth medium in a 4 °C refrigerator to prevent population growth of the bacteria culture.   4.2.1.3 Mixing and Preparing Paper Disks Four different concentrations of Ag, ZnO and TiO2 DMSO/nanopowder were prepared, to examine the antimicrobial ability of NPs on E. coli. These nanopowder were suspended in DMSO at concentrations: 100, 50, 10, 0.2 mg/ml. The DMSO/nanopowder suspensions were sonicated using a focused ultra-sonicator. The solutions were under the ultrasonicator probe for 30 minutes, three times in order to have well-distributed suspension of NPs in the solutions. [91]. Figure 4.2 shows all the solutions.   Figure 4.2 The distinctive appearance of different nanoparticles in four concentrations: (A) Ag 100 mg/mL, (B) Ag 50 mg/mL, (C) Ag 10 mg/mL, (D) Ag 0.2 mg/mL, (E) TiO2 100 mg/mL, (F) TiO2 50 mg/mL, (G) TiO2 10 mg/mL, (H) TiO2 0.2 mg/mL, (I) ZnO 100 mg/mL, (J) ZnO 50 mg/mL, (K) ZnO 10 mg/mL, and (L) ZnO 0.2 mg/mL.   82  The 6mm paper disks were soaked in the DMSO solutions then dried in a laminar hood in a sterile Petri dish. The antibacterial evaluation of metal NPs was executed using the disk diffusion method (Kirby–Bauer agar plating technique). Sterilized liquid agar was poured into sterile Petri dishes and allowed to solidify in a laminar hood. The antibacterial capability was modified using the agar well diffusion method [137]. Aliquots of 150 µL of bacterial culture with 106 colony-forming units (CFU)/mL concentration, were dispensed on the counting agar surface using sterile pipette tips and spread by a sterile polystyrene (PS) spreader. Each Petri dish was divided into 7 equal subsections. The impregnated disks were positioned on the agar surface with equal spacing. Two sterile paper disks without the metal NPs coatings (soaked in pure DMSO and dried) were used as the control for all the experiments. After arranging the disks, the inoculated Petri dishes were incubated for 24 hours at 37 °C. The antibacterial activity of NPs was evaluated by measuring the diameter of the zone of inhibition using a Vernier caliper  4.2.1.4 Measurement of NP Size Distributions The DMSO\NP suspensions were transferred into the specific cuvettes to allow measurement of the actual size of NPs in the solution in a Malvern Zetasizer Nano ZS (Malvern Instruments Ltd, Malvern, Worcestershire, UK). The device measures particle sizes based on quantification of the random variations in the scattering intensity of light within a suspension or solution, this method is known as dynamic light scattering (DLS).    83 4.2.2 Experimental Results 4.2.2.1 Characterization of Nanoparticles For the size measurement analyses, the prerequisite optical properties are the refractive index (n) and absorption (K), which are equal to k=3.99, 0.001, 0.00 a.u. and n=0.135, 2.41, 2.008, respectively for silver, zinc oxide and titanium dioxide. The examination of NP distributions in our solutions (Fig. 4.3) revealed that the ultrasonicator method was powerful enough to break down the agglomerated NPs. Using DLS, the majority of the NPs size quantified in the range between 80-120 nm confirming that the particles were not agglomerated.  Figure 4.3 Particle size distributions of (A) Ag, (B) TiO2 and (C) ZnO nanoparticles determined using a Mastersizer.  4.2.2.2 Antibacterial Assay  The in-vitro antibacterial efficiency of metal and metal oxide NPs: Ag, ZnO, and TiO2 were assessed using the agar disk diffusion assay. The control disks showed no antimicrobial activity. All NPs revealed signs of toxicity to the tested bacteria (Table 4-1). The ZoI results showed that A B C  84 the antibacterial capability of NPs varies with respect to the NPs physical and chemical form. It was previously concluded that TiO2 exhibited toxicity against bacteria at even low concentration. In this study, TiO2 NPs demonstrated no visible toxicity to E. coli at low concentrations. The results of the antibacterial tests show that ZnO was the most toxic to E. coli. (Figure 4.4 and 4.5)   Figure 4.4 Disk diffusion tests for different nanoparticles against the E. coli. The zone of inhibition (ZoI) is shown with a dashed circle representing a noticeable antibacterial influence. (1) TiO2 10 mg/mL; (2) TiO2 50 mg/mL; (3) ZnO 50 mg/mL; (4) ZnO 0.2 mg/mL; (5) ZnO 10 mg/mL; (6 and 8) Control; (7) TiO2 0.2 mg/mL; (9) TiO2 100 mg/mL; (10) Ag 100 mg/mL; (11) Ag 50 mg/mL; (12) Ag 10 mg/mL; (13) Ag 0.2 mg/mL; and (14) ZnO 100 mg/mL.         85  Figure 4.5 Bar graph of antibacterial activity of nanoparticles against E. coli in four concentrations (n=4, p>0.05, *p<0.05, **p<0.01).   Table 4.1 Mean zone of inhibition in diameter, (n=4)   	Nanoparticle Inhibition Zone (mm) Concentration (mg/mL) 100 50 10 0.2 Silver 4 ± 0.4 3.2 ± 0.3 2.2 ± 0.2 0.96 ± 0.2 Zinc oxide 8.5 ± 0.2 3.7 ± 0.1 0.5 ± 0.3 0.3 ± 0.1 TItanium dioxide 1.5 ± 0.1 0.2 ± 0.1 N/A N/A ZOI (mm) ZOI (mm) ZOI (mm)   86 4.2.2.3 Discussion Various techniques and methods have been investigated to provide adequate force to overcome the attractive particle interactions such as mechanical vortex, magnetic fields, ultrasonic bath, and ultrasonic probe. Another difficulty is to reinstate agglomerated NPs back to a well-spread suspension in which only consists of primary NPs individually. The main reason of aggregation/agglomeration is related to the strength of the Van der Waals forces that attracts NPs together in which that the shear forces cannot overcome the particle-particle force in the nanoscale. To separate two agglomerated NPs forces in dissimilar directions, have to be applied at nanosized to each NP and. It is hardly possible to generate appropriate micro-turbulence which creates a high force gradient to overcome the binding forces between the NPs. Hence, in the experiments, a concentrated ultrasonic probe was used to apply high micro-turbulence and shear force to the particles. The experimental result of NP distributions revealed that the ultrasonicator method is powerful enough to break down the agglomerate NPs because this method is able to overcome the particle-particle interaction in the solution. The ZoI results showed that the antibacterial capability of NPs can be varied with respect to the NPs physical and chemical form. It was previously concluded that TiO2 exhibits toxicity against bacteria at even low concentration [138]. In this study, TiO2 NPs nanopowder demonstrated no visible toxicity on E. coli at low concentrations. As previously it was shown, the main reason can be attributed to the fact that TiO2 is only capable of ROS generation, while ZnO and silver can release metal ion [139], [140]. The results of the antibacterial tests show that ZnO is the most toxic nanopowder to E. coli tested in this experiment. The MIC graphs also showed that the rate of the antibacterial capability of Ag, TiO2, and ZnO NPs will increase unequally and the best candidate of the tested materials is ZnO NPs.   87  4.3 Viable Counts Method The viable counts method to determine bacterial numbers is the most observable method. This low-cost, fast, and straightforward method is divided into two main techniques: 1) spread-plate technique and 2) pour-plate technique. A general assumption in the viable counts method is that the viable bacterial cells can grow and divide to form one colony. Therefore, counting the number of colonies reflects the number of viable bacteria cells in a sample. The number of viable bacteria can be found from the serial sample dilution before spreading and the number of colonies on the agar plates in CFU/mL (colony-forming units per mL).   4.3.1 Materials and Methods Lysogeny broth, Luria-Bertani (LB) and Oxoid Agar Bacteriological were obtained in powder form from Fisher Scientific Canada. E. coli (ATCC 11775) was used for experiments. The uncured LSR/NP nanocomposites were prepared using an ultrasonicator probe as described in Chapter 2. PDMS elastomer and curing agent (SYLGARD 184) were purchased from Dow Corning Co. PMMA sheets with 5 mm thickness were obtained from the local supplier. In the following sections, the process of the viable counts method using a high-throughput microfluidic chip described in detail.  4.3.1.1 Microfluidic Platform Preparation  Four microfluidic chips were prepared for four different LSR/NP nanocomposites with %wt of 5%, 10%, 15%, and 20%. In each chip, four chambers were equally filled with LSR/Ag, LSR/TiO2 LSR/ZnO, and LSR using a pipette. Next, the microfluidic chips were placed in a   88 desiccator for degassing under the vacuum pressure. The chips were cured in the oven at 65 °C for 6 hours. The modified PMMA plates were used to assemble the entire chips. Figure 4.7 shows the fully assembled microfluidic device.   Figure 4.6 The microfluidic chips with and without the LSR/NP nanocomposites and the fully assembled microfluidic platform.   4.3.1.2 Culturing Bacteria on Microfluidic Platform As previously described in Section 4.2, 25 gr/L of LB broth powder was dissolved and mixed in the sterilized Type 1 (ultrapure) water. The bacteria were grown overnight at 37 °C in an incubator shaker at 110 rpm. The bacterial suspension was adjusted to have 105 CFU/mL by using PBS and serial dilution procedure. For all experiments, the bacteria kept in LB Broth medium was stored in a refrigerator at 4 °C to disable bacteria population growth. For culturing   89 bacteria through the high-throughput microfluidic device, the bacterial culture was transferred to a sterile syringe. The syringe was connected via tubing and connectors to the microfluidic platforms. The flow rate of a syringe pump was adjusted to 0.5	𝑚𝐿/𝑚𝑖𝑛. The bacteria in medium was injected into the microfluidic systems under laminar flow until all the chambers were filled. Afterwards, the platforms were transferred to the incubator and the temperature was set to 37 °C, which was reported as the optimum temperature for E. coli growth [141]. No medium evaporations were observed and this can be attributed to the fact that there was no medium leakage from the microfluidic platforms.   4.3.1.3 Characterization of Bacteria Cell Viability  The procedure was started by placing cultured microfluidic chips in the incubator at 37 °C. The antibacterial performance test was carried out over 8 hours of culturing to expose the bacteria on the antibacterial effect of nanocomposites. In each time point (i.e., 2 hours, 4 hours, and 8 hours), the chip was placed in a sonicator bath for 60 s to detach the possible biofilm formation from the surfaces as previously described by Zips et al. [142]. Afterwards, the bacterial cells in each chamber were collected by mixing with PBS using a pipette. The collected medium was dispensed on the agar plate in petri dishes, followed by spreading the medium using a sterile spreader. The petri dishes were placed in the incubator at 37 °C overnight. The images from 2 hours, 4 hours, and 8 hours data were recorded by the microcopy camera and the viability from the recorded image were measured three times at each time point.    90 4.3.2 Results and Discussion Manually counting colonies units on agar plates is a time-consuming and tedious work. An automatic counting method was employed. This was performed using ImageJ software (National Institutes of Health, Bethesda, Maryland, USA) which is an open source Java-based image processing program. The analyze particle function in ImageJ enabled us to count the number of colonies faster and more accurately. The procedure for using this toolbar is discussed in detail in Appendix E.  The same CFU/mL of bacteria in raw milk (~105 CFU/mL [143]) was used for all experiments to minimize the biofilm formation. Figure 4.8 presents colonies on each specimen after 2 hours and 8 hours. The number of colonies in the viable counts method are usually in the range of 30-300 colonies per plate to discuss the results quantitatively. Since some agar plates have exceeded 300 colonies (350-400) in this research study, the number of colonies were divided by the maximum CFU in the control sample to be normalized between 0-1. Figure 4.9 illustrates the normalized CFU per each condition. The results demonstrated that LSR/TiO2 nanocomposites was the most effective antibacterial materials. However, at low concentration (5 wt%), the effect of the antibacterial agents was not sufficient to stop bacteria growth and/or kill bacteria cells. It was also observed that at high concentration (20 wt%), the efficiency was decreased possibly due to the aggregation/agglomeration of NPs inside the nanocomposites. Finally, this research resulted in that the best antibacterial nanocomposites was LSR with 15 wt% TiO2.    91    Figure 4.7 E. coli growth after 2, 4 and 8 hours on the surface of (A) LSR/Ag NPs; (B) LSR/TiO2 NPs; and (C) LSR/ZnO NPs. (n=3, p>0.05, *p < 0.05, **<0.01)  A B C *  Normalized CFU Normalized CFU Normalized CFU   92 4.4 Live/Dead Assay Method Live/dead staining technique using fluorescence dyes is one of the methods in which the cell viability can be quantitatively evaluated. For staining cells and measuring the cell viability, two main parameters, such as plasma membrane integrity and intercellular esterase activity, are considered. In this section, the antibacterial capability of the LSR/NP nanocomposites using the live/dead cell viability assay is studied and discussed.   4.4.1 Materials and Methods The bacterial cells were fluorescently labeled using a live/dead cell viability kit (Biotium, Fremont, CA, USA). The kit contains two fluorescence dyes: ethidium homodimer III (EthD-III) and calcein acetoxymethyl (Calcein AM). Calcein AM, which is a membrane-permeable dye, enters into the cytoplasm of bacteria cells and is cleaved to esterase in only live cells to yield the green fluorescent signal. EthD-III is a plasma membrane-impermeable DNA dye that is excluded by live cells and virtually non-fluorescent before it binds to the DNA of dead cells to produce a bright red fluorescence signal. The standard staining protocol is as follows. First, Calcein-AM and EthD-III stock solutions are placed at room temperature for 30 min to melt the solutions. Then, 1 µL of Calcein-AM and 5 µL of EthD-III are added to 1 mL of PBS. The resultant solution is vortexed to mix adequately and kept in the dark, cold place before use. The bacterial cell viability was evaluated by the same procedure as the procedure previously described in the viable counts method. After 8 hours culturing, the cells were stained using the prepared solution and an inverted fluorescent microscope (ZEISS Axio Observer, Zeiss, Germany) was used to monitor the viability of the bacterial cells. Two fluorescent channels were used to record the fluorescence microscope images of live and dead bacteria cells. The Z-stacking imaging mode   93 and ApoTome. 2 device (Zeiss, Germany) were used to capture a series of clear fluorescence images in the Z direction to prevent the variability of data from the non-uniformity of the surface.   4.4.2 Results and Discussion The live/dead assayed bacteria cells were monitored using 40X oil objective lens. Figure 4.8 presents the fluorescence images of the samples without NPs as a control. Figure 4.9 presents the fluorescence images of the samples with various NPs. To analyze the bacterial cell viability, the images were converted to 16-bit gray value format and the number of bacterial cells was counted by the nucleus counting plugin in ImageJ software (The image processing procedure is described in Appendix F). Finally, the antibacterial efficiency of the samples was calculated using the following formula:   𝐴𝑛𝑡𝑖𝑏𝑎𝑐𝑡𝑒𝑟𝑖𝑎𝑙	Efficiency	% = ÇdÈÉec	Z.	heÊh	ÉÊ9becËʝ	9eÌ,Zbʝ	‰dÈÉec	Z.	Ëœe	&	heÊh	ÉÊ9becËʝ	9eÌ ×100   (4.2)   The results of the live/dead assay method are agreed well with the one obtained from the viable counts method. As shown in Figure 4.10, 15 wt% NPs for all three types are the most efficient antibacterial agents. Also, among the three types of NPs, LSR/TiO2 nanocomposites showed the best antibacterial capability in the range of 10-15 wt%. In agreement with the previous Section 4.3, the antibacterial efficiency was decreased over 15 wt% NPs possibly due to the formation of   94 aggregation/agglomeration of NPs within the LSR. Therefore, the main challenge in antibacterial nanocomposite fabrication is to avoid the aggregation/agglomerations of NPs. Figure 4.8 Fluorescence images of live/dead assayed E. coli cultured on LSR without NPs as the control experiment. (A) 0 hour and (B) 8 hours culture of bacteria. Scale bar = 20 µm.  Figure 4.9 Fluorescence images of live/dead assayed E. coli after 8 hours culture on various LSR/NP nanocomposites. Scale bar = 20 µm. Control BA5 wt. % 10 wt. 15 wt. 20 wt. Ag TiZn  95   Figure 4.10 Antibacterial efficiency of LSR/NP nanocomposites after 8 hours  (n=3, p>0.05, *p < 0.05, **p<0.01).  4.5 Chapter Summary In this chapter, the experimental studies of the antibacterial effectiveness of the LSR/NP nanocomposites were discussed and described. Three different methods of antibacterial efficiency experiments were performed to characterize NPs and LSR/NPs nanocomposites. First, the antibacterial effectiveness of the NPs was evaluated using the disk diffusion method. The study revealed that ZnO NPs among three different types of NPs possessed the highest toxicity against E. coli. Second, the antibacterial efficiency of the fabricated LSR/NP nanocomposites were evaluated through the high-throughput microfluidic platforms and viable counts technique. LSR/TiO2 nanocomposites demonstrated the best antibacterial nanocomposite. Also, the   96 minimum antibacterial effectiveness was observed in LSR/Ag NP nanocomposites. Finally, the viability of E. coli, which were exposed to LSR/NPs on the microfluidic platform, was assessed and studied using the live/dead assay method. The obtained results were well matched with the results from the viable counts methods. Also, it was found from the both methods that the antibacterial capability of the nanocomposites was decreased after 15 wt%. This result can be possibly attributed to the non-uniform dispersion of NPs over 15 wt% within the polymer structure, which is the most critical challenge in antibacterial nanocomposite fabrication.    97 Chapter 5: Conclusion and Future Work  5.1 Conclusion The antibacterial materials for food storage and biomedical devices may play an important role in preventing humans from bacterial infections. One of the most common ways to fabricate antibacterial materials is to integrate the antibacterial agent into a base material structure. In this research project, the antibacterial nanocomposite materials were fabricated by encapsulating inorganic NPs into LSR structure. The fabrication process was carried out using an ultrasonicator probe to uniformly disperse the NPs in the viscous pre-polymer solution. The NPs and fabricated LSR/NP nanocomposites were characterized by various characterization methods. The type and concentration (i.e., wt%) of NPs affected several characteristics of LSR/NP nanocomposites, such morphology, mechanical, and hydrophobicity properties. The LSR/15 wt% TiO2 nanocomposite with revealed the highest mechanical Young’s Modules among all the nanocomposites. Also, the contact angle test showed that the most hydrophobic surface was the LSR/20 wt% TiO2 nanocomposite. The effectiveness of the antibacterial nanocomposite was assessed by using a high-throughput microfluidic platform. The device facilitated the experiments to be done rapidly in an inexpensive and high-throughput way. A C-shape microstructure was designed to improve the performance of the microfluidic chip. The microstructure was optimized using COMSOL simulations. The combination on 3D printing and replica molding technique were used to fabricate the reusable microfluidic platform. The fabricated PDMS chip was assembled with the sandwiched PMMA plate bolting method.    98 Three different tests were carried out to study the antibacterial efficiency of the NPs and LSR/NP nanocomposites. First, the antibacterial efficiency of pure NPs was evaluated by the disk diffusion method to measure ZoI. ZnO NPs exhibited the highest antibacterial efficiency against to E. coli. Next, the antibacterial LSR/NPs nanocomposites were assessed by two different techniques: 1) viable counts and 2) live/dead viability assay. The obtained results from both techniques showed that LSR/TiO2 with 15 wt% was the most effective antibacterial nanocomposite, while LSR/Ag with 5 wt% was the least.  The disk diffusion method resulted in the observation that ZnO as the most effective antibacterial NP. However, experiments done using the agar plate counting and live/dead viability assay methods showed LSR/TiO2 nanocomposites as the best antibacterial material. This discrepancy may be associated to the differences in hydrophobicity, solubility and mode of action of ZnO and TiO2:  § Hydrophobicity: It was previously concluded that as hydrophobicity increases, the required time for material diffusion increases and consequently ZoI will be smaller [144]. The results in Chapter 2 showed that TiO2 is more hydrophobic than ZnO. Therefore, the required time for TiO2 diffusion is more than ZnO and ZoI for TiO2 is smaller than ZnO.  § Solubility: The solubility is one of the main factors which affects the diffusion rate of material in disk diffusion method. Based on previous studies, it was shown that solubility of ZnO is higher than TiO2 [145]–[147]. Therefore, Zn2+ ions can diffuse easier than Ti4+ ions and consequently higher ZoI can be observed by ZnO. § Mode of action: The main three mode of action in NPs are: (i) dissolution, (ii) cellular uptake, and (iii) production of reactive oxygen species These antibacterial   99 activities can be categorized as in direct and indirect effects [140]. Therefore, the antibacterial activity of NPs may vary in different experiments based on the direct or indirect contact of NPs. When the bacteria were in direct contact with the LSR/NP nanocomposites by using microfluidic platform, the mode of action would have been more important in the antibacterial capability of the materials. De Angelis et al. concluded that TiO2 has higher impacts on bacterial cells than ZnO when NPs are in direct contact with bacteria and generally, TiO2 NPs antibacterial mechanisms are effective when they are in contact with bacterial cells [147], [148].  The hydrophobicity tests showed that the contact angle for the nanocomposites were measured as TiO2 > ZnO > Ag. Also, Young’s modulus of the fabricated nanocomposites was measured TiO2 > Ag > ZnO. Also, the results revealed that the increment trend for hydrophobicity and antibacterial efficiency were in good agreement. Likewise, as NPs wt% increase, the contact angle of the surfaces is increased. However, this trend is not applied to the antibacterial efficiency of nanocomposites with NPs above 15 wt%.  It is worth noting that the increment of wt% increases the antibacterial efficiency up to the specific concentration above which the antibacterial efficiency is decreased and tis may be associated to aggregation/agglomeration formation of NPs. The aggregation/ agglomeration can reduce the surface area to volume ratio, resulting in deteriorating the antibacterial capability. Summary of all the experiment results is shown in Table 5-1. Maximum and minimum value in each test are highlighted.    100 Table 5.1  Summary of all experimental results.  5.2 Future Work Several future works can be suggested to address the remaining challenges to fabricate a novel antibacterial nanocomposite as follows,  • Study the toxicity of the fabricated nanocomposites on mammalian cells. One of the essential parameters of the antibacterial nanocomposites is the toxicity of the NPs and LSR/NP nanocomposites on the mammalian cells. As the main goal of synthesizing the nanocomposites is to use them in food and biomedical industries, these materials are usually in direct contact with humans. Hence in order to produce an appropriate material, the toxicity of the nanocomposites to human is mandatory.   101 • Develop microfluidic devices for longer bacteria culturing. The microfluidic platform used in this study is capable of delivering both bacterial and media through only one inlet. By using the single delivery platform, the duration of the experiments is limited. The development of a chip that is able to inject materials through multiple inlets enable us to culture and study bacterial cells for a longer time. For the future work, a proposed microfluidic design is shown in Figure 5.1 below.   Figure 5.1 Schematic of the proposed microfluidic chip.  • Further optimization for wt% of NPs. Our experiments results demonstrated that the extremum point in antibacterial efficiency can be achieved in the range of 10-15 wt% of NPs. Therefore, both toxicity on mammalian cells and antibacterial efficiency should be analyzed in this range in order to find the optimized wt% for LSR/NP nanocomposites. • Find a biocompatible NPs. Recently, several green polymeric NPs also have been studied such as chitosan. Therefore, the investigation and comparison of the inorganic and organic NPs can be implemented to fabricate an effectual biocompatible antibacterial nanocomposite. 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The coated glass slides were used to characterize the shape and size of NPs. Figure S.1 illustrates the SEM images and size measurements of the NPs on the glass slides. Based on the SEM images, it may be concluded that the size of NPs is in the range from 50 nm to 250 nm, which is acceptable in accordance with the manufacturer specification. For studying the morphology of the NPs ImageJ was used. For processing the images: I. Importing the image: The agar plate image should be imported and converted to a grayscale or 8-bit image. (File» Import » Image» Type » 8-bit) II. Adjusting threshold: to optimize the cell counting process, the threshold of the images should be regulated while the all the cells are visible. (Image » Adjust » Threshold) III. De-noising the image: The noises were reduced using band-pass filter (Process » FFT » Bandpass Filter).  It is noted that the shape of the majority of Ag NPs are almost spherical [149]; TiO2 NPs are roughly hexagonal prisms with unsharpened edges [150]; and majority of ZnO NPs are in cylindrical structure [151]. In Figure S.1, TiO2 NPs are aggregated and NPs boundaries are not clear completely.    121  Figure S.1 SEM images and size measurements of three different NPs. (A) and (B) Ag NPs, (C) and (D) TiO2 NPs, and (E) and (F) ZnO NPs.  DCB A E1µm 0.5µm F1µm 0.5µm   122  Figure S.2 Processed images of NPs on the glass slides: (A)Ag NPs, (B) TiO2 NPs, and (C) ZnO NPs.   2 µm 500nm 500nm   123 Appendix B   This appendix covers the detailed steps for finding the contact angle in Chapter 2. For measuring the contact angle a DropSnake V2.0 plugin in ImageJ (a java based image processing program) was used. The contact angle is measured by a piecewise polynomial fit based on the edge of the liquid. The sequence of using the DropSnake plugin is discussed as follows: I. Importing the image sequence: For importing the images sequence for the measurement the image sequence should be used (File» Import » Image sequence) II. Converting image to 8-bit: In order to process the image, it should be converted to an 8-bit image. (Image» Type » 8-bit) III. Adjusting the brightness and tilt angle: After importing the images, the brightness should be set to have visible boundaries between liquid and air (Adjust » Brightness/Contrast). Also, to delete the possible errors of tilting the line tool determined the tilt angle of the surface and liquid with respect to the horizontal axis. After measuring the angle, it can be altered using the arbitrarily control to correct the angle. (Image » Rotate » Arbitrarily) IV. Cropping the area of interest: To improve the computational efficiency of the image processing it is beneficial to crop the image to neglect the unwanted section of the image (Image » Crop) V. Launching and initialization the DropSnake plugin: in the Add/move knot mode, place about 5-10 knots on the drop boundary. It is mandatory to define the drop contour starting from the left side of the drop boundary going along until the right side. After placing the last knot, by double-clicking on the image the spline will be closed.  VI. Refining the obtained spline: The knots positions can be changed by dragging and dropping to correct the spline.    124 VII. Recording the contact angle: Contact angles are showed in the image. Also, the measured contact angles will be transferred to the results table section, which can be exported as an excel file.   Figure S.3 Measuring contact angle by using DropSnake Plugin: (A) Automatic obtained spline and, (B) Refined spline.  A B   125 Appendix C   This appendix shows the screenshot of COMSOL Multiphysics simulations in 2D and 3D. Figure S.4 shows 2D simulation step by step. Figure S.5 shows 3D simulation step by step Figure S.4 Screenshot of COMSOL Multiphysics 2D simulations. Model Studies 1. Defining the fluid properties 3. Defining mesh  2. Defining the fluid properties 4. Defining study   126 Figure S.5 Screenshot of COMSOL Multiphysics 3D simulations.    1. Laminar flow simulation 2. Defining boundary conditions 3. Particle tracing simulation 4. Defining boundary conditions 5. Defining mesh  6. Defining fluid study 7. Coupling particles and fluid    127 Appendix D   This appendix covers the detailed steps for finding covered area by particles in Chapter 3. For determining the covered area, Particle Analyze in ImageJ was used. To calculate the total area Following steps were performed: I. Importing the image sequence: The image sequence for each time step should be imported and converted to a grayscale or 8-bit image. (File» Import » Image sequence» Type » 8-bit) II. Cropping the area of interest: The undesirable sections of the image should be cleared to show only the microfluidic domain. This can be achieved using the rectangular shape and cropping features. (Rectangle » Edit » Clear Outside) III. Adjusting threshold: In order to optimize the counting process, the image threshold should be adjusted while the all the particles are visualized. (Image » Adjust » Threshold) IV. Analyzing the image: To measure the area of particles, “Analyze Particles” feature is used.  V. Recording the results: The total calculate area of the particle is recorded in the result window. To save the results, the window should be exported to an excel file  Figure S.6 An example of the obtained results by ImageJ. .    128 Appendix E   This appendix describes the detailed method to count the colonies in agar plate counting method (Chapter 4). Counting colonies number is a time consuming and laborious procedure. Therefore, to decrease the error due to the manually counting the colonies an image processing method was utilized. Particle Analyzing in ImageJ, which is a Java-based image processing program, was used to count the number of colonies. Following steps show the full procedure: VI. Importing the image: The agar plate image should be imported and converted to a grayscale or 8-bit image. (File» Import » Image» Type » 8-bit) VII. Cropping the area of interest: The undesirable sections of the image should be cleared to show only the petri dish. This can be achieved using the oval shape and cropping features. (Oval » Edit » Clear Outside) VIII. Adjusting threshold: In order to optimize the counting process, the image threshold should be adjusted while the maximum number of colonies are visualized. (Image » Adjust » Threshold) IX. Analyzing the image: To count the number of colonies, “Analyze Particles” feature is used. The size and the circularity are the main parameters to optimize the number colonies measurements.  X. Recording the results: The total number of the colonies is recorded in the result window. To save the results, the window should be exported as an excel file. Image S.2 represents all the procedure. It is also notable that this method not only performs the counting faster but also increase the accuracy of the counting. As an example, Figure S.3 shows the capability of this technique to distinguish the colonies competently.     129   Figure S.7 Automatic colony counting using ImageJ; (A-E) The sequence of images processing from raw image to the counted is presented.  Figure S.8 An example to show the accuracy of the automatic colony counting procedure.   B A CD E  130 Appendix F   This appendix explains the complete technique to live/dead assay image processing which used in chapter 4. Wright Cell Imaging Facility (WCIF, University Health Network, Toronto, ON, Canada) was used for cell viability calculation. In order to perform automatic counting, Nucleus Counter plugin in particle analysis section was used. The steps for the counting is explained as follows: I. Exporting the fluorescence image: The captured images should be exported separately for each channel (green as live cells and red as dead cells). II. Importing the image: The exported images should be imported and converted to a grayscale or 8-bit image. (File» Import » Image» Type » 8-bit) III. Adjusting threshold: to optimize the cell counting process, the threshold of the images should be regulated while the all the cells are visible. (Image » Adjust » Threshold) IV. Analyzing the image: the cell number automatically can be counted via nucleus counter plugin. (Plugins» Particle Analysis » nucleolus counter) V. Recording the results: the plugin will record the number of counted cells, and it will be shown in the result section of the ImageJ program.  The full procedure should be carried out for each channel. Figure S.4 represents the steps of image processing to count the number of dead and live cells. The formula which was used in chapter 4 was: 𝑨𝒏𝒕𝒊𝒃𝒂𝒄𝒕𝒆𝒓𝒊𝒂𝒍	𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲	% = 𝑵𝒖𝒎𝒃𝒆𝒓	𝒐𝒇	𝒅𝒆𝒂𝒅	𝒃𝒂𝒄𝒕𝒆𝒓𝒊𝒂𝒍	𝒄𝒆𝒍𝒍𝒔𝑻𝒐𝒕𝒂𝒍	𝒏𝒖𝒎𝒃𝒆𝒓	𝒐𝒇	𝒍𝒊𝒗𝒆	&	𝒅𝒆𝒂𝒅	𝒃𝒂𝒄𝒕𝒆𝒓𝒊𝒂𝒍	𝒄𝒆𝒍𝒍𝒔 ×𝟏𝟎𝟎    (4.2)     131  Figure S.9 Required steps to post-process the captured fluorescence images; (A) Importing the images separately for each channel; (B) Converting the image format to 8-bit or 16-bit; (C) adjusting the threshold to count the cells; (D) collecting and exporting the obtained cell counting results. C DA B

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