Engineering and Modeling Carbon Nanofiller-Based Scaffolds for Tissue Regeneration

ENGINEERING AND MODELING CARBON

NANOFILLER-BASED SCAFFOLDS FOR

TISSUE REGENERATION

Dissertation

Submitted

The School of Engineering of the

UNIVERSITY OF DAYTON

In Partial Fulfillment of the Requirements for

The Degree of

Doctor of Philosophy in Engineering

Nuha Hamad Al Habis, M.S.

UNIVERSITY OF DAYTON

Dayton, Ohio

August, 2017

ENGINEERING AND MODELING CARBON NANOFILLER-BASED SCAFFOLDS

FOR TISSUE REGENERATION

Name: Al Habis, Nuha Hamad

APPROVED BY:

Khalid Lafdi, Ph.D. Donald Klosterman, Ph.D. Advisor Committee Chairman Committee Member Professor; Wright Brothers Endowed Joint Appointment with University of Chair in Nanomaterials, Chemical & Dayton Research Institute, Chemical Materials Engineering Department & Materials Engineering Department

Tony Saliba, Ph.D. Katia Del Rio-Tsonis, Ph.D. Committee Member Wilke Committee Member Distinguished Professor; Dean Professor; Department of Biology, Emeritus, Chemical & Materials Center for Visual Sciences at Miami Engineering Department University (CVSMU)

Robert J. Wilkens, Ph.D.,P.E. Eddy M. Rojas, Ph.D., M.A., P. E. Associate Dean for Research and Dean, School of Engineering Innovation Professor School of Engineering

Qc Copyright by

Nuha Hamad Al Habis

2017

ABSTRACT

ENGINEERING AND MODELING CARBON NANOFILLER-BASED SCAFFOLDS

FOR TISSUE REGENERATION

Name: Al Habis, Nuha Hamad University of Dayton

Advisor: Dr. Khalid Lafdi

Conductive biopolymers are starting to emerge as potential scaffolds of the future.

These scaffolds exhibit some unique properties such as inherent conductivity, mechanical and surface properties. Traditionally, a conjugated polymer is used to constitute a conductive network. An alternative method currently being used is nanofillers as additives in the polymer. In this dissertation, we fabricated an intelligent scaffold for use in tissue engineering applications. The main idea was to enhance the mechanical, electrical properties and cell growth of scaffolds by using distinct types of nanofillers such as graphene, carbon nanofiber and carbon black. We identified the optimal concentrations of nano-additive in both fibrous and film scaffolds to obtain the highest mechanical and electrical properties without neglecting any of them. Lastly, we investigated the performance of these scaffold with cell biology.

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To accomplish these tasks, we first studied the mechanical properties of the scaffold as a function of morphology, concentration and variety of carbon nanofillers. Results showed that there was a gradual increase of the modulus and the fracture strength while using carbon black, carbon nanofiber and graphene, due to the small and strong carbon-to- carbon bonds and the length of the interlayer spacing. Moreover, regardless of the fabrication method, there was an increase in mechanical properties as the concentration of nanofillers increased until a threshold of 7 wt% was reached for the nanofiller film scaffold and 1%wt for the fibrous scaffold. Experimental results of carbon black exhibited a good agreement when compared with data obtained using numerical approaches and analytical models, especially in the case of lower carbon black fractions.

Second, we examined the influence of electrical properties of nanofillers based on the concentration and the geometry of carbon nanofillers in the polymer matrix using experimental and numerical simulation approaches. The experimental results showed an increase in conductivity as the amount of nanofiller concentration increased. And regardless of nanofiller type, the trend remained the same. The percolation threshold was around 4-5wt% of nano-additive with PCL and PAN matrices, respectively. However, at the same concentrations, conductivity was higher in graphene-based nanocomposites than for CNF and carbon black-based nanocomposites. The numerical modeling highlighted the effect of nanofillers as constructing a conductive network due to the aggregation phenomenon. The conductivity trend for carbon black and carbon nanofiber-based composites by the numerical simulation approach was similar to the experimental approach.

Importantly, as the conductivity of the scaffolds increased, so did the cell density.

Consequently, this study has highlighted the close relationship between electrical conductivity, cell density and scaffold orientation. An increase in conductivity can be achieved in two ways: by molecular orientation of the nanofillers or by the appropriate selection of nano-additives such as graphene and carbon nanofiber.

Dedicated to my parents (Hamad & Amira) and my sibling

ACKNOWLEDGMENTS

My special thanks are in order to Dr. Khalid Lafdi, my advisor, for providing the time and equipment necessary for the work contained herein, and for directing this thesis and bringing it to its conclusion with patience and expertise. Thank you for helping me grow as an individual, a researcher and an engineer.

I would also like to express my appreciation to my dissertation committee. Thank you for your patience, guidance and advice throughout my studies. Dr. Klosterman, thank you for your assistance with helping me learn all of the instruments. Dr. Del Rio-Tsonis, thank you for allowing me to do my work in your lab at the Miami University. Dr. Saliba, thank you for your support and being part of my committee. It was an honor to share ideas, meetings and discussions. It was also an honor to have each of you on my committee and

I hold your thoughts and advice at the highest level.

To my friends, thank you for your patience, knowledge and support. This includes

Robyn Bradford-Vialva, who patiently helped with proofreading and editing; Dana Tobias, who offered guidance with the burning rate measurements; Christian Gutierrez, who supported me by giving me his time and knowledge through parts of this work.

Additionally, I thank my lab members in Kettering Lab, specifically Saja Nabat. Special thanks to Hassan Abd Al Majeed who supported and helped me to overcome tough times.

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TABLE OF CONTENTS

ABSTRACT ...... iii

ACKNOWLEDGMENTS ...... vii

LIST OF FIGURES ...... xii

LIST OF TABLES ...... xvii

LIST OF ABBREVIATIONS AND NOTATIONS ...... xviii

CHAPTER I LITERATURE REVIEW ...... 1

Background ...... 1 1. Tissue Engineering...... 1 2. Skin Grafts and Organ Transplants ...... 3

Introduction ...... 4 1. Tissue Scaffolds ...... 5 1.1. Hard Scaffolds ...... 9 1.2. Soft Scaffolds ...... 11 2. Materials Approach to Improved Scaffold ...... 12 2.1 Biopolymer and Compatible Polymers...... 12 2.1.1. Compatibility ...... 18 2.1.2. Structural Properties ...... 19 3. Conductive Scaffolds ...... 20 3.1. Conductive Polymers Approach ...... 21 3.1.1. Polypyrrole (PPy) ...... 23 3.1.2. Polyaniline (PANI) ...... 25 3.1.3. Polythiophene (PTh) ...... 26 3.1.4. Blend Polymers ...... 27 3.2. Carbon Additives Approach ...... 32 3.2.1 Conductivity...... 38 3.2.2. Surface Properties ...... 40 3.2.3. Cell Viability ...... 46 3.2.4. Durability ...... 47

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Cell Culture ...... 50 1. Cell Propagation...... 50

CHAPTER II MATERIALS AND CHARACTERIZATION ...... 53

Materials ...... 53 1. Graphene ...... 53 2. Carbon Nanofiber (CNF) ...... 54 3. Carbon Black ...... 55

Fabrication Method ...... 56 1. Spin-coating ...... 56 2. Electrospinning ...... 58

Materials Characterization ...... 59 1. X-Ray Diffractometer ...... 59 2. Raman Spectroscopy ...... 60 3. A Scanning Electron Microscope (SEM) ...... 61 4. Thermomechanical Analysis (TMA) ...... 62 5 Electrical Conductivity...... 63 6. Fluorescence Microscope ...... 63 7. MATLAB and ImageJ Software ...... 64

Cell Culture ...... 64 1. Thawing Procedure for Frozen Cells ...... 64 2. Flask Cultures Procedure ...... 65 3. Subculturing Procedure ...... 65

CHAPTER III MECHANICAL PROPERTIES OF CARBON NANO-ADDITIVES /POLY(Ε-CAPROLACTONE) BASED TISSUE SCAFFOLDS ...... 66

Introduction ...... 66

Materials and Experimental Methods ...... 70

Results ...... 72 1. Analytical Modeling of CB/PCL Elastic Moduli...... 78 1.1. Analytical bounds for CB/PCL modelling ...... 78 Hashin Shtrikman Bounds [148] ...... 78 Third-order Bounds (3OB) [149, 161] ...... 79 1.2. Direct Analytical Estimation ...... 79 2. Numerical Modeling of CB/PCL Elastic Modulus ...... 81 2.1. Generating and Meshing of the Model ...... 81 2.2. Comparison of Experimental Data with Analytical and Numerical Approaches ...... 83

3. Mechanical Behavior of Nano-Additives/PCL Nanocomposites ...... 84

Discussion and Conclusion ...... 88

CHAPTER IV INTELLIGENT DESIGN OF CONDUCTING NETWORK IN POLYMERS USING NUMERICAL AND EXPERIMENTAL APPROACHES ...... 90

Introduction ...... 90

Materials and Experimental Methods ...... 93 1. Materials ...... 93 1.1. Preparation of PAN Nanocomposite ...... 95 1.2. Preparation of PCL nanocomposite ...... 95 1.3. Preparation of mixtures for the “cocktail” approach ...... 95 2. Characterization ...... 96 3. Numerical Method ...... 96 3.1. Process Description ...... 98

Results ...... 100 1. Simulation Results ...... 100 1.1. Equivalent Resistance Solving ...... 100 1.2. Scaling &Time ...... 103 1.3. Aggregation principle ...... 104 1.4. Influence of Dagr Parameter ...... 105 1.5. Carbon Black in the Spin Coating Film ...... 107 1.6. Carbon Nanofiber in the Spin Coating Film ...... 107 1.7. The Mix of Carbon Blacks and Carbon Nanofiber ...... 111 2. Experimental Results ...... 113

Discussion and Conclusions ...... 118

CHAPTER V ENHANCING THE CELL GROWTH USING CONDUCTIVE SCAFFOLDS ...... 121

Introduction ...... 121

Materials and Experimental Methods ...... 124 1. Materials ...... 124 2. Fabrication of Conducting Scaffold ...... 125 3. Electrical Measurement ...... 126 4. Cell Culture and Seeding ...... 126 4.1 Sub-Culturing Procedure ...... 127 4.2 Fixing Adherent Cells ...... 127 x

5. Characterization ...... 127

Results and Discussion ...... 128

Conclusion ...... 137

CHAPTER VI CONCLUSION AND RECOMMENDATIONS ...... 138

REFERENCES ...... 141

LIST OF FIGURES

Figure 1.1. Cross-sectional SEM micrographs of (a) non-ﬁbrous methods to

manipulate micromorphology, (b) methods commonly employed to create

3D scaffolds exhibiting ﬁbrous structures with diameters on the order of

native ECM [11]...... 8

Figure 1.2. Injectable 3D-formed composite of β-TCP beads and alginate: (a) light

microscope photograph of the composite, (b) SEM photograph of the

composite, (c) SEM photograph of the composite surface. Bar is 1,000 µm

in (b) and 100 µm in (c) [14]...... 9

Figure 1.3. A few examples of tissue engineered scaffolds used in clinical tissue

regeneration for: (a) diabetic foot ulcer, (b) ear reconstruction, (c) human

mandibular reconstruction, (d) articular cartilage regeneration; (e) coronary

artery regeneration [25,26]...... 13

Figure 1.4. Architectures for biodegradable conducting polymers [63]...... 22

Figure 1.5. Polypyrrole reversible reaction [54]...... 23

Figure 1.6. Polypyrrole-configuration heteroaromatic rings and heteroquinoid form

[70]...... 27

Figure 1.7. (a) PCL non-conductive scaffold compared to (b) conductive scaffold

with PCL [75]...... 29

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Figure 1.8. Conductive nanofibrous scaffolds composed of PEGs-b -(PTh)4 and

PCL for tissue engineering [81]...... 32

Figure 1.9. Behavior of a two-way SME. Note step 2 of the cycle is ‘fix’ which

involves cooling at constant stress [116]...... 50

Figure 2.1. Illustration of Graphene structure [121]...... 54

Figure 2.2. Carbon nanofibers...... 55

Figure 2.3. Carbon black structure...... 56

Figure 2.4. Spin-coating process diagram [129]...... 57

Figure 2.5. Spin-coating device ...... 57

Figure 2.6. Electrospinning process diagram...... 59

Figure 2.7. X-ray diffraction machine [131]...... 60

Figure 2.8. Raman spectrometer (Renishaw inVia Raman microscope) [133]...... 61

Figure 2.9. The phenom ProX desktop scanning electron microscope (SEM) [135].

...... 62

Figure 2.10. Thermal mechanical analysis...... 63

Figure 2.11. Fluorescence microscope [136]...... 64

Figure 3.1. Dark field imaging shows the morphology of carbon black (left image) and its onion-like structure (right image) [157]...... 71

Figure 3.2. Typical stress-strain curves for 0% and 1wt% CB obtained during the

experimental tests on film scaffold for 3 and 4 samples each...... 73

Figure 3.3. Typical stress-strain curves for 3 and 5 wt% CB obtained during the

experimental tests on film scaffolds for 4 samples each...... 74

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Figure 3.4. Typical stress-strain curves for 7 and 10 wt% CB obtained during

experimental testing on film scaffolds for 4 samples each...... 75

Figure 3.5. The relationship of modulus vs. additives concentration for film

scaffolds...... 77

Figure 3.6. Microstructures of CB/PCL composites...... 82

Figure 3.7. Meshes of microstructures used for numerical simulations...... 83

Figure 3.8. Elastic modulus vs. additive concentration for the fibrous scaffolds...... 85

Figure 3.9. Elastic modulus vs. additive concentration for the film scaffolds...... 85

Figure 3.10. Typical stress-strain curves for CB, CNF, and graphene obtained

during experimental tests on fibrous scaffolds (upper) and film scaffolds

(bottom)...... 87

Figure 4.1. Illustration of minimal distance calculation ...... 98

Figure 4.2. The flow chart of numerical process...... 99

Figure 4.3. Illustration of network's different configuration...... 101

Figure 4.4. Variance variation vs. Base volume...... 103

Figure 4.5. Illustration of aggregation principle...... 105

Figure 4.6. (a) Evolution of conductivity vs. percentage (b) conductivity evaluation

vs. Dagr ...... 106

Figure 4.7 (a) Example of a spin coating film with CB, (b) Graphical view of the

48 simulations' results, (c) Conductivity vs. carbon blacks percentage in

weight, (d) Percolation proportion vs. carbon black concentration ...... 109

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Figure 4.8. (a) Example of a spin coating film with Carbon Nanofiber, (b) Graphical

view of the 48 simulations' results, (c) Conductivity vs Carbon Nanofiber

percentage in weight, (d) Percolation proportion vs Carbon nanofiber

concentration...... 110

Figure 4.9. (a) Example of a spin coating film with a mix of Carbon Nanofiber &

Carbon Black, (b) CB/CNT Mixture Law for Conductivity ...... 112

Figure 4.10. SEM images of (a) carbon black, (b) CNTs, (c) graphene. SEM images

of spin coating film of (d) CB/PAN, (e) CNT/PAN, (f) graphene/PAN.

SEM images of spin coating film of (g) 10 wt% of CB/PCL, (h) 10wt% of

CNT/PCL (i) 10wt% of graphene/PCL...... 115

Figure 4.11. Comparison of Raman spectra of CB, CNF and graphene...... 116

Figure 4.12. Relationship between the conductivity & concentration of the nano-

additive with (a) PCL systems (b) PAN systems...... 117

Figure 4.13. The Mixture Law of 5%wt of CB & CNF/ PAN nanocomposites ...... 118

Figure 5.1. v. Dark field imaging shows the onion like structure of carbon black

(CB) [278]...... 128

Figure 5.2. SEM morphology of carbon nanofibers (CNF)...... 129

Figure 5.3. SEM morphology of graphene platelets...... 129

Figure 5.4. SEM images of electrospinning based fibers of (a) CB/PCL, (b)

CNF/PCL, (c) graphene/PCL...... 130

Figure 5.5. SEM images of spin-coating based samples of (a) CB/PCL, (b)

CNF/PCL and (c) graphene/PCL ...... 130

Figure 5. 6. XRD measurements of (a) graphene, (b) CNF and (c) CB...... 131

Figure 5. 7 Fluorescent microscope images of fixed HLE cells stained with DAPI

and grown on CB, CNF or graphene fiber-based scaffolds (a), (b), (c) and

their bright field corresponding images (a’), (b’) and (c’). Images of DAPI

stained cells grown on thin film scaffolds for CB (d), CNF (e) and graphene

(f) and their respective bright field images (d’), (e’) and (f’)...... 133

Figure 5. 8. Cell density measured by counting DAPI+ cells grown on electrospun

fiber scaffolds (a) 24hr, (b)72hr and (c) 120hr after plating. (left side) and

thin film scaffolds (a) 24hr, (b)72hr and (c) 120hr after plating. (right side) ..... 135

Figure 5. 9. Relationship between the conductivity & concentration of the nano-

additive with PCL systems...... 136

Figure 5.10. Relationship between cell density and time of incubation with 1wt%

of (a) fiber and (b) thin film scaffolds ...... 136

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LIST OF TABLES

Table 3.1. Nanofibrous scaffolds with PLA [143]...... 68

Table 3.2. Young’s modulus and fracture of CB additives/PCL of composite

scaffold ...... 76

Table 3.3. Comparison of experimental modulus result with different existing

analytical models...... 80

Table 3.4. Homogenized Young’s modulus: comparison between experimental,

numerical and analytical results...... 84

Table 3.5. Young’s modulus and fracture strength for carbon additive/PCL fibrous

scaffolds...... 86

Table 3.6. Young’s modulus and fracture strength of carbon additive/PCL film

scaffolds...... 86

Table 4.1. The physical properties of CNF ...... 94

Table 4.2. The physical properties of carbon black(CB) & exfoliated graphite ...... 94

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LIST OF ABBREVIATIONS AND NOTATIONS

1D: One dimensional

AZT: Zidovudine

CB: Carbon black

CB: carbon black

CNF: Carbon nanofibers

CNTs: carbon nanotubes

–COOH: carboxylic acid cPE: crosslinked polyethylene

CTS: chitosan

DAPI: 4′,6-diamidino-2-phenylindole

ECM: cell’s extracellular matrix

ECM: extracellular matrix

FCNT: functionalized carbon nanotube

FDA: Food and Drug Administration

GEL: gelatin

GFOFER: Glycine-phenylalanine-hydroxyproline-glycine-glutamate-arginine

GFOGER: phenylalanine-hydroxyproline-glycine-glutamate-arginine

GICs: superconducting graphite intercalation compounds

GO: graphene oxide

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HA: hyaluronic acid

HA: hydroxyapatite

HDF: human dermal fibroblasts

HLE: human lens epithelial cells hMSCs: human mesenchymal stem cells

HUVECs: human umbilical vascular endothelial cells

MC3T3-E1: mouse osteoblast-like cells

MGO: Modified graphene oxide

MSCs: mesenchymal stem cells

MWCNTs or MWNTs: multi-walled carbon nanotubes

N6: nylon 6 nHAP: nanohydroxyapatite

NMS: nanofibrous membrane scaffold

NPs: apatite nanoparticles

PANI: polyaniline

PANI-GO: polyaniline/graphene oxide

PC12: rat pheochromocytoma

PCL: polycaprolactone

PDLLA: poly (D, L-lactide)

PEDOT: poly(3,4-ethylenedioxythiophene)

PEO: polyethylene oxide

PGA: polyglycolic acid

PGS: poly (glycerol sebacate)

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PHBV: (poly (3-hydroxybutyrate-co-3-hydroxy valerate))

PI: polyimide

PLA: poly (lactic acid)

PLDL: poly(l-lactide/dl-lactide)

PLGA: poly (lactic-co-glycolic acid)

PLGA: poly(lactide-co-glycolide)

PLLA: poly (ւ-lactic acid)

PMMA: poly (methyl methacrylate)

PP: polymer-oxidized polyprrole

PPF: Poly (propylene fumarate)

PPF: poly (propylene fumarate)

PPy: polypyrrole

PPyCOOH: poly(1-(2-carboxyethyl) pyrrole)

PTh: polythiophene

PU: polyurethane

PVA: polyvinyl alcohol

PVA: Polyvinyl alcohol

RGD: the peptide arginine-glycine-aspartate

SEM: Scanning Electron Microscope

SF: chitosan (CS)-silk fibroin

SLG: single-layer graphene

SME: SMPs with multiple shape memory effects

SMPs: shape memory polymers

SWCNTs or SWNTs: single-walled carbon nanotubes

TIPS: thermally induced phase separation

TMA: Thermomechanical Analysis

US-tube: ultra-short carbon nano-tube

VEGF: vascular endothelial growth factors

VEH: Valence Effective Hamiltonian

XRD: X-Ray diffraction

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CHAPTER I

LITERATURE REVIEW

Background

1. Tissue Engineering

The modern-day concept of tissue engineering became a part of mainstream medicine in 1987. The term combined the definition of “tissue” as “a collection of similar cells and the intercellular substances surrounding them” with the definition of

“engineering” defined as “the science concerned with putting scientific knowledge to practical uses.” When the concept of “tissue engineering” was adopted by the medical profession in 1988, it defined “tissue engineering” as “the application of the principles and methods of engineering and the life sciences toward the fundamental understanding of structure-function relationships in normal and pathological mammalian tissue and the development of biological substitutes to restore, maintain, or improve functions.” The definition of “tissue engineering” then became the basis for spawning off the specialized fields of biomedical engineering dealing with the physiology of tissues, bioprocessing engineering dealing with using cells and organisms in producing biochemical materials, and cell engineering dealing with the engineering of individual cells and in large part mammalian cells [1].

Over twenty-five years later, the definition of tissue engineering has evolved to be recognized as “the creation of new tissues for the therapeutic reconstruction of the human body, by the deliberate and controlled stimulation of selected target cells through a systematic combination of molecular and mechanical signals” [2].

The history of tissue substitution and engineering dates back to at least the sixteenth century (1564) when Ambroise Paré (renowned surgeon in the French military) described tissue replacement and substitution with prosthetic teeth, replacement noses and penile structures (called “artificial yards”) following amputation. In the mid to late 1800s,

John Hunter experimented with transplanting teeth in humans. This technique was common in England where the transplanted tooth acquired the name “scion-tooth.” To evaluate the viability of tissue transplantation as it related to acceptance of donor tissue by the host, Hunter experimented with transplantation of other tissue, for example, grafting cock testicle tissue into hen abdominal tissue. Some of the earliest attempts at xenotransplantation of tissue occurred due to sexual diminuendo in men and what is now referred to as erectile dysfunction. In the late nineteenth century, Charles Edouard Brown-

Séquard experimented on himself to attempt to “revitalize himself” which in the nineteenth century appeared to be akin to modern day Viagra or Cialis. Brown-Séquard’s version was a combination of dog and guinea pig sperm, testicular tissue and blood prepared as an injection. In 1920, Serfe Voronoff reported revitalizing hundreds of men for a duration of one to two years by grafting ape testicular tissue to the patient’s own testes. This paved the way for the development of skin grafting, the first mainstream application of tissue substitution and engineering [1].

2. Skin Grafts and Organ Transplants

Skin graft experiments were first conducted on the transplantation of feathers, hair and skin in Aves and Mammalian classes of animals by Friedrich Dieffenbach in the first part of the nineteenth century (1822). While Dieffenbach’s experiments with “free skin graft” failed in humans, he became known as a pioneer of modern-day plastic surgery with his use of “pedicled flaps.” During this time, early rhinoplasty was also being conducted by Christian Bunger and Guiseppe Barino. It wasn’t until 1870 that free skin grafts were first successful. Jacques Reverdin invented the concept of using only a small graft (about

5 mm wide) on “aseptic granulating surfaces.” Following Reverdin, Karl Theirsch used square-inch grafts secured with plaster-of-Paris dressings. Others worked at securing larger grafts for facial reconstructions. In this way, skin grafts evolved as the first medically used form of tissue engineering that is still advancing today, now typically using cadaver skin tissue or amniotic cell grafts. From tissue substitution and grafting evolved organ transplantation with Alexis Carrell taking the lead by developing his principles of

“vascular anastomosis” at the beginning of the twentieth century. The year 1902 marked the first experimental kidney transplant experiments in animals. However, successful

“whole-organ” kidney transplants did not occur until 1954 in Boston when one twin’s kidney was transplanted to another twin. Since then, nearly every human organ has been the subject of successful or at least experimental transplantation. Modern-day tissue engineering is dependent on cell culture technology, i.e. the ability to culture cells to promote and sustain cell proliferation. The possibility of being able to grow cells or have cell replication in vitro, was first conceived by Leo Loeb at the turn of the twentieth century

(1897). 3

This was followed by the growth of amphibian (frog) nerve cells in culture. Again,

Alex Carrel, in combination with Montrose Burrows, was instrumental in the proliferation of cell and tissue culture technology [1].

Introduction

Tissue engineering consists of ways that improve the regeneration of human cells and tissues which include manipulating either natural and/or synthetic materials to provide structural integrity and the necessary biochemical information to new cells including stem cells as they begin proliferating and differentiating into specific tissues [3].

Three approaches are normally used with tissue engineering. The first is infusion of isolated cells. The second is treatment with growth factors that promote cell proliferation and induce tissue growth; and the third involves implanting scaffolds. The implanted scaffolds can also be infused with tissue-specific cells and corresponding growth factors or even mesenchymal stem cells [4].

Tissue engineering usually requires three essential components for tissue to regenerate. The first and foremost essential element needed to engineer regenerative tissue is a “substrate.” While substrates can take on different forms, these substrates are most commonly referred to as scaffolds. However, scaffolds have also been referred to in literature as constructs, structures or templates. Most scaffolds are three-dimensional in nature [5].

1. Tissue Scaffolds

Scaffolds imitate and mimic the three-dimensional environment of a cell’s extracellular matrix (ECM). Scaffolds are necessary to provide the support that cells need for proliferation, which are made from synthetic or natural materials. They act as a framework and support for cell adhesion, proliferation and differentiation. Thus, it is necessary for scaffolds to have the required mechanical strength [6].

With scaffolds, cells are still able to maintain their inherent and innate phenotype.

Many diverse types of scaffolds have been constructed, fabricated and developed.

Scaffolds are normally classified according to their chemical nature; and can normally be divided into four classes: synthetic, metallic, protein-based or carbohydrate-based.

Requirements for all scaffolds include biocompatibility and biodegradability. The products of the biodegraded scaffold must be non-toxic byproducts. The biodegradability must also be able to be controlled with the reabsorption rate of the scaffold commensurate with cell growth, especially in vivo. Surface chemistry of the scaffold must also be considered. This is important for cell adhesion and cell attachment. Surface chemistry is also important for both cell proliferation and differentiation. The porosity of the scaffold is also a substantial consideration as pore size is key to cell growth, cell migrations and the transport of nutrients and waste products by the cell and in the extra cellular matrix. Thus, interconnectivity is also a key factor for these considerations [7].

Scaffolds essentially act as a matrix. They use biomaterials, namely ligand with integrins (cell receptors) to promote cell adhesion. They can also use alternate biomaterials that promote cell adhesion, such as certain biomaterials which attract and absorb adhesion

proteins. The adhesion proteins can then bind the cells. Scaffolds are often reinforced so that they can sustain the shape and form of the defective or injured site. This promotes the process of repair and reconstruction by forming a barrier. This barrier inhibits the growth and infiltration of foreign tissues which are not involved in the repair, reconstruction and regeneration processes [8,9].

To be safe and effective, scaffolds must meet certain requirements in composition, design and functionality. The materials used to construct or fabricate the scaffold or substrate must be biocompatible. Biocompatibility refers to the safety of the scaffold. The scaffold must be constructed or fabricated out of all non-toxic materials. Biocompatibility includes not using any materials or substances in the scaffold that would cause an inflammatory response or immunogenic reaction. For most applications, the scaffold should be constructed as a three-dimensional matrix. The three-dimensional structure must be relevant and coherent with the expected physiological environment in which it will be introduced. This is essential for cell function. The matrix should also exhibit high porosity, i.e. have void spaces. Highly porous scaffolds permit the infiltration of new cells into the matrix. High porosity also allows the infusion into and diffusion throughout the matrix of nutrients needed for cell proliferation. Additionally, high porosity is essential for the exchange of waste products.

Another requirement is that the surface properties of the scaffold must be bioactive.

Bioactivity is contingent on the surface chemistry and topography of the scaffold.

Bioactivity is necessary to promote cell adhesion and attachment. Bioactivity also improves the interactions between the surrounding tissue and the matrix.

This is especially important with synthetic matrices that are not inherently bioactive. Furthermore, the mechanical properties of the scaffold must promote appropriate mechanical behavior. This includes the ability to seamlessly integrate into the surrounding tissues. Mechanically, the scaffold must be able to avoid and withstand stress shielding which is one of the implant problem in hip joint that lead to bone less and revision surgery.

The scaffold must also be able to withstand [10] and exhibit anisotropy at the material structure which influence orientation of cells and ECM deposition. This is critical for the scaffold to function in a manner that can influence the orientation of new cells as well as formation and deposition of the extra-cellular matrix. Finally, the scaffold must be biodegradable; and the degradation rate must be such that the scaffold functions as a functionalized matrix [3,11-13].

Scaffolds can be categorized into two major groups. The first group is three- dimensional structures, also known as a “preformed matrix.” The second group is injectable matrices. The preformed matrix can be divided into non-fibrous and fibrous scaffolds. The preformed matrix can also be further divided into synthetic, inorganic and natural matrices. Fabricating non-fibrous scaffolds can be accomplished in a variety of ways to manipulate the morphology of the scaffold. These methods include electrospinning, gas-foaming and thermally induced phase separation (TIPS). Fabricating fibrous three-dimensional scaffolds that include structures like the extra cellular matrix can also be accomplished by a variety of methods. These include electrospinning, hydrogel, needling (non-woven) and self-assembly (Figure 1.1) [3].

Figure 1.1. Cross-sectional SEM micrographs of (a) non-ﬁbrous methods to manipulate micromorphology, (b) methods commonly employed to create 3D scaffolds exhibiting ﬁbrous structures with diameters on the order of native ECM [11].

Injectable matrices are comprised of compositions that are liquid at room temperature. When appropriately stimulated, the liquid gels or solidifies. Gelling or solidification can occur through a variety of processes, which include thermal gelation, ionic gelation, radical polymerization, photocrosslinking, and self-assembly. Hybrids exhibit characteristics of both a preformed matrix and an injectable matrix. These are known as 3D composite matrices (Figure 1.2) [3].

Figure 1.2. Injectable 3D-formed composite of β-TCP beads and alginate: (a) light microscope photograph of the composite, (b) SEM photograph of the composite, (c) SEM photograph of the composite surface. Bar is 1,000 µm in (b) and 100 µm in (c) [14].

As noted above, scaffolds can be made of organic (natural), inorganic (e.g. metallic) or synthetic materials. The selection of material depends on its final purpose. Moreover, scaffolds have barriers, gels or 3D matrices which mimic the extra cellular membrane of the desired tissue. Natural scaffolds utilize natural materials from human or xenogeneic sources (animals) [15]. The utilized extra cellular material may include agarose, alginate, chitosan, collagen, Matrigel®, intestinal submucosa and silk protein [16-19].

1.1. Hard Scaffolds

Tissue engineering of hard tissues, bone and cartilage require hard scaffolds that are designed and fabricated to exhibit the same or very similar characteristics as bone or tissue. Hard tissue scaffolds are 3D scaffolds that serve as a support structure. This support structure promotes cell adhesion, cell proliferation and differentiation to create healthy bone and healthy bone tissue that is capable of restoring functionality to damaged or injured tissue. Hard tissue scaffolds on load-bearing sites are long-term or permanent – not temporary; and they must retain their biological integrity, shape, and strength. Biological integrity must be retained throughout the regeneration process as well as throughout the

repair of the injured or damaged bone tissue.

Bone replacement hard tissue scaffolds for reconstructing and repairing bone defects must be biocompatible with surrounding tissue, and be easily shaped or molded so it can be easily formed into the exact size and shape of the bone defect. These hard tissue scaffolds must also be non- or hypoallergenic, non-immunogenic and non-carcinogenic.

They must also be radiolucent, trauma-resistant, maintain their strength and stability in the long term, and capable of maintaining their volume. Hard tissue scaffolds for bone repair must also exhibit osteoconductivity, meaning that they must be able to support and encourage bone growth, ingrowth and integration into the surrounding bone tissue.

Metallic scaffolds are prime examples of hard scaffolds. Biocompatible metallic scaffolds are used in reconstructing, regenerating and repairing bone. Unlike many of the other types of scaffolds, metallic scaffolds can provide a permanent structure and framework. This is useful for long-lasting repair of bone defects. There are various existing strategies and technologies for manufacturing and fabricating metallic scaffolds and various levels of biocompatibility of currently available commercial metallic scaffolds

[20].

Robotic dispensing referred to as “robocasting” has been utilized as a technique to fabricate hard scaffolds with very complex structure and architecture. This architecture includes shape, size and porosity. As discussed above, pore geometry is particularly important [21].

1.2. Soft Scaffolds

Soft tissue scaffolds rely on adipose tissue as a primary structure in restoration, reconstructive and/or augmentative soft tissue repair [22]. However, current scaffold materials for soft tissue repair fail to have optimal volume retention, experience cell death at the donor site, and have poor biocompatibility. Approaches based on stem cell technology to engineer human soft tissues such as adipose tissue using soft tissue scaffolds that have a shape and dimensions that are predetermined offer a solution to existing problems with soft tissue repair. Creation of biologically viable adipose tissue can be accomplished by utilizing the adult stem cells of a patient, proliferating them and then differentiating them specifically into adipose tissue through adipogenic differentiation.

This adipogenic tissue is then encapsulated into selected biocompatible polymer material.

In constructing soft tissue scaffolds in such a manner for implantation at the damaged tissue site, there is minimal trauma at the tissue donor site. This is because soft tissue scaffold implantation can use a very small needle size, possesses optimal immune compatibility because it is the individual’s own stem cells that are being use, and exhibits extended volume maintenance due to the stem cells’ ability to replenish adipogenic cells combined with the ability to retain the predefined shape and dimensions of the soft tissue scaffold.

However, there are still problems with extended volume maintenance, promotion of tissue maturation, angiogenesis, integration into existing soft tissue and then scaling up the process. Still, stem-cell based soft tissue scaffolds will be turnkey applications for plastic and reconstructive surgery [23].

The soft tissues can be repaired and restored by using the extracellular matrix- assisted tissue such as a natural source of prosthetic mesh material. Cook Medical’s

Surgisis® soft tissue graft provides the extracellular components which support the spread of new healthy tissue, recover the damaged site of tissue, and guide the healing response.

This prosthetic mesh material is more distinct than synthetic materials due to its ability to remodel tissue instead of scar tissue [24].

2. Materials Approach to Improved Scaffold

2.1. Biopolymer and Compatible Polymers

Synthetic polymers are commonly used for the fabrication of nanofiber scaffolds.

Numerous synthetic polymers have been explored for use as biodegradable materials for scaffolds. These include poly(lactic acid) (PLA), poly(lactic-co-glycolic acid) (PLGA), polycaprolactone (PCL), poly(methyl methacrylate) (PMMA), polyglycolic acid (PGA), and polyvinyl alcohol (PVA). Polymer scaffolds can be combined with growth factors cells. These polymer scaffolds have numerous applications, including regeneration of blood vessels (including coronary arteries), bone, skin, cartilage and even ear which is depicted in Figure 1.3 [4].

Figure 1.3. A few examples of tissue engineered scaffolds used in clinical tissue regeneration for: (a) diabetic foot ulcer, (b) ear reconstruction, (c) human mandibular reconstruction, (d) articular cartilage regeneration; (e) coronary artery regeneration [25,26].

Synthetic biopolymers are viable alternatives for biomedical uses and applications.

The synthetic biopolymers poly(glycolide), poly(d,l-lactide-coglycolide), poly(ւ-lactic acid), PCL, and PGA have received approval from the U.S. Food and Drug Administration

(FDA). The FDA has licensed these for in vivo use and applications. This makes these biopolymers easily available to use in fabricating tissue engineering scaffolds. Most biodegradable polymers that are biologically derived from natural sources will likely be biocompatible. PLA and PCL classified as aliphatic polyesters, and their copolymers have promising characteristics for biomedical applications because of their low toxicity, biocompatibility, biodegradability, and reabsorption properties [27,28].

PCL has been extensively researched and explored for use as scaffolds for tissue engineering. PCL is a hydrophobic, semi-crystalline polymer. Crystallinity decreases when the molecular weight of PCL increases [29]. PCL is soluble with a low melting point between fifty-nine to sixty-four degrees Celsius. PCL has excellent blending compatibility as well as excellent rheological and viscoelastic properties. There is widespread use of PCL for tissue engineering scaffolds [30]. PCL-based scaffolds have been used for tissue engineering and regeneration of many tissues including skin, bone, cartilage, tendons, ligaments, nerves and blood vessels. However, bone tissue uses are limited by PCL’s mechanical properties, which tend to be inferior in load-bearing capacities [31].

Poly(anhydride-co-imides) including poly[pyromellitylimidoalanine-co-1,6- bis(carboxyphenoxy) hexane], known as PMA-ala: CPH, has been studied extensively as a scaffold material for tissue engineering. PMA-ala: CPH matrices tested and compared with poly(lactic acid/glycolic acid) matrices in rat subcutaneous tissue, both recorded similar degradation rates in the period of 60 days [32]. Additionally, biodegradable polyphosphazenes have undergone widespread investigation for their biocompatibility in both in vitro and in vivo capabilities. Specifically, amino acid ester polyphosphazenes have superior osteocompatibility and are also good candidates for bone tissue matrices [33].

Synthetic biodegradable polyphosphoesters also have excellent biocompatibility. They also mimic or are similar to the natural structure of nucleic acid [28].

Polyanhydrides and polyurethane are also good choices for biomedical utilization due to their biocompatibility and biodegradability [28]. Aliphatic anhydrides have been in existence for nearly a century since they were first developed in 1932 [34].

The original use of polyanhydrides was for textile applications. Following widespread in vitro and in vivo testing on the safety and biocompatibility as well as the effectiveness of their drug delivery capability, the FDA approved aliphatic polyanhydrides as a drug delivery vehicle [35].

Polyurethane has also been explored extensively and evaluated for its superior biocompatibility and desirable mechanical properties [36]. Polyurethane has been investigated for use as longer-term and permanent medical implants. These include cardiac pacemakers and vascular grafts. However, there are some challenges in making and using synthetic biopolymers. Some may trigger immune responses and be immunogenic. It is difficult to make chemical alterations or modifications to these biopolymers. When chemical modifications are made, the modifications may inherently alter the bulk properties of these biopolymers. Functionalizing these biopolymers may solve some of these noted problems. Functionalization can be performed in diverse ways. One way is to introduce functional groups to the monomers of these biopolymers. The introduction of these functional groups is initiated in a protected form before polymerization and then deprotected after polymerization. A second method is to introduce functional groups to the polymer chains through additional chemical modification [28,37,38].

Poly(lactic acid), also called polylactide (PLA), is a thermoplastic aliphatic polyester. This polyester is derived from natural, renewable resources. The sources of these derivatives include corn starch in the United States, tapioca starch in Asia, and sugarcane in other regions of the world. Polylactide is biodegradable, especially in the presence of oxygen, but not recyclable.

Because it is biodegradable, PLA composites or blends would be good choices for nanocomposite material, fabricating scaffolds and biomedical applications. Many different forms of polylactide exist, all distinct in nature such as poly(ւ-lactic acid) (PLLA). PLLA is the product of polymerization of L,L-lactide (also called L-lactide). PLLA has distinct characteristics: 37% crystallinity; 60-65°C glass transition temperature; 173-178°C melting temperature; and 2.7-16 GPa tensile modulus. Further, PLLA can be heat-resistant to 110°C [39].

Fabrication of composite scaffolds using poly (ւ-lactic acid) and hydroxyapatite has also been evaluated in the engineering of bone tissue. However, the problem has been that these composite scaffolds have been shown to have inferior mechanical properties when compared with pure poly (ւ-lactic acid) scaffolds. This is due to the agglomeration of the various particles combined with the weak interaction of the interfacial component.

Previous attempts to correct these deficiencies in the fabrication of the poly (ւ-lactic acid)- hydroxyapatite composite included double sonication of the hydroxyapatite and/or raising the amount of the hydroxyapatite used. However, neither of these proved effective when it came to enhancement of the mechanical properties of the scaffold. In one study a hydroxyapatite combination was utilized, combining the hydroxyapatite with another filler, specifically mesoporous silica (SiO2) nanoparticles; adding 5% SiO2 nanoparticles to the hydroxyapatite nanopowder and then subjecting it to double sonication. Using mesoporous silica-hydroxyapatite reinforced poly (ւ-lactic acid) scaffolds did not result in any decrease in bioactivity [40].

Nanofibrous scaffolds can be comprised of polycaprolactone (PCL), collagen I and hydroxyapatite (HA) nanoparticles to enhance the adhesion and survival of mesenchymal stem cells (MSCs). This mixture is in the dry weight ratio of fifty percent PCL, thirty percent collagen I, and twenty percent HA nanoparticles (50% PCL: 30% col I: 20% HA).

A nanofibrous scaffold was fabricated by electrospinning using this mixture. Comparing the cytocompatibility of scaffolds fabricated with the PCL-Col-HA tri-component mixture with three other scaffolds, the three comparison scaffolds were electrospun scaffolds fabricated with (1) one hundred percent PCL; (2) one hundred percent collagen I; and (3) eighty percent PCL and twenty percent HA (bi-component 80% PCL: 20% HA). The tri- component bone-mimetic scaffolds demonstrated the most rapid cell migration/spreading and substantially great cell proliferation. This is due to the low tensile modulus of the tri- component material. The tri-component scaffolds also absorbed a significantly greater amount of fibronectin and vitronectin (the adhesion proteins) than any of the other types of scaffolds. This was true for both in vitro and in vivo (rat tibiae). The tri-component scaffolds also demonstrated increased levels of a specific marker indicating the tri- component scaffold’s potential to promote osteoblast survival and differentiation [41].

Three-dimensional scaffolds can be fabricated from these synthetic polymers in many ways. Fabrication can occur by freeze-drying, solvent casting, solid free-form fabrication, gas foaming, particulate leaching and even microsphere sintering. These techniques work well for producing a three-dimensional structure and porous scaffold which are necessary to promote cell adhesion and cell proliferation. However, 3D scaffolds fabricated with any of these techniques are still insufficient.

Fabrication according to these methods still cannot produce a scaffold with the necessary topographical features to mimic the needed extra cellular matrix [27].

2.1.1. Compatibility

An essential characteristic and prerequisite of biomaterials used for scaffolds is biocompatibility. Biocompatibility is defined as “the ability of a material to perform with an appropriate host response in a specific application” [42]. How a tissue responds in vivo after implantation depends on a wide variety of factors. These factors span the gamut from the physical properties to the chemical properties to the biological properties of the materials. Other factors that must be considered are the shape, size and physical structure of the implanted scaffold. The active biocompatibility of biodegradable materials must also be accounted for and evaluated over time. Long-term biocompatibility of permanent implants is also a principal factor [27].

A wide selection of natural polymers can be prepared from plant or animal sources.

These natural polymers include starches, soy proteins, chitin, cellulose, hemicellulose, alginates, polylactic acid, polyhydroxyalkanoates and many others. Natural polymers are a good source of polymers for scaffolds. Polymers from plant or animal sources are abundant, renewable, and biodegradable. Because they are natural sources, the likelihood of biocompatibility increases. Natural polymers have been extensively explored including the manufacture of natural polymer composites. Composites consist of the natural polymer combined with other polymers. These other polymers could be synthetic or another natural polymer. Composites also may include natural and/or synthetic fillers [39].

Biopolymers can be strengthened further by the addition and blending of elastomers. Different methods have also been used to improve compatibility and enhance the biopolymers’ advantageous properties. These methods include adding block copolymers. Block copolymers include diblock, triblock and other random copolymers such as PCL-PEG multiblock copolymer [43] as well as a PEO-PPO-PEO triblock copolymer [44].

2.1.2. Structural Properties

Three-dimensional biocompatible scaffolds can be modified to enhance the surface properties of the scaffold. Surface modifications can influence the adhesion and proliferation of mesenchymal stem cells (MSCs). The surface of the scaffolds can be modified by treating poly-C-caprolactone (PCL) nanofiber scaffolds with O2 plasma, forming p-PCL nanofiber scaffolds. In one study, aligned PCL nanofibrous scaffolds in one group and random PCL nanofibrous scaffolds in the other group were fabricated. Both were fabricated through electrospinning. Both groups had their surface modified by treatment with O2 plasma. The MSC cultures were then evaluated for their adhesion, morphology, proliferation, and interaction with the scaffold. The results showed that the increased quantity of cells grown on the PCL nanofibrous scaffolds in general were substantially higher (statistically significantly higher) than the non-nanofiber PCL scaffolds. Further, plasma-treated (p-PCL) scaffolds (whether random or aligned) showed greater MSC proliferation. However, when comparing the aligned nanofiber scaffolds with the random nanofiber scaffolds, the MSC proliferation on the random nanofiber scaffolds was substantially greater [45].

The structural properties of scaffolds are paramount in fabricating scaffolds that mimic the extra cellular membrane’s nanofibrous nature. To evaluate the extra-cellular matrix (ECM) of cartilage (and therefore for chondrogenesis), the nanofibrous nature of the ECM is defined in large part by the “size and depth-dependent alignment of collagen fibers within hyaline cartilage” [46]. By electrospinning hyaluronic acid (HA) fibers, the fabricated scaffold exhibits enhanced mechanical properties and increased cell adhesion properties. Specifically, this is due to the resulting intrafiber crosslink density and the peptide arginine-glycine-aspartate (RGD) density, as the migration, proliferation and adhesion (i.e. focal adhesion formation) of the studied human mesenchymal stem cells

(hMSCs) are dependent upon the RGD density. Electrospinning in this manner also affected the interactions of the hMSCs as well as gene expression in hMSCs [46].

3. Conductive Scaffolds

As a promising research field, conductive scaffolds play a pivotal role in harvested tissue for transplantation due to their higher electrical and mechanical properties, especially for nerve, cardiac and bone tissue engineering [47,48]. Conductive scaffolds are fabricated from polymers that are electrically conductive. The alternating π bonds in the backbone of conducting polymers produce a valence band of loosely held electrons, which is responsible for the electrical conductivity, which allows efficient transfer of charge carriers along the backbone chains [49,50]. In addition, the carbon additives approach is more recently used for constructing tissue engineered scaffolds to promote the regeneration of electroactive tissues [51].

The following discussion is based on the two general topics of conductive tissue scaffolds and the physical attributes of carbon additives. The conductive polymer approach discussed below focuses on the combination of conductive polymers and other polymers.

The carbon additive approach is a strategy that couples the advantageous properties of polymers with the carbon additives of graphene, carbon nanofibers and carbon black. The biopolymer and carbon additive combined approaches have become significant in both the engineering and biomedical fields where they are successfully used for many purposes.

The polymer and carbon additive combined approach is especially attractive for human health clinical implementation because of the capability of carrying out a variety of functions while taking up a very small amount of space. Finally, the attributes of carbon additives are divided into the sub-topics concerning the properties of conductivity, surface properties, cell viability, durability and mechanical processes.

3.1. Conductive Polymers Approach

Conductive polymers expanded to biomedical applications in the 1980s when they were used as biosensors due to their compatibility with biological molecules [52]. In the mid-1990s, the electrical stimulation of conductive polymers was used to modify cellular activities, including migration, adhesion, protein secretion and DNA synthesis [53,54]. Cell surface molecular reorganization was enhanced by fibroblast locomotion directed within an electric field [55]. Conductive polymer-oxidized polyprrole (PP) has been used to enhance the stimulation of neurite outgrowth [56]. Ozawa et al. developed an electrical environment to produce a stimulated DNA synthesis in an experiment on mouse osteoblast- like cells (MC3T3-E1) The mechanism was partially triggered by calcium ions [57]. Also,

A DC electric field provided the environment for human keratinocytes directed cell migration with Cyclic AMP-dependent protein kinase [58]. Li and Kolega realized that cell migration was successfully increased by applying direct current electric fields to bovine vascular endothelial cells; actin filament distribution was also modified [59]. By 2003, the conductivity of polymers was being investigated using electrical simulations [60].

Conductive polymers have been shown to positively affect damaged electro- responsive tissues of the nervous system, heart and brain [61]. Optical and electrical properties of conductive polymers are chosen above inorganic semi-conductors and metals because they are easy to produce [62].

Figure 1.4. Architectures for biodegradable conducting polymers [63].

The conducting part of structures that provide electrical charges is theorized to be at the tips of the degradable segments, consistently or randomly spread throughout the entire architectural structure (Figure 1.4) [63].

Conducting polymers provide an efficient means to support tissue engineering scaffolds, drug delivery devices, neural probes and bio-actuators due to their ability to deliver the electrical signal from an exterior source on the seeded cell, their biocompatibility, tunable conductivity, and environmental stability. Numerous conductive polymers such as polypyrrole (PPy), polyaniline (PANI), polythiophene (PTh), poly(3,4-

ethylenedioxythiophene) or PEDOT, and novel conducting polymers have been widely used in biomedical applications [54].

3.1.1. Polypyrrole (PPy)

The first conductive polymer that showed its effect on mammalian cells was polypyrrole [53]. PPy had a positive cell adhesion effect and resulted in growth of several cell types including nerve tissue [64], endothelial cells [65], rat pheochromocytoma (PC12) cells [66], keratinocytes [67] and mesenchymal stem cells [68].

The conductivity of PPy depends on the reduction and oxidation states of PPy to provide a reversible reaction as shown in Figure 1.5.

Figure 1.5. Polypyrrole reversible reaction [54].

PPy in the form of a tissue support substrate that exhibited conductivity was used in an experiment to enhance the growth of keratinocytes. The research showed that PPy has potentially significant importance for use as a biological tissue/cell support due to its functional properties [68]. Rat primary keratinocyte cultures were studied for their response to electrical stimulation made possible with a PPy substrate. Researchers developed electropolymerized PPy films on porous stainless-steel filters. The filters had a porosity of 120 µm. The experiments were repeated until an optimized PPy electrical

stimulation potential with respect to the cell culture media composition was accomplished.

Keratinocytes were seeded in tissue culture plates (which is not the common procedure).

After the seeded keratinocytes adhered to the tissue culture plates (5 to 6 hours), PPy films situated on stainless steel supports were placed over the cells. The outcome under 100 mV of electrical stimulation for 2 hours demonstrated an increase in cell viability by 20% [69].

Therefore, the general physical and chemical properties that make PPy suitable for tissue engineering are high conductivity, high stability in air, electroactivity pH, biocompatibility, lack of biodegradability and low solubility in water. Limitations that affect the use of PPy in tissue engineering have been identified as insolubility in organic solvents and that it lends itself poorly to some processes [70].

PPy is attractive in nerve tissue because it demonstrates cell compatibility and useful conductive properties [71]. Although many different strategies have been attempted, the lack of success for healing very small nerve problems continued until neural tissue engineering was undertaken. Examples are discussed at the end of the section where

PPy is combined with other PPy-type conductive polymers to develop improved tissue engineering uses.

The conductive materials PPy nanoparticles and polylactide were used to develop nanotubes by implementing biodegradable and conductive nanocomposite. The reversible reaction between the oxidation and reduction states leads to high conductivity (Figure 1.5).

A biodegradable composite was made from PPy and poly (D, L-lactide) (PDLLA). The composite preparation was produced using emulsion polymerization of PPy immersed in a

PDLLA solution. Fibroblast growth increased when electrical stimulation was applied with

DC current at medium intensity. The size of the composite membrane was 3.0×2.5×0.03 cm3 and contained 5% PPy at 100 mV [60].

3.1.2. Polyaniline (PANI)

PANI is the most important conductive polymer because its characteristics include a straight-forward polymerization process, reduction-oxidation properties, chemical stability, and good conductivity compared to other polymers. PANI is inexpensive and its applications are wide ranging [72]. One of the attractive attributes of PANI that stands out is its ability to be electrically switched between resistive and conductive states. Physical and chemical characteristics of PANI that make these conductive polymers attractive for tissue engineering are high conductivity, environmental stability, biocompatibility, lack of biodegradability and suitable redox properties. On the other hand, the limitations of PANI are low solubility in organic solvents and poor electroactivity below pH 4 [70].

The oxidation of PANI causes three different basic forms and the form depends upon the level of oxidation. The polymer with no oxidized groups, but fully reduced is called leucoemeraldine. The half-oxidized emeraldine base with fully oxidized PANI is called the pernigraniline base. The last form is the half-oxidized polymer (reduced units = oxidized units) in the emeraldine oxidation state and is commonly termed the emeraldine

PANI base. The oxidation level that is most significant is the emeraldine PANI base [72].

Researchers developed a notable method to reduce the electric deterioration of

PANI in tissue engineering applications. Damia Mawad et. al., doped PANI with phytic acid on the surface of a chitosan film for heart tissue to keep the dopant isolated in the

tissue scaffold [61]. A dopant “defines the properties of the polymer and allows its functionalization for a specific application” [73]. By isolating the dopant in the conductive scaffold, PANI’s brief time of electrical activity was prolonged. In fact, the electrical properties were improved to the point that no electric deterioration occurred [61]. The process adopted was to first dope the PANI with phytic acid on a chitosan film surface.

Chitosan film was chosen because the chelation reaction between chitosan and phytic acid is very strong. The reaction results in a conductive patch with the appropriate characteristics to use in heart tissue repair. The resulting material could sustain its electroactivity and exhibit a low surface resistivity of 35.85 ± 9.4 kilohms per square [61].

Incubation with heart tissue (the physiological medium) for two weeks produced an oxidized form. First, ex vivo experiments showed an immediate positive electrophysiological effect on the heart tissue. Next, in vivo, the generated tissue scaffold did not cause proarrhythmogenic heart activities. The research resulted in a “robust conductive system used at the interface with electro-responsive tissue” [61]. Therefore, the method of using PANI for heart tissue repair shows excellent properties to use with the improved interface developed in the research.

3.1.3. Polythiophene (PTh)

Polythiophene-based biomaterials as tissue scaffolds face the same electric deterioration challenge. PTh is reduced from air exposure and from reactions taking place during incubation with a cell culture medium [61]. As shown in Figure 1.6, PTh is a PPy heteroaromatic molecule of five-membered rings with heteroatoms that bridge the “C1 to

C4 atoms of the cis-polyaromatic backbone” [70]. Limiting mesomeric forms are either aromatic or quinoid. The aromatic and quinoid are not energetically equal. The heteroatoms highly influence the conjugated polymers’ band gaps and the quinoid forms’ higher aromatic stability. A band gap measurement is the Valence Effective Hamiltonian (VEH).

Researchers predict that as the band gap decreases, the contribution of the quinoid increases. The resulting activity at the molecular level is a competition for the confinement of π-electrons at two locations: chain delocalization and within the ring [70].

Figure 1.6. Polypyrrole-configuration heteroaromatic rings and heteroquinoid form [70].

3.1.4. Blend Polymers

One proposed use of PEDOT with PLLA is to bind drugs to cultured cells and tissues, and then take advantage of the ability to electrically stimulate the cells because of polymer properties. The capabilities of PPy and its related polymers PLLA and PEDOT were found to have a particularly high advantage due to versatility. Researchers hypothesized that conductive polymers allow for the connection of physical properties and applications like doping. The model for the drug release application was influenced by several factors [74].

Physical properties of the polymers that were most impactful were porosity, structure, mechanical properties and color. Doping concentration was linked to the type of

biological activity initiated and then to the release of the drug. Polymer functionalism, biocompatibility, and biodegradability are directly related to the tailored application.

Research has found that the most influential element is dopant choice [73]. The conduction function of polymers is the easiest level of modification. It is the level where material properties can be controlled before synthesis and after synthesis. Therefore, the conclusion of the research was that the significance of using conductive polymers in smart materials tissue engineering was a major factor moving the new generation of tissue engineering forward [73].

Guo et al. successfully fabricated an electroactive, porous and tubular scaffold with properties of non-cytotoxicity suitable for neural tissue regeneration. The scaffold was made from a hybrid of PCL hyperbranched, degradable and conducting co-polymer blends as shown in Figure 1.7. The scaffold was produced by controlling different feed ratios for a solution-casting/salt-leaching process. Tests showed the homogeneity of the distribution of interconnected pores, both on the surface and the cross-section. The scaffolds were measured for conductivity and showed the same conductivity as films of the same composition, when “the scaffolds were between 3.4×10-6 and 3.1×10-7 S cm-1”

[75]. Conductivity was found to be dependent upon the ratio of the hyperbranched degradable conductive polymer to the PCL. The films were doped with camphorsulfonic acid to provide a 30° contact angle with water, producing a hydrophilic surface. The scaffolds were tested for toxicity and found to exhibit no cytotoxicity. Therefore, the result was a fabricated scaffold with PCL that showed excellent potential for use in neural tissue repair [75].

Figure 1.7. (a) PCL non-conductive scaffold compared to (b) conductive scaffold with PCL [75].

PCL has been researched in copolymer configurations to find suitable applications.

Bose et al. reported biomedical polymers PCL and PLA exhibited reduced bioactivity compared to other polymers and low modulus. Therefore, the two conductive polymers are not suitable for bone regeneration projects [76].

When electrically stimulated, the PPy co-polymer PPy-PCL (PPy-poly(ε- caprolactone)) was shown to increase rat pheochromocytoma (PC12) cells with neurites compared to non-electrically stimulated PPy-PCL. The purpose of using co-polymers was to enhance nerve regeneration in PC12 cells [77].

The use of PPy with PDLLA (poly (D, L-lactic acid)) in a composite conducting nerve conduit proved highly successful. PC12 cells were used to seed the conduits and under conditions of 100 mV for 2 hours the neurite-bearing cells and median neurite length increased along with increases in PPy. The experiment showed a successful repair of rat sciatic nerves, which indicates exciting potential for PPy/PDLLA composite conducting conduit for applications in neural tissue engineering [71].

PPy is used as scaffolds to induce the healing of tissue (tissue regeneration) because of its electroactivity. PPy is often modified with biological moieties to improve the

interface between the tissue and the biomaterial. A derivative of PPy, poly(1-(2- carboxyethyl) pyrrole) (PPyCOOH), was found to be useful as a bioactive platform to enhance cell adhesion due to the –COOH carboxylic acid. Researchers have cultured human umbilical vascular endothelial cells (HUVECs) on films compose of PPyCOOH.

The films’ surfaces were also modified with the application of Arg-Gly-Asp (RGD) as a cell adhesive. The platform proved practical and demonstrated that PPyCOOH needs to be taken seriously for use in PPy composites. There are a variety of biological molecules that are bioactive conducting platforms. These can be used for targeted biomedical purposes

[78].

The conducting polymers, also known as electro-active polymers, that are generally considered for biomedical tissue engineering are PPy, PANI, PTh, and the derivative

PEDOT [70]. The electrochemical functions of conductive polymers are improved by doping, synthesis in one-step processes, choice of platform, and novel applications that have been described in the literature. PPy has a conductivity of 102 to 7.5×103

S cm−1 therefore it demonstrates a high electrical conductivity [79]. PPy is also easy to prepare and the surface can be modified easily [80]. A major research goal is to maintain electroactivity for the non-degenerate band gap ground states, which are often the focus of experiments. However, electrochemical synthesis can ruin the electric sustainability. Other improvements can be introduced such as the scaffold material chosen and controlling the electrical activity so that it is confined to the scaffold such as with doping. Overall, some compromises must be made to optimize conductive polymers for tissue engineering implementation.

In other words, conductivity must be balanced with functions including charge transport, process possibilities and stability [70]. The above discussion showed examples of how researchers are producing an optimal implementation of a conductive polymer for successful tissue engineering applications.

A complex experiment was developed to evaluate the practicality of using electrospun nanofibers (Figure 1.8). Hatamzadeh et al. found that fabricated electrospun nanofibers were appropriate for tissue engineered scaffolds. PEGs-b-(PTh)4/PCL were the basis for fabricating electrically conductive nanofibers for tissue engineering. After measuring the biological and physicochemical factors of the conductive nanofibers, they were found appropriate for scaffolds [81]. Poly (ethylene glycol) s-modified polythiophene and poly(ε-caprolactone) were the foundation of nanofibrous electrically conductive scaffolds [81].

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Figure 1.8. Conductive nanofibrous scaffolds composed of PEGs-b -(PTh)4 and PCL for tissue engineering [81].

3.2. Carbon Additives Approach

Tissue engineering employs extensive use of carbon meshes. Carbon meshes are prepared from carbon fibers and carbon nanotubes (CNTs). Carbon nanotubes came into existence in 1990 and have exemplary and unique properties. Nanotubes, due to their superior electrical, mechanical and optical properties, as well as their thermal conductivity and chemical stability, are useful in numerous engineering applications. Even a small amount of CNTs incorporated into polymers or polymeric materials enhances the mechanical and physical properties of the polymer and the electrical properties [82].

Inadequate dispersion of CNTs is one drawback. CNTs tend to form rope or bundle structures because of van der Waals forces. However, electrospinning CNTs provides for more optimal alignment of the CNTs in a polymer matrix. This is due to the high extension of the electrospun jet as well as the sink flow. CNT alignment following dispersion by electrospinning CNTs in a polymer solution can be predicted mathematically. Carbon nanotubes can be single-walled carbon nanotubes (SWCNTs or SWNTs) or multi-walled carbon nanotubes (MWCNTs or MWNTs). Examples of electrospun CNT-polymer composite nanofibers include: MWCNT-polyethylene oxide, MWCNT-polyvinyl alcohol,

MWCNT-epoxy resin, MWCNT-polycarbonate, SWCNT-polystyrene, SWCNT- polyurethane. Other alignment approaches such as chemical functionalization and wrapping also provide for better alignment of the CNTs in the polymer matrix. Aligned nanotube synthesis through deposition onto a substrate that has been chemically modified is an alternate approach [83].

Carbon nanotubes have superior mechanical properties needed for scaffolds.

Another drawback is that CNTs are not biodegradable. Extended use in vivo has yet to be evaluated. However, CNTs that have been functionalized, either by carboxylation or hydroxylation, are water-soluble. This means that these functionalized CNTs can be cleared from the body. This occurs through blood filtration and excretion through the renal system making them safe for use in tissue engineered scaffolds. Incorporation of biodegradable materials in making CNT composites was also found to enhance the carbon nanotubes. Carbon nanotubes also serve as superior substrates for cell growth and proliferation.

Substrates fabricated from either biocompatible SWCNTs or MWCNTs were utilized as platforms for the growth, proliferation and differentiation of nerve cells. MWCNTs have also demonstrated osteoproductivity. Osteoproductive material is a material that “can elicit both intracellular and extracellular cell responses at the material surface” [84]. When carbon nanotubes are added to PCL, the properties of the PCL show marked improvement and enhancement. This includes PCL’s conductivity, its mechanical properties, its gas barrier properties and its thermal properties [84].

Other studies have examined the use of carbon nanotubes with natural or synthetic polymers (nanotube composites) for use in tissue engineering aimed at creating artificial bone and regenerating bone tissue. Ideally scaffolds consisting of a small percentage of carbon nanotubes will mimic the characteristics and properties of the extracellular matrix

(ECM) found in bone tissue. The ECM directly affects cell differentiation, phenotype and cell migration. The ECM is also critical because of its three-dimensional structure. The three-dimensional structure not only provides support and tensile strength to the tissue, but it also provides a substructure for facilitating “cellular adhesion and handling, storage of growth factors, cytokines and chemokines, and signaling for morphogenesis and cell differentiation” [83].

When designed CNT-polymer nanocomposite for tissue engineering applications, it is important to evaluate the mechanical properties of these materials. Poly (propylene fumarate) (PPF) is a promising polymer for use as a CNT-composite material for use in scaffolds for tissue engineering. PPF is a biodegradable linear polymer. When composites are formed with low concentrations of SWCNTs, the SWCNT-PPF polymer matrix shows

significant increases “up to two- to threefold increase” in compressive and flexural mechanical properties when compared against PPF-only polymer matrices. The low concentration though must be less than 0.5wt% [85].

Research has shown that using carbon nanotubes is superior to trying to replace and integrate the ECM in the bone regeneration and bone tissue engineering process. Carbon nanotubes (CNTs) are viable alternatives because of their similarity to ECMs. CNTs are also able to interact with both ECM-specific proteins, osteoblasts, cardiomyocytes and neurons. Finally, carbon nanotubes may be able to be used with stem cells to control and direct stem cell differentiation [83,85].

Another alternative is using ‘water dispersible’ carbon nanotubes (CNTs) in bone regeneration that utilizes carbon-nanotube-reinforced scaffolds. Specifically, functionalized CNT-biodegradable polymer composite scaffolds have been developed and fabricated. These are useful for tissue engineering, and especially for bone applications.

There are several advantages of utilizing functionalized carbon nanotube (FCNT)-polymer composite scaffolds. These include enhanced mechanical strength, enhanced bio- mineralization and features that mimic the extra cellular matrix. FCNT-dispersed polymer scaffolds can also provide for delivery of osteo-specific factors to aid in bone growth.

Finally, the surface chemistry of the FCNTs can be adjusted by varying the type and quantity of the functional groups associated with the CNT, which permits ‘property turnability’ [86].

Several methods exist for fabricating hard tissue scaffolds, including fabricating biodegradable polymeric hard tissue scaffolds. The mechanical properties, including the

mechanical strength, of the polymeric scaffold can be improved by creating a composite material using multi-walled carbon nanotubes (MWCNTs). Specifically, water dispersible

MWCNTs and poly(lactide-co-glycolide) (PLGA) scaffolds can be used because they exhibit mechanical properties that are similar to that of human cancellous bone. Thus, fabrication of three-dimensional MWCNT-PLGA porous scaffolds can be accomplished at

3wt% MWCNTs. The in vitro results show desirable cell viability, cell proliferation and factor mineralization. However, the twelve-week in vivo study resulted in an inflammatory response. Yet the MWCNT-PLGA scaffolds did show significant increases in both compressive strength and modulus while also resulting in enhanced cell adhesion and cell proliferation [87].

One dimensional (1D) nanostructures are attractive for tissue engineering in the biomedical tissue repair area, because they have high porosity and large surface area to volume ratios. Carbon nanofibers allow easy adjustments to their properties, functions, and structures [88]. As the number of materials that can produce carbon nanofibers is increased, their high aspect ratio and easily manipulated fabrication techniques are properties that allow a broad range of designs.

Carbon nanofibers (CNF) in a composite with the polymer PLGA produces a suitable scaffold for bone tissue engineering. Using other polymers such as PLA, PCL and

(poly (3-hydroxybutyrate-co-3-hydroxy valerate)) PHBV do not work well for bone tissue scaffolds because they are hydrophobic. The problem arises during the inorganic phase of electrospinning bone tissue scaffold. In order to find a solution to the problem, the composite PLGA-CNF based scaffolds were developed by varying the amounts of PLA

and PGA in order to find the best ratio combination for the PLGA. The resulting implementation of the PLGA-CNF successfully encouraged cell proliferation and induced cardiomyocyte and neuroblastoma cell growth. The researchers concluded that PLGA-

CNF scaffolds were suitable for cardiac and neural tissue engineering [89].

Hybrid PVA in a conductive composite was produced with poly (vinyl alcohol)

(PVA)-graphene oxide (GO) nanofiber coated with poly(3,4-ethylenedioxythiophene)

(PEDOT) [38-40]. The purpose was to check the suitability of the scaffold as a super capacitor. The results were good. The measurement of capacity retention was 82.41% after

2000 CV, and then dropped 11.27% after 5000 cycles. The drop was caused by the electrode material shrinkage and swelling during charging and discharging [90].

“Carbonizing polyaniline/graphene oxide (PANI-GO)” composite and PANI nanorod arrays were successfully placed on either side of GO nanosheets. This resulted in a nano-porous 3D architecture made of N-doped carbon nanorod arrays. The nanorods were regular carbon materials grown on graphene and measured 100 nm long and 30 nm wide. The material was porous because of PANI chain decomposition. Due to large surface area and porosity, the addition of the nitrogen group has enhanced the ionic transport and the super capacitance of 3D carbon materials. The researchers provided a step-by-step hierarchal carbon material fabrication that was based on the conductivity of the polymers and graphene oxide. Future research will focus on high-rate electrode supercapacitor materials [91].

Polyvinyl alcohol (PVA) was one of the composite materials used to produce a fibrous scaffold with exceptional conductivity and extra-high toughness. These

characteristics are needed to build suitable neural constructs. The fibrous scaffold was built with hybrid graphene (Gr) nanosheets-sodium alginate (SA)/PVA graphene-alginate PVA

(Gr-AP). The novel composite when compared to the AP scaffolds was found to improve toughness 4-fold with a composition of 1 wt% Gr. The researchers found that the Gr-AP scaffolds contained “superior electrical and mechanical properties with PC12 cell interaction” on the scaffolds (PC12 cells were cultured onto the Gr-AP scaffolds). The positive results indicated a high potential for electrical simulation using the hybrid Gr-AP scaffolds for nerve regeneration [92].

3.2.1. Conductivity

Conductivity is critical to the scaffold’s ability to promote cell adhesion, proliferation and differentiation. Chitosan/nano-hydroxyapatite scaffolds have been used to demonstrate the effect of conductivity. Chitosan/nano-hydroxyapatite membranes used “grid-controlled constant voltage corona charging” to possess negative charges. The negatively charged membranes were evaluated to determine biocompatibility, the ability to induce osteogenesis, and the ability to induce osteogenic differentiation. The results of the study showed enhanced osteoblast properties on the negatively-charged chitosan/nanohydroxyapatite composite membranes when compared to the non-charged control membranes. Specifically, the negatively-charged chitosan/nano-hydroxyapatite composite membranes had increased cellular adhesion, cell proliferation and the capacity to promote cell differentiation [93].

Multi-walled CNT (MWCNTO-GO, 50%, w/w) oxides were used to prepare PDLLA scaffolds. The MWCNTO-GO was made with an oxygen-plasma functionalization attractive for tissue engineering. The results showed a large increase in PDLLA conductivity following an increase in MWCNTO-GO loading. The increase amounted to approximately 5 orders of magnitude. Moreover, PDLLA hydrophobicity was reduced after MWCNTO-GO integration, subtracting one of the disadvantages of PDLLA. Results also showed that PDLLA/MWCNTO-GO scaffolds promoted cell adhesion and reduced bactericidal activity [94].

Carbon-based fillers including carbon black, carbon nanotubes, graphene and graphene oxide have shown successful applicability with copolymers because they are amendable to electroconductivity control. These carbon-based materials are especially practical as fillers when compared to metal fillers because oxidation is not a concern. Metal fillers, when oxidized, form an insulation layer on the surface of the particles [95,96].

Conductive polymers and carbon-based fillers are beneficial for electrical conductivity processes in tissue engineering because the conductive polymers remain close to the fillers.

The filler is within the polymer matrix and forms conductive paths [97,98]. Therefore, conductive composites have mechanical characteristics and processing ideal for plastics.

Advantageous properties of hybrid composites made from conductive polymers and carbon black or graphene include, flexibility, light weight process capabilities, the absorption of mechanical shock without disruption, and low production costs [99]. These properties are better than in other fabricated composites.

An example of a conductive composite fabricated with non-conjugated polymers is the composite polystyrene and graphene with a loading of 2.5 vol% which showed good electrical conductivity. Fabrication was carried out by solution mixing and conductivity was 1 S/cm [100].

3.2.2. Surface Properties

The structural properties of scaffolds are enhanced by the addition of carbon nanotubes. Researchers have examined the morphology, porosity and mechanics of a porous scaffold before it is modified with multi-walled carbon nanotubes (MWNTs) and then again after modification with MWNTs. Carbon nanotubes are thought to be capable of changing or influencing the properties of a polymer matrix. These properties include the biology and physiochemistry of the polymer as well as its mechanical and electrical properties. In one study, bioresorbable polymers poly(l-lactide/dl-lactide) (PLDL) were used. PLDLs have been used to prepare nanocomposite scaffolds in two ways. The first method was using salt leaching and the second method was using a salt leaching-gas foaming combination technique. However, the salt-leaching-gas foaming combination technique proved to be superior to the older salt leaching alone method. The advantages included better mechanical properties and parameters which permitted better maintenance of the scaffold’s high porosity. Further, the combination technique is less complicated, allowing it to be accomplished more efficiently and within a quicker time frame. Finally, the modification of the scaffold with the MWNTs appeared to aid in increasing cell proliferation [101].

Multi-walled carbon nanotubes (MWCNTs) are useful for creating nanostructured matrices that have biomimetic features. To evaluate surface properties of scaffolds with

MWCNTs, MWCNT scaffolds were used and the cellular response to these structures was observed, with particular attention to the effects that could be attributed to the local topography of the structures. First, the MWCNTs were evaluated for their mechanical properties which resulted in a determination that the mechanical stability of the MWCNT- based polymer matrices was within the desired parameters. Next, the biocompatibility of the MWCNT matrices as well as the cell-matrix surface interaction were assessed.

Following incubation on the matrices, increased cellular activity was noted as well as cell- adhesion and cell-sensitivity to the nanostructured matrices. A discovery was made that the surface properties of a uniform, regular topography promoted cell adhesion and positively influenced cell behavior in relation to the matrices and more closely mimicked the extra cellular matrix [102].

Glycine-phenylalanine-hydroxyproline-glycine-glutamate-arginine (GFOFER) peptide modification of the surface and oriented topography by fiber alignment on nanofiber mesh scaffolds are useful in modulating, directing and positively affecting cell behavior. Surface properties of the structural orientation of nanofibers and the functionalization of their surface affect the differentiation and migration of human mesenchymal stem cells (hMSCs) in tissue engineered scaffolds. An in vitro study first examined the movement of hMSCs on nanofiber meshes into a cell-free zone. The study utilized mitomycin C treatment to accurately measure the extent to which proliferation was responsible for the migration of the cells.

The experimental group consisted of poly(ε-caprolactone) meshes with oriented topography. These meshes were created by “electrospinning aligned nanofibers on a rotating mandrel” [103]. The control group was randomly oriented meshes. Both groups of meshes were coated with a “triple-helical, type I collagen-mimetic peptide, containing the phenylalanine-hydroxyproline-glycine-glutamate-arginine (GFOGER) motif” [103].

The results of the study showed that when the meshes were functionalized with the

GFOFER peptide, it modified the behavior of the cells. This occurred with or without oriented topography. Functionalization with GFOFER peptide substantially enhanced the hMSC’s migratory ability, proliferation and its differentiation (osteogenesis). When combined with alignment, the oriented GFOFER meshes showed increased migration in the same direction as the aligned fibers [103].

Sonication can modify the surface properties of single-walled carbon nanotubes

(SWCNTs). Sonication is typically used to diffuse or disperse SWCNTs throughout an aqueous medium. This can be accomplished in different ways. The first way is by functionalizing the SWCNTs covalently with a strong acid. The second way is by functionalizing the SWCNTs non-covalently. Non-covalent functionalization uses dispersants that adsorb onto the surface of the SWCNTs while they are being dispersed.

Sonication is the normal method of inciting the dispersion. However, it was suspected that free radicals may form during sonication, which in turn would cause the SWCNTs to undergo covalent modification. The question arose then whether surface quality of

SWCNTs was compromised by sonication. When sonication effects on the surface modification of SWCNTs were examined, results indicated that SWCNT dispersion in an

aqueous medium using traditional sonication did not in fact cause any detectable covalent modifications when compared with SWCNT without sonication. However, if sonication were induced longer or at a higher frequency, then some, but still less than ten percent, of the surface quality is damaged by covalent modification [104].

Functionalized ultra-short single walled carbon nanotube composite scaffolds are very useful in tissue engineering in increasing the structural strength and structural compressive modulus of the scaffolds. In one study, three kinds of highly porous scaffolds were fabricated, each one made from a different material. The purpose of the study was to evaluate the effects of each material used and their respective relative porosity on each scaffold’s pore structure, the mechanical attributes of each and culture of bone marrow stromal cells. The first one was made using a poly (propylene fumarate) (PPF) polymer.

The second was made using an “ultra-short carbon nano-tube (US-tube) nanocomposite.”

The third was made using a “dodecylated US-tube nanocomposite (F-US-tube).” All the materials resulted in similar porosity and pore size. The interconnectivity through connections that were 20 μm or more for all the scaffolds was nearly one hundred percent of the pore volume. The compressive modulus and strength, as well as the off-yield strength of the F-US-nanotube nanocomposite scaffolds were greater about equal to the other two materials. The bone marrow stromal cells also attached and proliferated equally with all three different material scaffolds [105].

Binary-nano-carbon-polymer composites enhance the mechanical strength and load transfer of the resulting fabricated multi-walled nanotubes (MWNTs). The mechanical strength and load transfer of MWNTs are important because these are crucial in developing

advanced polymer composites. One study demonstrated that binary-nano-carbon-polymer composites would be useful for three-dimensional scaffolds for use in tissue engineering.

The enhanced mechanical strength and load transfer is attributable to the synergistic effects and cooperative behavior of the MWNTs and the single-layer graphene (SLG). The single- layer graphene alone (SLG composites) demonstrated compressive deformation and had less than desired mechanical strength and load transfer. Close examination of the formation of the MWNT-SLG mixture revealed that the MWNTs actually bridged two single-layer graphene plates together in the polymer composite. Thus, this revealed the nature of the synergistic effect producing enhanced structural properties [106].

The safety and efficacy of vascular endothelial growth factors (VEGF)-loaded multi- walled carbon nanotubes (MWNTs) composite scaffolds in repairing defects in the abdominal wall have been studied. Safety and efficacy were evaluated both in vitro and in vivo. MWNTs with VEGF are prepared by modified plasma polymerization treatment.

MWNTs can effectively transport VEGFs to cells or tissues in vitro because they have large surface areas and inter cavities. Thus, the VEGF-loaded MWNT composite scaffolds were implanted in rats. At intervals of 2 weeks, 4 weeks, 8 weeks and 12 weeks, the scaffold-containing tissue was examined. A composite made at 3% MWNT had lower cytotoxicity. This combined with an “appropriate release performance” [107] induced a higher rate of vascularization of the acellular dermal matrices in porcine (pigs). However, the study revealed that MWNTs still caused side effects that called the safety of use in vivo into question [107].

Graphene has a variety of general properties including magnetic, thermal, mechanical, optical, magnetic and electronic. Theoretically, graphene polymer composites should be compatible with tissue engineering applications, but their surface properties make it a challenge. This is because the natural surface properties are not amendable to “reliable manipulation of well-dispersed graphene” [108]. Researchers have worked to tailor graphene surface properties by applying surface treatments. As an example, Dai et al. focused on properties associated with the graphene-polymer matrix interface. The dispersion of graphene and the polymer in a matrix was improved using in situ polymerization. Modified graphene oxide- (MGO) based polyimide (PI) nanocomposites and graphene oxide (GO) demonstrated higher mechanical properties when compared to

GO/PI. The dispersion of MGO with higher homogeneity was greater than with GO/PI composites. Strong interfacial interactions were observed in both types of composites

[108]. After simulating the strong interfacial reactions, researchers suspected that the modification of the graphene by the introduction of polymer caused a flexible interface providing an “effective path for load transfer” [108]. For these reasons, graphene and biopolymer hybrids are a potential alternative with appropriate properties.

Biomimetic materials are materials that are developed to mimic materials in natural biology. Tissue regeneration research is using in situ 3D microporous nanocomposite scaffolds to heal bones. A simple reaction is needed, based upon a lyophilization post- hydrothermal reaction. The material produced by the reaction is a 3D porous scaffold that has suitable characteristics for repairing bone including apatite particle distribution that is similar to natural bone.

The material is characterized by a highly porous network structure; and thermal properties are appropriate as well. The material is made with apatite nanoparticles (NPs) that resemble bone [109].

The apatite nanoparticles are further developed with a simple freeze-drying post hydrothermal process. A hydrothermal reaction is used to cause the deposit of NPs within the chitosan (CTS) matrices. Next, freeze-drying is used to produce the necessary 3D architecture. The researchers observed that pore size and porosity of the compound structure were not influenced by the particle content or particle size of the CTS. The procedure allowed the compression modulus rates to increase two times higher than when working with CTS on its own. Not only that, but cyto-compatibility testing for the MC3T3-

E1 concentration of the pre-osteoblast cell line was advantageous over the pure CTS scaffold. This research demonstrated that nanocomposite 3D micro-porous scaffold is a potential means to improve bone tissue regeneration [109].

3.2.3. Cell Viability

Morphology and cell viability experiments were carried out to determine the behavior of hMSCs on different substrates. Two experiments were carried out to compare substrates using hMSCs cultured in normal stem cell medium. The second test was specifically looking at stem cell differentiation by culturing cells on the commonly used osteogenic media. The following polymer materials were included in the experiment: hMSCs grown on PET and PDS slides without graphene and hMSCs on graphene-coated glass slides and PET and PDS.

The comparison showed no difference in the rate of growth on different substrates, so cell viability was not impacted by graphene. The only observed difference was a lower cell viability measurement on the PET and PDS slides with or without graphene present [110].

Graphene enabled the scaffolds to exhibit biocompatibility with the hMSCs.

Fabrication of graphene scaffolds for tissue engineering is important for stem cell transplantation and for enhancing specific cell differentiation into bone, muscle, and cartilage. The acceleration rate can be increased with a controlled approach for implementing growth factors and osteogenic inducers [110].

Cell viability was increased when interleukin-10 conjugated electrospun PCL nanofibrous scaffolds were used for nerve regeneration. These scaffolds promoted macrophages for in vivo nerves. Peripheral nerve injury showed improved regeneration due to the role of macrophages, so promoting the growth of macrophages is a positive result. Interleukin 10 (IL-10) is a protein called cytokine that promotes healing because it enhances the macrophages to transfer to a healing state. The IL-10 was attracted to the nanofibrous scaffold. The pairing with nanofiber scaffolds demonstrated the capability of promoting cell viability [111].

3.2.4. Durability

Hybrid conductive polymer and nanoparticles were fabricated with the purpose of producing durable, high performance nanofiber scaffolds for bone tissue regeneration.

PVA was deposited in situ on electrospun nylon 6 (N6) single nanofibers in a thin layer

[112]. PVA was chosen for its hydrophilic properties.

The researchers hypothesized that PVA’s hydrophilic, good biodegradation and tissue-like elastic properties would improve in situ performance of electrospun nylon nanofibers. The chemical reaction between N6 nanofibers and PVA resulted in hydrogen bonding in a traditional melt-blending procedure. The hydroxyl groups on PVA lent themselves to modification for “attachment growth factors, adhesion proteins or diminishing immunogenic response” [112]. Researchers found that hydrogen bonding improved the crystalline properties of N6; and PVA increased the wettability of the N6 mat and improved cell adhesion of pre-osteoblast cells. This demonstrated that the 3D scaffold produced with a hybrid of PVA/N6 can potentially enhance bone disease therapies [113].

A multipolymeric scaffold consisting of PCL/ECL/CAP was produced as the base for a brain therapy delivery system. Nanoparticles of alginate material were dispersed throughout the scaffold. An optimal formulation of the delivery system resulted in good stability by integrating Zidovudine (AZT) among the nanoparticles. Delivery of the drug within the central nervous system improved with small nanoparticle diameter (~68.04 dm) while conductivity was -10.61mV. Harilall et al. [114] determined matrix erosion was slow in vivo because of the semi-crystalline polymers. The bioerosion rate was 14.4% after

30 days of implantation. Percent mass erosion was calculated using the following equation

푀° − 푀푡 Matrix Erosion (%) = ×100 푀° where M0 is the initial mass of scaffold and Mt is the mass of the scaffold at time t [114].

Earlier research concluded that this composite scaffold had pores that were small and evenly distributed.

The small pores helped to reduce penetration of water through the matrix of the polymer composite, resulting in a reduction in matrix erosion [115].

Carbon black (CB) is one of a variety of materials that has been implemented for improving the performance of shape memory polymers (SMPs). Ma et al. added carbon black nanoparticles to a crosslinked polyethylene (cPE) scaffold to produce a two-way

SMPs with multiple shape memory effects (SME). Before this experiment, 1-way SMPs were the only ones that had been well-studied. The experiment showed that CB in a low volume fraction was enough to exhibit beneficial results on 2-way SME cycles. A small decrease in crystallinity was observed when CB particles were added (the decrease was only from 21.3% to 15.7%) [116].

The researchers noted that the most significant measurement was the increase in the actuation ratio Ra. The actuation ratio was measured in step 2 of the cycle as shown in

Figure 1.9.

푅푎= (ε2 – ε1) × 100%

Strain fixity and recovery were measured to evaluate performance. At small loadings of

CB particles (0.5 to 1.0 vol%), Ra improved by more than a factor of 1.5. Meanwhile, earlier research on high loadings of CB at amounts >10% with polyurethane (PU) one-way

SMPs improved strain fixity but decreased the capability for shape recovery speed and decreased the shape recovery ratio [116]. Tensile modulus increased with CB during the amorphous state and allowed for highly-oriented crystal formation when cooling was undertaken under tension. However, other states besides the fixing state caused problems that interfered with durability [116]. 49

Figure 1.9. Behavior of a two-way SME. Note step 2 of the cycle is ‘fix’ which involves cooling at constant stress [116].

Cell Culture

To grow cells and regenerate, repair and restore tissue, scaffolds must promote and support cell proliferation and growth [117].

1. Cell Propagation

Modifying scaffolds to promote and enhance cell proliferation of tissue-specific cells as well as proliferation and differentiation of stem cells into tissue-specific cells have been examined.

In one study, scaffolds were fabricated from poly(glycerol sebacate)/collagen

(PGS/collagen) core-shell fibers using electrospinning. PGS was used for the core while

the collagen polymer was used as the shell. The authors also fabricated 100% collagen nanofibers by electrospinning as the control to compare with the core-shell fibers. A co- culture system was used, comprised of cardiac cells in one group and mesenchymal stem cells (MSCs) in the second group. This allowed for both positive and negative control groups. The co-culture system looked at proliferation of the cells and MSC differentiation into cardiac cells. To demonstrate differentiation, actinin and troponin were used as marker proteins. The results of the study demonstrated that use of PGS/collagen core-shell fibers in combination with a cardiac cell-MSC co-culture system enhanced cell survival.

Additionally, modification increased proliferation and enhanced MSC differentiation into cardiac cells. Using such fibers in a co-culture system such as this would allow for cardiac tissue engineering in a clinical setting [117].

Amelogenin is capable of augmenting cell proliferation when it is used as an additive to scaffolds fabricated through electrospinning for use in tissue engineering.

Amelogenin is a well-known enamel matrix protein. Developing enamel forms onto the amelogenin during cell proliferation and growth. Previously, amelogenin was used in periodontal and wound-healing studies and applications. Amelogenin can be obtained by extracting it from unerupted porcine (pig) tooth buds and added in the electrospinning process. By incorporating 5mg/ml of amelogenin into the electrospun scaffolds, the scaffolds showed enhanced cell proliferation properties. These included enhanced mechanical properties in both types of amelogenin scaffolds, increased mineralization of fibers in the amelogenin-poly(glycolic acid) scaffolds, and improved adhesion in the

human dermal fibroblasts in the poly(ε-caprolactone) scaffolds. Thus, addition of amelogenin during electrospinning of these two types of scaffolds can be beneficial [118].

Other modifications can also be made to augment cell proliferation. For example, incorporating nanohydroxyapatite (nHAP) inside a chitosan (CS)-silk fibroin (SF) nanofibrous membrane scaffold (NMS) provides a favorable microenvironment. A favorable microenvironment is one that more closely mimics the natural physiology of bone tissue. A favorable microenvironment is also one that promotes cell proliferation

(here, increased osteogenesis of the implanted cells) and differentiation of stem cells (here, human bone marrow mesenchymal stem cells (hMSCs) were used). Specifically, the quantity and location of the nHAP on osteogenesis and osteogenic differentiation of the hMSCs demonstrated a direct positive correlation between the degree and extent of differentiation of the hMSCs with the quantity of the nHAP. However, the location of the nHAP within the nanofiber did not appear to be a statistically significant variable. In vivo experimentation was conducted using CS/SF/30% nHAP NMS-seeded hMSCs implanted in nude mice. The results of these experiments showed that n-HAP CS-SF-encapsulated

NMS are useful for potential tissue engineering applications [119].

The aim of this dissertation is to enhance and evaluate the tissue scaffold using nanocomposites material by doping polymer onto nano-additives. Three different additives were applied which was carbon nanofiber, carbon black and graphene. These nanofillers have unique features of configuration, geometry, conductivity, mechanical properties and surface properties that encourage to study their behaviors with polymer and Cell growth.

CHAPTER II

MATERIALS AND CHARACTERIZATION

Materials

In this thesis work, the materials used are promising for biomedical applications.

These materials involve carbon nanofillers based on polymer nanocomposite with unique electrical and mechanical properties that can enhance and support cell regeneration. The polymer used was a biopolymer called polycaprolactone (PCL), (M̅̅̅̅w̅= 80,000) which was purchased from Sigma-Aldrich. Carbon nanofillers were graphene, carbon nanofiber

(CNF) and carbon black.

1. Graphene

Graphene is a single crystal with a honeycomb structure as shown in Figure 2.1.

Exfoliated graphite, used in this study, is produced from superconducting graphite intercalation compounds (GICs) by thermal shock or rapid temperature change

[120].

Figure 2.1. Illustration of Graphene structure [121].

2. Carbon Nanofiber (CNF)

Carbon nanofibers are also known as filaments. The first form of nanofibers was carbon fiber, which was prepared by carbonizing cotton and bamboo. In the 1879s, Thomas

Edison used carbon fiber as the filament of a light bulb, and it has been developed tremendously for both fundamental scientific research and practical applications [122,123].

CNF, contain graphene layers organized as piled cones, cups or plates in a cylindrical nanostructure. Catalytic decomposition of hydrocarbons can fabricate it on small metal particles. The catalytic particles controlled the diameter of the nanofibers through a growth process. Also, it can be formed of CNF and govern the degree of crystalline order by manipulating several parameters [124]. CNF in this study provided by Pyrograf Products

Inc. Figure 2.2 shows the morphology of CNF.

Figure 2.2. Carbon nanofibers.

3. Carbon Black

Carbon black (CB) is considered as oldest manufacturing materials, which referred to a range of industrial products including furnace, thermal, channel and acetylene blacks.

In 3rd Century Asia, the Chinese and Indians used carbon black as a pigment in the black ink. Carbon black application was growing and therefore gained its industrial market due to their extensive use as a filler in elastomers, plastic and paints to modify mechanical, electrical and the optical properties of materials [125]. Carbon black is usually formed by incomplete combustion process of heavy petroleum products. Carbon black is one of the para-crystalline carbon forms that is characterized by high surface-area-to-volume ratio

[126]. Carbon black consists of three fundamental properties which are particle size, structure and surface chemistry (Figure 2.3). The compilation of the small spherical particles chain is known as structure, and these structures include a carboxyl or hydroxyl group on the surface of carbon black [127]. Carbon black that we used in this dissertation is a high conductive (Vulcan XC 72R) powder obtained from Cabot® Corporation.

Figure 2.3. Carbon black structure.

Fabrication Method

The process of synthesizing a solution of nanofillers included dispersing the nanofillers by sonicating the solution (nanofillers and acetone) for two days. Then, the solution was stirred with 14 % wt of PCL solution at 65 °C. Finally, the PCL solution was prepared with acetone by stirring it under 65 °C for two hours maximum. In this dissertation, we used five different loads of (graphene, CNF and carbon black) nanofillers and employed two methods of fabricating the membranes: spin-coating and electrospinning.

1. Spin-coating

Spin-coating is a useful technique for depositing thin films onto substrates. During the spin coating, a uniform film (a few nanometers to a few microns in thickness) quickly forms on the substrate [128]. A typical spin process involves of a dispensing phase where the fluid is deposited onto the substrate surface at high speed and is then dried of excess solvent (Figure 2.4).

In this study, a thin film membrane with 7 to 10 micrometers thickness was deposited onto the square shape of the glass slide which stabilized it onto the device substrate surface by air suction (Figure 2.5). Minor amounts of PCL nanocomposite were applied onto the center of the glass slide, while the glass was spinning at 300 RPM for 90 seconds.

Figure 2.4. Spin-coating process diagram [129].

Figure 2.5. Spin-coating device

2. Electrospinning

Electrospinning is a process to produce fibers in which a solution in a pressurized nozzle is forced immediately into an electromagnetic field where a collector rapidly aligns the newly formed the nanofiber. The advantage of electrospinning is its ability to convert the solutions into fibers with diameters of up to ten nanometers through an electromagnetic field. This process makes it possible to manufacture solid, hollow or even porous fibers. In this dissertation, the fibers are made from PCL dissolved with carbon nano-additives in acetone. Electrospinning parameters for polymer-based nanocomposite were 24V, 5.1

AMPS of the DC motor. The distance between the syringe and the collector was 24 cm.

The jet speed was 0.07-0.17 ml/min. This process requires a safety cage due to the 15KV voltage used, and the very small dimensions of the fibers produced (Figure 2.6).

Figure 2.6. Electrospinning process diagram.

Materials Characterization

Materials characterization generally refers to the procedures used to measure the structure and properties of materials to help understand their behavior [130]. Many characterization techniques were used to describe and test the materials. The following sections describe these techniques.

1. X-Ray Diffractometer

X-Ray diffraction (XRD) is a unique non-destructive technique to identify the crystallinity of a material. It is used to measure and analyze the crystal structure, orientation, phase, average grain size, and crystal defects. It can accurately identify the

“fingerprint,” or atomic arrangement of the materials by knowing the peak intensities at different locations within the lattice. These peaks of XRD generated by constructive 59

interference of a monochromatic beam of X-rays diffracted at correct angles from each set of lattices d-spacing in a sample. A Rigaku X-ray diffractometer (Figure 2.7) was used in this study to characterize the crystallinity of the raw materials. The SmartLab software provided an enhanced flexibility to the researcher. Amongst its many functionalities, it was also able to change the optical configurations in short period of time as well as making easily automated alignments under the computer’s control.

Figure 2.7. X-ray diffraction machine [131].

2. Raman Spectroscopy

Raman spectroscopy (Figure 2.8) is a process that provides information about molecular vibrations which used for sample identification and quantitation. The performance involves shining a monochromatic light source or laser on a sample

(nanofillers) and detecting the scattered light’s wavelengths. Then, elastic scattering occurs when most of the scattered light is of the same frequency as the light source. The small amount of the scattered light which does not reflect the same frequency of the source can be due to interactions between the incident electromagnetic waves and the vibrational energy levels of the molecules in the sample. Plotting the frequency of the "altered" light

versus frequency of the laser results in a Raman spectrum of the sample. On scales in respect to the laser’s frequency, “the band positions will lie at frequencies that correspond to the energy levels of different functional group vibrations.” [132].

Figure 2.8. Raman spectrometer (Renishaw inVia Raman microscope) [133].

3. A Scanning Electron Microscope (SEM)

The scanning electron microscope (Figure 2.9) operates a focused beam of high-energy electrons to generate multiple signals at the surface of solid samples. The signal which resulting from electron-sample interactions reveal information about the sample including external morphology, crystalline structure, chemical composition, and orientation of materials making up the sample. Also, it is capable of performing analyses of selected point locations on the sample; this approach is especially useful in qualitatively or even semi- quantitatively determining chemical compositions, crystalline structure, and crystal orientations (using EBSD) [134].

Figure 2.9. The phenom ProX desktop scanning electron microscope (SEM) [135].

4. Thermomechanical Analysis (TMA)

Thermomechanical analysis (TMA, Q400, TA Universal) was used to test the mechanical properties and measure the thickness of the thin films and fibrous membranes

(Figure 2.10). TMA was adjusted on the standard mode, film/fiber probe, 50.01 ml/min sample purge flow, 0.06 to 0.49 N force load, 30-50 °C heating rate temperature and 8 mm sample size.

Figure 2.10. Thermal mechanical analysis.

5. Electrical Conductivity

The conductivity of the thin film of PCL nanocomposites based on carbon nanofillers tested by using a two-probe method with copper electrodes and a KEITHLEY

2700 multimeter/DATA acquisition system.

6. Fluorescence Microscope

We used Nokia fluorescence microscope (MF53) to provide an image of DAPI stained human lens epithelial cells (HLE) which grow on the fiber and thin film scaffold

(Figure 2.11) representing cell density.

Figure 2.11. Fluorescence microscope [136].

7. MATLAB and ImageJ Software

MATLAB software used to study the numerical simulation and model the electrical conductivity of the thin films. Also, ImageJ software was used to measure and analyze cell density.

Cell Culture

We used transformed Human lens epithelial (HLE) cells of the B-3 line provided from American Type Culture Collection (ATCC). The protocol of cell culture includes thawing and sub-culturing procedure which is described below.

1. Thawing Procedure for Frozen Cells

A vial containing the frozen cells was incubated at a 37°C in a water bath with keeping the O-ring and cap out of the water to avoid any contamination for approximately

2 minutes. After the contents of the vial thawed, the vial was sprayed with 70% ethanol.

From this step on all operations were performed under strict aseptic conditions. The cells were transfer to pre-warmed media and centrifuged at approximately 125 x g for 5-10 minutes to remove the cryoprotective agent. Cells were resuspended in Eagle’s Minimum

Essential Medium EMEM (ATCC® 30-2003™) with 20% concentration of Fetal Bovine

Serum (FBS) (ATCC® 30-2020™) and transferred to a 75 cm2 tissue culture flask. The cells were incubated at 37°C and 5% CO2 in air atmosphere.

2. Flask Cultures Procedure

After the seeding process, the cells were monitored for cell attachment, growth and possible of microbial contamination.

3. Subculturing Procedure

The cells were subcultured by separating the cells from the dish using the enzyme

Trypsin for less than 30 seconds. The process was repeated for 60 seconds at room temperature. Complete growth medium was then added to neutralize the trypsin and the contents were placed in a centrifuge tube. The contents were centrifuged at approximately

125 x g for 5-10 minutes. The medium and trypsin were aspirated and new media was added to resuspend the cells. At this time, the cells were ready to culture on biomaterial scaffold.

CHAPTER III

MECHANICAL PROPERTIES OF CARBON NANO-ADDITIVES/POLY(Ε-

CAPROLACTONE) BASED TISSUE SCAFFOLDS

Introduction

The research over several decades has found that increasing polymer mechanical properties are observed with increasing carbon nano-additive content

[137,138]. Fracture resistance of carbon nanofiber (CNF)/epoxy composites increased 66% and 78% as a result of the addition of 0.5 and 1.0 wt% CNF, respectively [138]. An increase in microhardness of CNF composites correlated with increasing CNF content when using the mixing method. The results showed that epoxy matrix microhardness increased by 53%

(at 0.5 wt% CNF), 62% (at 0.75 wt% CNF) and 100% (at 1.0 wt% CNF). The high modulus strength and high aspect ratio of CNF was responsible for hardness enhancement [139].

The effect of CNF geometry is complex and studies of the association between fibers and fillers are not consistent. Therefore, no clear conclusions have been drawn about the relationship of CNF geometry to mechanical properties. On the other hand, general knowledge can be ascertained from the CNF-matrix interfaces, because they highly influence the properties of CNF-modified composites. CNF/polymer interfaces have been

found to influence the final properties [140].

Carbon additives can be incorporated in medical applications efficiently. For instance, nanofibers are practical for neural tissue engineering because they allow the necessary mechanical support for nerve regeneration scaffolds, while simultaneously inhibiting non-neural cell growth. For example, scars which are caused by non-neural cell growth are depressed by CNTs; meaning that CNTs lower the risk of scar tissue formation

[141]. To boost the mechanical properties of scaffolds, fiber size and nanocomposition should be optimized. Research reported that the bending Young’s modulus increases as the fiber diameter of polymeric nanofibers decreases. Furthermore, the type of nanofiber materials, whether single materials or composite, can affect the mechanical properties.

Biljana et al. testified that the nanofibers based on polyvinyl alcohol (PVA) and polyethylene oxide (PEO) demonstrated reduced bending Young’s modulus indicating increased elasticity. The increased elasticity is a property needed for wound and skin repairs. However, nanofiber based on polyethylene oxide/chitosan (PEO 400K/CS) was stiffer which consequently makes it a suitable candidate for bone, tendon, and cartilage tissue scaffold engineering [142].

Cartilage tissue engineering was used to develop polymer substrates with

PLA nanofibers that had been modified with carbon nanotubes (CNTs) and gelatin (GEL).

The product was fibrous membranes produced by the electrospinning method. The hybrid fibrous membranes were constructed from PLA and gelatin nanofibers; CNTs-modified

PLA nanofibers; and pure PLA-based nanofibers. The electrical and mechanical properties of the PLA, PLA+CNT and PLA+GEL microstructures were contrasted and compared.

The PLA+CNT demonstrated the highest values for tensile strength and Young’s modulus as shown in Table 3.1. The highest electrical resistivity was measured for the PLA showing a value > 1015 Ωm, whereas the PLA+CNT measured 6.7 Ωm; and the PLA+GEL did not measure any electrical resistivity. The results demonstrated a promising potential for tissue engineered scaffolds to be successfully used for repairing cartilages [143].

Table 3.1. Nanofibrous scaffolds with PLA [143].

Tensile Strength Young’s Modulus Electrical Resistivity Type (MPa) (MPa) (Ωm) PLA+CNT 8.8 ± 0.7 461 ± 39 6.7 PLA 1.8 ± 0.4 178 ± 14 >1015 PLA+GEL 6.2 ±0.3 375 ± 22 -

Scaffolds can be fabricated as 3- and 2-dimensional shapes and can mimic the human body’s natural substrates; bones, cartilage and muscles [144,145]. Graphene is one of the 2-dimensional structures which possessed particularly attractive properties such as the highest Young’s modulus of any material and flexibility [146].

One promising candidate to fabricate composite scaffold is poly(ε-caprolactone)

(PCL). This precursor is hydrophobic, and it can provide excellent mechanical strength when invested in a composite nanofiber. Researchers produced collagen/PCL composite to enhance cell attachment and differentiation. Zhang et al. fabricated a core-shell structure of collagen-coated PCL nanofibers (Collagen-r-PCL) and a collagen-coated PCL nanofibrous matrix using a coaxial electrospinning technique and soaking process, respectively. As a result, both scaffolds showed extreme suitability for cell proliferation.

In addition, the cell morphology of human dermal fibroblasts (HDF) density on the

Collagen-r-PCL nanofiber membrane increased more than collagen-coated PCL by 10%.

[147].

Characterization of composites can also be made by means of analytical and numerical methods. Analytical methods can be divided into two groups including the well- known Voigt and Reuss (VR) bounds, Hashin and Shtrikman’s bounds [148], and third order bounds [149] in order to bound the properties and direct estimations of Mori-

Tanaka’s theory. The objective of the mechanics of microstructures is to derive the physical properties and the local fields and deformation of composite specimens from the knowledge of the nature of the constituents, their distribution, and their constitutive laws.

Bergstrom and Boyce [150] modeled the CB aggregates as squares or dodecaedron in an elastomeric matrix and as the union of CB spherical-shaped particles by Naito et al. [151].

In Laiariandrasana et al. [152], a composite model was also obtained from periodic homogenization by placing a spherical CB particle at the center of a tetrakaidecaedron cell.

A 3D morphological model was used by Jean et al. [153] in order to estimate the effective elastic modulus of a polymer with CB fillers based on large-scale finite element (FE) computations. The addition of CB to polymer leads to significant improvements in the physical and mechanical properties of composites. Djebara et al. [154] were interested in modeling the elastic modulus of polymer nanocomposites reinforced with rigid particles using numerical homogenization techniques based on the FE method. The elastic properties of the studied microstructure were obtained with different boundary conditions which included the effect of particle concentration and their distributions. Several references were very relevant to the modeling approaches of CB filled polymer composites [153,155,156].

All these published works have shown the need for a three-dimensional microstructural model that took into account the interaction between aggregates and the interaction of CB fillers with the polymer. In this dissertation, the effect of CB nano-additives on the mechanical properties of nanocomposite scaffolds was studied experimentally and numerically. The fraction of CB particles in the mixes varied from 0% to 10 wt%. The modeling methodology was based on a 3D numerical homogenization technique with the help of finite element, while the theory of bounds and direct estimations were used to carry out the analytical approach. The 3D modeling took into account the three phases: CB particles, aggregates and PCL matrix. The experimental, analytical and numerical results were compared for various CB concentration.

Materials and Experimental Methods

A mixture of polycaprolactone (PCL) and carbon black made using spin coating were used to make the film scaffolds.

The characterization of the morphology of the carbon black is shown in Figure 3.1.

Using dark field imaging, we can observe that carbon black consists of spherical nanoparticles in which these particles are arranged in the form of an onion-like structure

[157]. These particles have an average dimension of 300 nm.

Figure 3.1. Dark field imaging shows the morphology of carbon black (left image) and its onion-like structure (right image) [157].

Scaffolds were prepared by mixing 14 wt% PCL and carbon black. Five different weight percentages of carbon black were dispersed in 5 ml of acetone and were ultra- sonicated for 2 days. Following the ultrasonication process, a solution of 0.644 g PCL and

5 ml acetone was stirred at a temperature of 65°C for 2 hours. Then, a spin coater method

(Speed line P2604 Technologies) was used to produce a PCL/carbon black thin film scaffold using a spin speed of 3000 rpm for 90 seconds.

In addition, scaffolds based on carbon nanofillers were prepared with PCL using the same solution process. Besides the spin-coating method, we used electrospinning to fabricate fibrous scaffolds using a syringe pump (New Era Pump Systems, Inc. NE-300), voltage controller (Stanford research systems, Inc. Model PS375), rotator (Dayton® DC

Motor, 4Z145), rotator controller (Mastech, HY3010E), a syringe (30 mL Luer-Lor™

Syringe, BD), and a 17# needle. The voltage between the needle and the collector was 15 kV with a feeding rate of 0.003 mL/min, and a rotator speed of 5.7 m/s.

Results

The evaluation of the mechanical properties is important especially in biomedical applications. The mechanical properties can control the performance of the biomedical tool such as a scaffold. A scaffold based on CB can provide excellent mechanical properties superior to those of polymer scaffold. This work examined the mechanical behavior of different specimens of scaffold reinforced with CB rigid particles. Figures 3.2, 3.3 and 3.4 show the tensile stress curves for various concentrations of CB thin film scaffolds. After comparing between the distinct concentrations of CB additive with PCL, scaffold composites with 7% concentration showed higher strength than other concentrations and pure PCL. In fact, an incorporation of CB in polymer mixes improved the mechanical properties of the composites.

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4 0 wt% CB 3.5

2.5

1.5 Stress (MPa) (MPa) Stress 1 Series2 Series3 0.5 Series4 0 0 0.1 0.2 0.3 0.4 Strain (mm/mm)

4 1 wt% CB 3.5

2.5

1.5 Stress (MPa) (MPa) Stress 1 Series2 Series3 0.5 Series4 Series1 0 0 0.1 0.2 0.3 0.4 Strain (mm/mm)

Figure 3.2. Typical stress-strain curves for 0% and 1wt% CB obtained during the experimental tests on film scaffold for 3 and 4 samples each.

4 3 wt% CB 3.5

2.5

1.5 Stress (MPa) (MPa) Stress 1 Series2 Series3 0.5 Series4 Series1 0 0 0.1 0.2 0.3 0.4 Strain (mm/mm)

4 5 wt% CB 3.5 3 2.5 2 1.5

Stress (MPa) (MPa) Stress 1 Series2 Series3 0.5 Series4 Series1 0 0 0.1 0.2 0.3 0.4

Strain (mm/mm)

Figure 3.3. Typical stress-strain curves for 3 and 5 wt% CB obtained during the experimental tests on film scaffolds for 4 samples each.

3 7 wt% CB 2.5

1.5

1 Series2 Stress (MPa) (MPa) Stress Series3 0.5 Series4 Series1 0 0 0.1 0.2 0.3 0.4 Strain (mm/mm)

3 10 wt% CB 2.5

1.5

1 Stress (MPa) Stress Series2 Series3 0.5 Series4 Series1 0 0 0.1 0.2 0.3 0.4 Strain (mm/mm)

Figure 3.4. Typical stress-strain curves for 7 and 10 wt% CB obtained during experimental testing on film scaffolds for 4 samples each.

Increasing CB nano additives in the polymeric matrix showed an obvious enhancement in mechanical properties. The averaged Young’s moduli were determined.

These values correspond to the average Young’s modulus for all tested specimens. Table

3.2 presents a measurement of modulus and fracture strength of the scaffold as a function of CB additive concentration. Seven wt. percent CB concentration has the highest modulus

(101.25 MPa) and fracture strength compared to the other concentrations. The 10 wt% has the smallest averaged Young’s modulus (58.7MPa). Figure 3.5 shows the relationship of modulus versus additive concentration. After adding CB particles to the polymeric matrix, an increase in the modulus value was noticed until a threshold was reached at 10 wt%.

Beyond 10 wt%, a decrease in the modulus occurred. Adding 7 wt% CB into the composite scaffold resulted in a 64% improvement in Young’s modulus. Then, when the concentration changed from 7 to 10 wt%, a sharp decrease in modulus occurred (5% reduction).

Table 3.2. Young’s modulus and fracture of CB additives/PCL of composite scaffold

CB (wt%) Young’s Moduli Standard Gain Ultimate Stress Variation (MPa) Deviation (%) (MPa) (%) 0 61.8 9.92 0 2.21 0 1 65.2 9.01 +5.50 2.74 +23.98 3 80.7 24.32 +30.54 1.86 -15.84 5 87.6 20.43 +40.75 1.77 -19.91 7 101.3 27.68 +63.83 2.8 +26.70 10 58.7 2.97 -5.02 2.40 +8.60

140

120

100

Modulus (MPa) Modulus 40

0 PCL 1% CB 3% CB 5% CB 7% CB 10% CB

Figure 3.5. The relationship of modulus vs. additives concentration for film scaffolds.

Once the experimental characterization of CB filled polymer composites was completed. A numerical study was performed using two approaches: (1) an analytical modeling of CB/PCL using existing analytical models and bounds, and (2) a numerical homogenization method of these samples using finite element method (FEM). We have focused on the multiscale analysis of the homogenized elastic moduli through knowledge acquired from the mechanical properties of each phase: CB, PCL and their distributions.

The elastic properties of the PCL matrix were computed experimentally and also for CB properties; published data were used [153]. For CB particles, the Poisson ratio is usually taken as 0.3 and the Young’s modulus is 80,000 MPa. A comparison was carried out between the experimental data and the obtained results from the analytical and numerical homogenization techniques.

1. Analytical Modeling of CB/PCL Elastic Moduli

Various analytical homogenization methods can be found in the literature [156].

The popular existing approaches will be assessed in the isotropic case namely: the Mori and Tanaka model [158], the Smallwood [159] and Guth-Gold [160] models, the first-order bounds of Voigt and Reuss, the optimal bounds of Hashin and Shtrikman [148], and the third-order bounds [149, 161]. Using these models, elastic properties of CB/PCL are determined by knowing those of each phase, “m: PCL matrix” and “i: CB inclusion”, and

“p” CB volume fraction.

1.1. Analytical bounds for CB/PCL modelling

The mechanical properties of composites can be bounded from physical information of the constituents. The more common bounds are Hashin and Shtrikman's

(HS) based on the volume fraction of components and 3PB. In practice, it is difficult to obtain useful and exact results beyond the 3OB. The expressions of these bounds are:

Hashin Shtrikman Bounds [148]

  p  kkHS m  1/(ki k m )3(1   p )/(3 km  4 m )  (1) 1 p kk   HS i  1/ (km k i )  3 p / (3 ki  4 i )

Third-order Bounds (3OB) [149, 161]

3OB are the most sophisticated analytical models for estimations of elastic, thermal and electrical properties of spherical particle reinforced polymers. They depend on the properties of two phases, the filler volume fraction, the particle shape and their distribution and on the morphological function ζ1. These bounds were initially proposed by Beran and

Molyneux [13]; Milton [161] and summarized by Toquato [162]. These bounds are valid for multiphase media, and more generally, for elastic properties of random two-phase materials with overlapping spheres. Analytical expressions are highlighted in the references [161, 163].

HS and 3OB models obviously propose to calculate the bulk and shear moduli. It should be pointed out that to derive Young’s modulus, Equation (3) is used.

1.2. Direct Analytical Estimation

The direct analytical models, adapted for rigid spheres, used in this investigation were presented by Equations 4 and 5, respectively, represent the Smallwood (S) [159] and

Guth-Gold models (GG) [160]. It well known that Mori–Tanaka’s model and the generalized self-consistent estimates (GSCE) [164] cannot give a good prediction for the case of composites with particle agglomeration [165].

ESmallwood E m (1 2.5 p ) (4)

2 EGuth Gold E m (1  2.5 p  14.1 p ) (5)

The evolution of the homogenized Young’s modulus vs. CB volume fractions were studied.

Table 3.3. illustrates the comparison between analytical models and the experiment data for volume fraction ranging from 0% to 10%.

For different concentrations of CB aggregates, it appears that the experimental

Young’s modulus values systematically lie between the HS and 3PB bounds, which agrees with the homogenization theory. It also appears that for lower concentrations, existing models closely match the experimental data except the HS+. Beyond a proportion of 10%, the experimental values decrease; this limit corresponds to the percolation threshold. Aside from the effect of aggregate size, the physico-chemical phenomena could be the cause of poor model estimation for large CB fractions.

Table 3.3. Comparison of experimental modulus result with different existing analytical models.

Mass Volume fraction fraction HS 3OB- S GG Experimental test 3OB+ HS+ (%) (%) 0 0 61.80 61.80 61.80 61.80 61.8±9.9 61.80 61.80 1 0.6 62.53 62.60 62.73 62.76 65.2±9.0 64.43 302.67 3 1.82 64.03 64.24 64.61 64.90 80.7±24.3 81.27 795.68 5 3.06 65.59 65.97 66.53 67.34 87.6±20.4 113.95 1302.92 7 4.32 67.23 67.77 68.47 70.10 101.3±27.7 163.08 1824.93 10 6.25 69.80 70.66 71.45 74.86 58.7±2.9 269.80 2637.68

Evaluations of the elastic properties of CB polymer composites can be obtained by means of several analytical methods. These models obviously converge when the volume

fraction of particles or the contrast between the properties of phases is small. Otherwise, a notable difference was observed. Note that, an alternative way of solving CB/PCL homogenization problems consists of applying numerical methods.

2. Numerical Modeling of CB/PCL Elastic Modulus

Regarding the numerical techniques, the homogenization problem was solved using simulations on samples of microstructures for which the representative volume element

(RVE) plays a key role. The RVE is defined as the volume of CB/PCL composite material that contains a sufficient amount of CB particles.

2.1. Generating and Meshing of the Model

To model the structure of a polymer with carbon black fillers, Jean et al. presents various kinds of models [166]. According to Honglei et al., particles randomly placed in a composite domain suffice to give an accurate prediction [165]. El Moumen et al. show that an RVE of 50 rigid spheres is the minimum size to give a realistic estimation [167, 168].

Figure 3.6 (a) shows microscopic morphology of CB-filled PCL polymer matrix.

Qualitatively, this morphology illustrates that the microstructure of CB/PCL contains three scales. These scales are: the scale of the PCL matrix, the scale of aggregates, and the scale of CB particles. The CB spherical particles have a mean radius of 300 nm. The union of set particles creates aggregates. Looking at the morphology, it seems that the distribution of CB is homogeneous with some aggregates. To model with precision this microstructure, all of these morphological parameters are needed.

In our computation, 1,000 CB particles are randomly implanted in PCL domain with the possibility of interpenetration of coating in order to create a clustering phase (or aggregates) (Figure 3.6 (b)). The algorithm of implementation has already been described in our several works, El Moumen et al. [169], and proposed by Digimat-FE software.

Figure 3.6 (a) shows the microstructure of PCL containing 10% CB fillers. This RVE clearly reveals the multiscale microstructure of this composite with three scales: spherical particles, the aggregates, and the PCL matrix. A zoom in on the aggregate phase is presented in Figure 3.6 (c) This phase is obtained by overlapping spheres.

(a) CB randomly distributed (b) A simulated micro- (c) A zoom in on the in PCL polymer matrix structure with 1,000 CB aggregate phases particles

Figure 3.6. Microstructures of CB/PCL composites.

Several techniques are available to mesh a microstructure within the FE method. In the present work, priority has been given to create a FE mesh that follows the microstructure interfaces and constituents: particles, aggregates and matrix (Figure 3.7).

This is called the conforming meshing technique [153, 168, 169]. Digimat-FE software is

used with 324133 tetrahedral elements taking into account internal coarsening and curvature control of aggregates. We have also defined how finely the curved edges are discretized by defining chordal deviation ratio in the software.

Only PCL matrix Only CB rigid spheres CB/PCL matrix

Figure 3.7. Meshes of microstructures used for numerical simulations.

2.2. Comparison of Experimental Data with Analytical and Numerical Approaches

A simple uniaxial test, in adopting the tension boundary conditions, was applied to the generated microstructures of CB/PCL. The homogenized Young’s modulus was determined with the help of FEM. The numerical results obtained for various particle concentrations are displayed in Table 3.4 and compared with experimental data and analytical models. As expected, these results increase when increasing the CB concentration and more closely match the experimental data for lower fractions. The maximum difference between numerical and experimental results is found in the case of high CB fractions starting at 7%. But taking into account the standard deviation of experimental data, it appears that the results are in good agreement. Methods for estimating mechanical properties are based on the micromechanics interaction of composite

constituents. In the case of CB scaffold composites, there is also a chemical interaction between the rigid particles and the PCL matrix. This chemical interaction does not take into account analytical and numerical approaches.

Table 3.4. Homogenized Young’s modulus: comparison between experimental, numerical and analytical results.

Mass Volume Fraction Fraction HS 3OB- S GG FEA Test 3OB+ HS+ (%) (%) 0 0 61.8 61.8 61.8 61.8 61.8 61.8 ± 9.9 61.8 61.8 1 0.6 62.5 62.6 62.7 62.8 62.6 65.2 ± 9.0 64.4 302.7 3 1.8 64.0 64.2 64.6 64.9 64.4 80.7 ± 24.3 81.3 795.7 5 3.1 65.6 65.9 66.5 67.3 68.3 87.6 ± 20.4 113.9 1302.9 7 4.3 67.2 67.8 68.5 70.1 69.7 101.3 ± 27.7 163.1 1824.9 10 6.3 69.8 70.7 71.5 74.9 72.8 58.7 ± 2.9 269.8 2637.7

3. Mechanical Behavior of Nano-Additives/PCL Nanocomposites.

Young's moduli and the fracture strength of graphene and carbon nanofiber have been demonstrated also. Results of these nano-additives had a trend similar to carbon black.

This part of the dissertation examined the mechanical behavior of different scaffold nanostructures of nano-additives as a function of structure and geometry. Loading additives into the polymeric matrix showed an obvious enhancement in moduli. Figures 3.8 and 3.9 show the relationship between modulus and additive concentration for the fibrous and film scaffolds, respectively. Whether it is a fiber or film scaffold and nano-additives type, after loading additives into the polymeric matrix there is an increase in modulus until a threshold is reached: 1 wt% for the fibrous scaffolds and 7 wt% for the film scaffolds. After which,

there is a noticeable decrease in modulus. Also noted was a gradual increase in modulus from carbon black to CNF to graphene.

220 Graphene 200 CNF 180 CB 160 140 120 100 80 Modulus (MPa) Modulus 60 40 0 0.25 0.5 0.75 1 2 Concentration (wt%)

Figure 3.8. Elastic modulus vs. additive concentration for the fibrous scaffolds.

Graphene 145 135 CNF 125 CB 115 105 95 85 75 Modulus (MPa) Modulus 65 55 0 1 3 5 7 10 Concentration (wt%)

Figure 3.9. Elastic modulus vs. additive concentration for the film scaffolds.

Tables 3.5 and 3.6 show measurement results for elastic modulus and fracture strength of the fibrous and film scaffolds as a function of carbon additive concentration and geometry. Graphene had the highest value of modulus and fracture strength compared to CNF and carbon black. The highest moduli noted occurred with 1% (224.5 MPa) and

7% (146.8 MPa) graphene concentration for fibrous and film scaffold, respectively.

Table 3.5. Young’s modulus and fracture strength for carbon additive/PCL fibrous scaffolds.

Additive/PCL Graphene CNF Carbon Black Modulus Ultimate Modulus Ultimate Modulus Ultimate Concentration % Stress Stress Stress 0 44.7 3.3 44.7 3.3 44.7 3.3 0.25 87.1 9.6 69.4 5.8 50.1 6.9 0.50 141.2 9.5 76.3 4.6 63.6 6.5 0.75 158.8 8.9 94.1 4.2 70.3 4.9 1 224.5 8.5 180.3 4.0 92.8 4.5 2 73.5 3.3 66.7 3.0 46.1 4.5

Table 3.6. Young’s modulus and fracture strength of carbon additive/PCL film scaffolds.

Additive/PCL Graphene CNF Carbon Black Modulus Fracture Modulus Fracture Modulus Fracture Concentration % (MPa) (MPa) (MPa) (MPa) (MPa) (MPa) 0 61.8 2.2 61.8 2.2 61.8 2.2 1 77.7 3.2 71.5 1.2 65.2 2.7 3 106.8 3.8 88.4 2.7 80.7 1.9 5 122.8 2.4 108.1 1.3 87.6 1.8 7 146.8 1.4 117.2 1.3 101.3 2.5 10 87.4 0.8 60.6 2.8 58.7 2.4

Figure 3.10 shows the tensile stress curves of carbon black, CNF, and graphene for fibrous scaffolds and thin film scaffolds, respectively. After comparing the distinct types of carbon additives with PCL, the graphene/PCL nanocomposite showed higher strength

over the other additives and pure PCL in both the fibrous scaffold and the film scaffold.

4 PCL Stress (MPa)Stress CB-PCL 2 CNF-PCL Graphene-PCL 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Strain

PCL Stress (MPa)Stress 1 CB-PCL CNF-PCL Graphene- PCL 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Strain

Figure 3.10. Typical stress-strain curves for CB, CNF, and graphene obtained during experimental tests on fibrous scaffolds (upper) and film scaffolds (bottom).

Discussion and Conclusion

Carbon black (CB) spherical particles were added to poly(ε-caprolactone) (PCL) polymer to produce strong synthetic tissue scaffolds for biomedical applications. The objective of this work was to study the mechanical behavior of CB/PCL-based nanocomposites using experimental tests, multi-scale numerical approaches, and analytical models. The mechanical properties of CB/PCL scaffolds were characterized using thermal mechanical analysis and results show a significant increase in the elastic modulus with increasing nanofiller concentration up to 7 wt %. This negative effect occurred because of the formation of aggregates. Carbon black’s natural tendency for agglomeration in polymeric matrices consequently decreases the mechanical properties [149]. This is a major problem because of stress concentration around the inclusions and defect areas.

Finite element computations were performed using simulated microstructure and a numerical model based on the representative volume element (RVE) was generated.

Thereafter, Young's moduli were computed using a 3D numerical homogenization technique. The approach takes into consideration CB particle lengths, their random distribution, and agglomerations into PCL. Experimental results were compared with data obtained using numerical approaches and analytical models, and good agreement was observed, especially in the case of lower CB fractions.

Mechanical testing verified the effect of adding carbon additives to polymeric matrices. Results showed the following: that graphene and CNF had the same trend in mechanical behavior as carbon black with increasing concentration; and that graphene- loaded membranes had the highest mechanical strengths followed by CNF and carbon

black. This is due to several factors including graphene’s structure, its small and strong carbon-to-carbon bonds which prevent thermal fluctuation from destabilization, and the length of its carbon bonds (0.142 nm). Furthermore, because graphene is highly elastic, it has the ability to retain its initial size after force release [170]. The reason for mechanical failure in the membranes that contained graphene concentrations greater than 1 wt% was because of breaks in intralayer crosslinks [171]. In the case of CNF, increasing the amount of CNF weakened mechanical strength due to CNF bundles that had a certain amount of inherent defect densities based on size. Therefore, increasing the amounts of CNF bundles increased the number of voids and defects that negatively affected density. This was a major problem because stress concentration increased around the defects under loading which resulted in low strain capability and premature failures [137]. Lastly, carbon black’s natural tendency to agglomerate in polymeric matrices led to decreased mechanical properties as carbon black concentration increased [172].

CHAPTER IV

INTELLIGENT DESIGN OF CONDUCTING NETWORK IN POLYMERS

USING NUMERICAL AND EXPERIMENTAL APPROACHES

Introduction

Carbon nanomaterials exhibit extraordinary electrical, thermal, optical and mechanical properties because of their special allotropic forms. Carbon black shows relatively low electrical conductivity due to their onion like concentric structure [173].

Carbon black is used for a variety of conducting applications such as electromagnetic shielding [174], UV absorption [175], antistatic applications [176-178]. Conversely, carbon nanofiber (CNF) and graphene are made of graphene layers which is ether lamella or cylindrical; both exhibit high electrical, thermal and mechanical properties. Carbon nanofibers is made using chemical vapor deposition with seed catalysts and reactive temperature above 600C. Depending on the thermodynamic conditions, such as time, temperature, gas concentration and catalyst type, the nanofiber configuration structures vary from Dixie cup, fish bone, Bamboo, twisted or spiral [179]. These various carbon nanofibers have been used for battery electrode [180], chemical absorption [181], nanocomposite reinforcement [182], thermal management and conductive nanofillers

[183].

In contrast, graphene is made using two methods ether chemical vapor deposition or electro-chemical methods. Both lead to theformation of lamella platelets. The thickness varies between one to several graphene layers. This material is used extensively in a variety of applications such as electronics [184,185] chemical absorption [186,187] nano composites [188] and energy harvest [189-191]. As a nanofiller, graphene is a promising material to enhance the physical properties of polymeric nanocomposite. As an alternative to the traditional conjugated polymer, carbon nanomaterials can be a good candidate as a nanofiller to enhance polymer conductivities [192,193]. CNFs, carbon black and graphene have been widely studied in this article. There have been different studies showing that there are various percolation threshold values and conductivity levels. The conductivity of the isothermal annealed polypropylene plates had threshold and conductivity differences based on the addition of Carbon black (threshold conductivity of 10-7 S/m at 0.12%) and multi-wall carbon nanotube (threshold conductivity of 10-5 S/m at 0.015wt%) [194].

Munoz et al and Skakalova et al studied the conductivity of SWCNT based polymer nanocomposite [195,196] they obtained the same electrical conductivity value (104 S/m) but at different concentration (75wt% and 13.5wt%). These conflicting results might be caused by several factors such as nanofillers’ dispersion, shape, size, aspect ratio, orientation, and concentration. With the development of supercomputers and new algorithms, the simulation method became a powerful method to solve scientific [197,198] and engineering problems [199,200]. In the last few decades, numerous modeling and simulations had been developed to predict physical properties of carbon nanocomposite.

Chunyu et al used the Monte Carlo method to verify that the tunneling resistance played a critical role in the electrical conductivity of carbon nanocomposite [201]. Besides the basic

parameters, a novel morphological model developed by Takuya Morishita et al., which provided a glimpse into the role of aggregation in nanocomposite [202]. Additionally, the

Florent et al. established carbon nanotube (CNT) based conductive network with a 3- dimensional multi-node method [203]. Those modeling simulated a real phenomenon in a

CNT based nanocomposite. The CNTs appear to be entangled with each other and form a network. Great improvements have been made which helped researchers to develop a better understanding of how the CNT forms a conductive network in a polymer matrix. However, most of the previous models considered the nature of the materials as an important parameter, fewer studies are concerned with the effects of the manufacturing process. One significant factor caused by the manufacturing process is the degree of dispersion or aggregation of nanofillers in the polymer matrix. The agglomeration morphology of carbon nanotube has been described as a fractal geometric structure [204]. The megahertz detection property of a SWCNT coupled with Sierpinski antenna was investigated numerically and experimentally. The experiment showed the SWCNT array to be a promising structure for bolometer [205]. Yu-Chun et al. used the fractal analytical approach to study the surface properties of the modified multi-walled carbon nanotube

[206]. Yajun Yin et al. represented the design fractal of super carbon nanotubes with strict self-similarities depending on the geometric conditions and described the fractal dimensions of the super carbon nanotubes [207]. Haibao Lu et.al studied the improvement of the electrical properties of the polymeric matrix by incorporating with carboxylic acid functionalized CNT and carbon fiber [208]. The conductive carbon- based fillers combined with the polymeric composite was useful for electrical actuation [209]. Conductive network is widely used in sensors for small molecular detection [210-212], pressure [213]

and temperature [214] detection. The use of carbon nanomaterials had a significant advantage because of their light weight and low concentration and their potential of functionalization with additional surface molecules. Generally, four processing methods were used in sensor fabrication: spin coating [215], deposition [216], casting and electrospinning. All these methods are used today in industries to make electronics [217], bio-sensing and bio-medical scaffolds [218]. In this study, an experim ental approach will be carried out to study the conductive behavior as a function of nanofiller type, concentration. With the help of numerical simulations an aggregation parameter will be developed to study the effect of nanofiller dispersion. Two basic polymers will be used and thin film membranes will be prepared using the spin coating method with a variety of concentration of carbon nanotube, carbon black and graphene. In addition, this article will include the significance and effect of aggregation of the nanofillers.

Materials and Experimental Methods

1. Materials

PAN white powder (acrylonitrile-co-methyl acrylate copolymer, acrylonitrile content 94%,

M̅̅̅̅푤̅=100,000) was purchased from Scientific Polymer Inc. and used as received without any further purification. Polycaprolactone (PCL), (M̅̅̅̅w̅= 80,000) was purchased from

Sigma Aldrich. The carbon nanofiber (CNF) was provided by Pyrograf Products Inc.

Physical properties are shown in Table 4.1.

Table 4.1. The physical properties of CNF

Average bulk density of CNF (g/cm3) 0.019-0.048 Nanofiber wall density (g/cm3) 2.0-2.1 Nanofiber density (including hollow core) (g/cm3) 1.4-1.6 Average catalyst (iron) content (ppm) <14,000 Average outer diameter (nm) 125-150 Average inner diameter (nm) 50-70 Average specific surface area (m2/g) 65-75 Total pore volume (cm3/g) 0.140 Average pore diameter (Å) 82.02

Graphene was exfoliated by thermal shock or rapid temperature change of the intercalated graphite compound, which was previously described [219]. High conductive Carbon black

(CB) is Vulcan XC 72R, Cabot®. The Physical properties of carbon black and exfoliated graphite are shown in Table 4.2. The solvents used in this study are DMF (N, N- dimethylformamide) and acetone. Before mixing with polymer, we have chosen either shear mixing (IKA® shear mixer, T25 digital, Ultra Turrax), sonication (Bransonic® 5800 sonicator) or both.

Table 4.2. The physical properties of carbon black(CB) & exfoliated graphite

Bulk density of CB (g/cm3) 0.02-0.38 Density of CB (g/cm3) 1.7-1.9 Particle size of CB(nm) 300 volume conductivity @23C of CB (Ohm-cm) 1.9 Surface area of small exfoliated graphite(m2/g) 16.02 Surface area of medium exfoliated graphite (m2/g) 15.61 Surface area of large exfoliated graphite (m2/g) 15.35

1.1. Preparation of PAN Nanocomposite

In order to obtain a well-dispersed and homogeneous mixture of CNFs and PAN in

DMF, several significant steps were implemented. In order to prepare a 10wt% mixture of

CNFs to PAN by weight, 50mg CNFs were dispersed into 5mL DMF solution, and then, ultra-sonicated for 2 days. After 2 days of sonication, 0.5g PAN powder was added to 5 ml

DMF solution and stirred while maintaining a temperature of 65°C. A homogenous solution was obtained and remained stable for weeks without any aggregation or precipitation. A Speed line P2604 spin coater (Speedline Technologies) was used for fabrication. Spin coating parameters for PAN based nanocomposites were set at 1000rpm for 90 seconds. The thin film was transferred to a 70°C oven in order to remove the solvent.

The aim of this step was to avoid the porous or sponge structure during the drying process

[220].

1.2. Preparation of PCL nanocomposite

14wt% of PCL of acetone solution was prepared at 65°C and then mixed with carbon nanomaterials which was similar to the process described above. Spin coating parameters for PCL based nanocomposites were set at 3000rpm for 90 seconds.

1.3. Preparation of mixtures for the “cocktail” approach

We mixed two different nano-additives based polymer nanocomposite which is CNT and carbon black using the same processes described above.

2. Characterization

The thickness of all the samples was measured by a thermal mechanical analysis (TMA, Q400, TA universal) at room temperature (~23°C). Conductivity was tested by using a two-probe method with copper electrodes and a KEITHLEY

2700 multimeter/DATA acquisition system. A Phenom Desktop SEM (Pro X,

Phenom) was used to characterize the morphology of nanofillers and samples.

Raman technique (Renishaw in-Via Raman Microscope, 633nm laser) was used to characterize the raw materials.

3. Numerical Method

The first step is to reconstruct the 3D geometry of the nanofillers and the network inside the polymer. The second step involves analyzing the network and its properties. This simulation will focus on junction resistances between nanofillers, assuming that the conductivity is mainly dependent on the quantum tunneling effect.

The length of the tunnel junction, the thin layer of non-conductive polymer, is the parameter that determine if the nanofiller is connected to the network. Some assumptions have been made for the simulation. The first assumption is that the nanofillers cannot cross each other or cross the considered volume. The second assumption is that the junction resistance will be the only resistance taken into account for the resistance of the network. Since CNF shows the highest conductivity value then its resistance is ignored. Finally, CNF geometry is represented as a cylinder with a hemisphere at its extremities.

The diameter of the cylinder will be 300 nm. The length of the CNF is randomly set in a range of 15 to 30µm. The Carbon Black geometry is represented as a sphere of

300nm.

In order to calculate the resistance of a junction, it is necessary to calculate the minimal length between two nanofillers. The three outcomes using this simulation are the distance between two CNFs, between two carbon blacks and between one CNF and one carbon black. In the case of the two CNF’s, the minimal distance was calculated by minimum distance function (Eq. 1).

a, b, u, v, S, T ∈ ℝn

s, t ∈ ℝ

S = {s × b + (1 − s) × a|0 ≤ s ≤ 1}

T = {t × u + (1 − t) × v|0 ≤ t ≤ 1}

distance of (S, T)

(Eq.1) n 2 = √∑(s × bi + (1 − s) × ai − t × ui − (1 − t) × vi) i=1

The function consists of two parameters S and T, which represent the two points on the segment of the CNF axis as depicted on Figure 4.1.

Figure 4.1. Illustration of minimal distance calculation

In the case of a CNF with a carbon black, one of the parameters is replaced by the coordinates of the carbon black center. For the carbon black to the carbon black the distance is a simple calculation of distance between the centers.

3.1. Process Description

This simulation was an iterative process that had two main conditions. First, in order to build the additive’s network we had to test the hypothesis & rules applied to the current experiment. As the process of creation of nanofillers is random, the tests (rhombus) on Figure 4.2 were intended to validate every nanofillers’ compliance to the rules & hypothesis. Second, to analyze the network, we need to determine whether a conductive network was built. If the network exists, the related equivalent resistance can be calculated. Organize the nanofiller setting in order to determine the link between them which should lead to the creation of a percolation bath way.

In the case of percolation, a matrix solving process was applied to calculate the

network resistance.

Figure 4.2. The flow chart of numerical process.

Results

1. Simulation Results

The network analysis code determines the percolation state of the experiment, if a percolation path exists, it determines the equivalent resistance of the virtual sample. The simulation starts from one conductive edge and will follow the connections stored as a function of the quantum tunneling links to determine if the path leads to the other conductive edge. To prevent a closed-loop, it is essential that the same link is not counted twice. Additionally, we must ignore any dead ends.

1.1. Equivalent Resistance Solving

Solving the equivalent resistance is based on Kirchhoff's circuit laws. The circuits are arranged on a matrix equation based on a node method [221]. The system of equations allows for the solving of the resistance value by inverting the system.

For a system of N nanofillers with L links between them and the conductive faces as depicted on Figure 4.3, the system of equation can be written in a single matrix equation (Eq. 2):

R ∗ V = Y ( ) R ∈ Mn+2,n+2 ℝ (Eq.2)

(V, Y) ∈ Mn+2,1(ℝ)

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Figure 4.3. Illustration of network's different configuration.

The V matrix represents the potential precisely: ∀i ∈ [2, n + 1], Vi represents the additive i electrical potential. V1 and Vn+2 represents the electrical potentials of the two conductive faces.

The matrix Y is null except from the Y1,1 and Yn+2,n+2 coefficients that have the value of the electrical potential of the two conductive faces.

The matrix R is depended on the distances of the functioning links under the following rule:

c ∈ ℝ, resistance coefficient.

Dl ∈ ℝ, distance of j functioning link.

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For each Dl, realizing the link between the two entities (an additive or one of the

c conductive faces), x and y, the term will be added to the R matrix under the Dl following rule: c Rx,x = Rx,x − Dl

c Rx,y = Rx,y + Dl

c Ry,x = Ry,x + Dl

c Ry,y = Ry,y − Dl

To ensure a non-zero matrix determinant thus the reversibility of the matrix, if an R matrix line is null the coefficientRi,j, with j = i, is set to 1. Finally, the first and the last line of Rare set to null and the coefficient R1,1 and Rn+2,n+2 are set to one. The simulation then proceeds in an inversion of the system (Eq. 3).

V = Y ∗ R−1 (Eq.3)

This provides the electrical potential of each additive inside the calculation volume. The electrical current inside the calculation volume can be determined with the electrical potentials and then the equivalent resistance in the function of the voltage applied to the conductive faces.

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1.2. Scaling &Time

The scaling is a key parameter in this simulation. The setting of the nanofillers inside the considered volume is a random process. Any results from the simulation has to come from a batch of experiences and the size of the volume impacts variance of the results.

Figure 4.4 shows the evolution of the variance from nearly 4 to under 0.01. The variance is divided 400 times by multiplying by a factor 5 the base volume. A larger variance will result in more computation time.

Figure 4.4. Variance variation vs. Base volume.

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1.3. Aggregation principle

The first simulation showed that a random distribution of nanofillers would not produce a conductive network unless there is some kind of aggregation. Thus, the idea for an aggregation of nanofillers was added to the simulation. This approach allows the network analysis to determine the electrical conductivity trends. The aggregation process was implemented by using the following methods: nanofillers were still placed randomly in a given volume, but after the distance calculations, the

* aggregation part was added before the storage of the quantum tunneling functioning links. The portion that will aggregate the new additive is ruled by one parameter known as the distance of aggregation. This parameter determines if the new additive is within the distance of aggregation. If several additives satisfy this requirement the closest one will be the new additive as depicted in Figure 4.5.

* Aggregation part means the same process in flow chart (Aggregation)

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Figure 4.5. Illustration of aggregation principle.

1.4. Influence of Dagr Parameter

The influence of the distance of aggregation parameter (Dagr) which can be related to the trend for the nanofillers to form aggregate will impact the overall conductivity of the samples. This influence was studied using carbon blacks for the concentration from 0.5 to 10 percent in weight regarding to the polymer and by step of 0.5 percent. The volume of the calculation is parallelepipedic in relation to experimental tests conducted on spin coating film. The simulation is a virtual representation of a sample at each value of percentage and Dagr. A batch of 48 simulations were conducted with the average of each batch shown in Figure 4.6.

This work represents 7680 simulations. Figure 4.6(a) shows a clear increase of the conductivity along with the increase of the value of the parameter. Based on this information we conclude that the aggregate is useful to the creation of a conductive

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network. Figure 4.6(b) shows the conductivity evolution for the 10 percent weight in the case of carbon blacks that the conductivity is converging.

Figure 4.6. (a) Evolution of conductivity vs. percentage (b) conductivity evaluation vs. Dagr

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1.5. Carbon Black in the Spin Coating Film

Carbon blacks inside the calculation volume represented in Figure 4.7(a) is a

3D model. After solving the network, the simulation displays in red all the nanofillers connected directly by the intermediary of others to the first conductive edge. The nanofillers not belonging to the conductive network are shown in gray.

Figure 4.7(b) represents the output of 48 independent workers computing 20 different concentration levels. Thus 960 iterations of the simulation were performed to determine the influence of the concentration on the electrical conductivity. Figure

4.7(c), which represents the evolution of the electrical conductivity mean value of the 48 workers bench shows three parts. After a slow start, there is a rapid increase to finish with a slowdown in terms of conductivity gain.

Figure 4.7(d) shows a fraction of simulation which achieved a conductive network.

This can be seen as a probability of obtaining a conductive network regarding the concentration in weight of the Carbon Black used in the polymer.

1.6. Carbon Nanofiber in the Spin Coating Film

Carbon nanofiber inside the calculation volume were represented in Figure 4.8(a) as 3D model. After solving the network, the simulation displays in red the functioning links between the nanofillers connected directly by the intermediary of others to the conductive edge. Figure 4.8(b) represents the output of 48 independent workers computing each 24 different concentration levels. Thus 1152 iterations of the simulation were performed to determine the influence of the concentration on the electrical conductivity. Figure 4.8(c)

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shows a steady increase of conductivity as concentrations of carbon nanotubes rises. Figure

4.8(d) shows a fraction of simulation which achieved a conductive network. This can be seen as a probability of obtaining a conductive network regarding the concentration in weight of the carbon nanotube used in the polymer.

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Figure 4.7 (a) Example of a spin coating film with CB, (b) Graphical view of the 48 simulations' results, (c) Conductivity vs. carbon blacks percentage in weight, (d) Percolation proportion vs. carbon black concentration

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Figure 4.8. (a) Example of a spin coating film with Carbon Nanofiber, (b) Graphical view of the 48 simulations' results, (c) Conductivity vs Carbon Nanofiber percentage in weight, (d) Percolation proportion vs Carbon nanofiber concentration.

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1.7. The Mix of Carbon Blacks and Carbon Nanofiber

Given the results of the two types of nanofillers, the simulation was used to simulate a mix of the two nanofillers to see if the conductivity would follow a simple mixture law.

For this experiment the total weight percentage was fixed at one percent. The mix was completed according to the following rules:

X = Carbon Nanofiber weight percentage

Y = Carbon Blacks weight percentage

Z = Nanofillers weight percentage

1,0.9,0.85,0.8,0.75,0.7,0.65,0.6,0.55,0.5,0.45,0.4,0.35, Y ∈ ( ) 0.3,0.25,0.2,0.15,0.1,0 { Z = 1% X = Z − Y

One of the challenges faced during the calculation of the mix was the difference between the sizes of the two nanofillers; carbon nanofiber is more than 300 times longer than a carbon black sphere as shown in Figure 4.9(a). The calculation volume size must be set according to the nanotubes own size and will be larger than the carbon blacks spheres.

Consequently, it requires a large number of sphere units to maintain the nanofillers weight percentage, which is constant during the mix calculation. Figure 4.9(b) shows that the electrical conductivity does not follow the mixture law, and we can see a decrease in terms of conductivity regarding the mixture law. The mix of nanofiller is less effective in building a good conductive network.

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Figure 4.9. (a) Example of a spin coating film with a mix of Carbon Nanofiber & Carbon Black, (b) CB/CNT Mixture Law for Conductivity

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2. Experimental Results

Raw materials in this study were characterized by SEM and Raman spectroscopy.

The morphology of carbon black, CNF, and graphene are shown in Figure 4.10 with different scale bars as well as the morphology of spin coating of PCL/nanofillers and PAN/ nanofillers. The dimension of carbon black nanoparticles is about 300nm based on the given information and observation. Carbon black used in this study was naturally aggregated. After sonication and spin coating process, some aggregation of CB/PAN remained as can be observed in Figure 4.10(d). The aggregation size is not measurable.

Different types of aggregation may have different effects on the conductive behavior of this nanocomposite. The smaller aggregation could be only several nanoparticles and the larger one could be a tenth of a micron. The diameter of CNF was confirmed by Figure

4.10(b) and was around 150 nm. CNF showed a random dispersion in the polymer matrix in Figure 4.10(e). The same observation could be noted with CNF/PCL in Figure 4.10(h).

In addition, there is a porosity structure observed for CB/PCL in Figure 4.10(g). Graphene material was produced by a process previously described. As a result, the graphene material used in this study was micro-/nano- pellet. In Figure 4.10(c), the graphene pellets present a flame-like feature which indicates the wide distribution of thickness. While multi-layers of graphene were embedded into the polymer matrix, the flame-like feature disappeared which could be recognized in Figure 4.10(f, I). We believe that the edges of graphene might work as the connection in conductive network and interfaces. It was very interesting to see graphene pellets had the edge perpendicular to the thin film surface. Further study is needed to reveal the behavior of graphene in spin coating process.

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In order to understand the structure of nanofillers, a Raman microscope was employed to study the identity of D band and G band. In Figure 4.11, curves of normalized

Raman shift present a clear ratio difference for each nano-additive and displayed two prominent peaks corresponding to G and D band. Peak width of carbon black used to be very broad due to the high amorphous phase [222] and the grain size of the carbon black materials [223]. This result agrees with the published report from Jawhari et al. [224] The

Raman spectroscopy result of CNF had a lower width for D band and G band. Normally, a well-organized structure (less disordered structure) could lead to a sharper peak. The graphene curve showed a high ratio of intensity of the G band against to D band. The large area of D band in graphene curve indicated that the material had more defects than perfect graphene and might be much thicker. As a consequence, we call it an exfoliated graphite.

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Figure 4.10. SEM images of (a) carbon black, (b) CNTs, (c) graphene. SEM images of spin coating film of (d) CB/PAN, (e) CNT/PAN, (f) graphene/PAN. SEM images of spin coating film of (g) 10 wt% of CB/PCL, (h) 10wt% of CNT/PCL (i) 10wt% of graphene/PCL.

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Figure 4.11. Comparison of Raman spectra of CB, CNF and graphene.

The conductivity test was performed by using 2 copper plate probes, the test direction was perpendicular to the film plane. After compressing the film firmly, a stable value was recorded. Two polymers were used as matrices: PCL and PAN. PCL has a glass transition temperature about -60°C, which for PAN is ~90°C. Due to the fact that PAN has a much higher Tg than PCL, PCL is much more elastic than PAN at room temperature. As a consequence, while testing, PCL nanocomposite films deformed much more than PAN.

These differences in mechanical behavior led to a difference in conductive behavior. Figure

4.12 (a, b) shows the conductivity as a function of the concentration of nanofillers. A conductive network formed at about 3 to 5wt% transition region which led to an increase in conductivity by order of magnitude. Both figures indicate that a conductivity increased with each increase in the concentration.

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Figure 4.12. Relationship between the conductivity & concentration of the nano-additive with (a) PCL systems (b) PAN systems.

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The conductivity results of the mixture of carbon black and CNF nanocomposite

(Figure 4.13) clarified that the increase in conductivity was specifically attributed to an increase in the amount of CNF. The concentration of the mixture was kept constant at

5wt%, so the CNF proved to have the dominant effect. The conductivity of the mixture did not follow the mixture law of composite.

Figure 4.13. The Mixture Law of 5%wt of CB & CNF/ PAN nanocomposites

Discussion and Conclusions

The experimental result showed the conductivity increased with an increase in the amount of nanofillers concentration. Regardless of the type of nano-filler used the trend remained the same. The percolation threshold is around 4-5wt% of nano-additive. But at the same concentration, the conductivity is higher in graphene based nanocomposites than for CNF and carbon blacks based nanocomposites. This result was expected because the conductivity of carbon black is lower than that of CNF and graphene due to their spherical

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onion like geometry and their small grain size. The contact between two adjacent carbon black particles is controlled by Van der Waals interaction. However, in the case of CNF and graphene, two modes of bonding interactions are assumed: covalent and Van der Waals bonds which explains their value increase in conductivity.

One of the most useful properties of graphene is that it is a zero-overlap semimetal

(with both holes and electrons as charge carriers) which leads to higher electrical conductivity than CB and CNF. In graphene, each atom is connected to 3 other carbon atoms on the two-dimensional plane, leaving one electron freely available in the third dimension for electronic conduction. When comparing the three types of fillers, the electrical conductivity of graphene is higher than CNF and CB. The exfoliated graphite has electrical conductivity about 2.8–3.2 kS/m [225]. On the other hand, the conductivity of carbon nanofiber and carbon black are 5 x 10-5 Ω.cm, 9.30 S/cm respectively [226,227].

For both PCL and PAN based systems, the numerical simulation and experimental measurement seem to be in agreement. The conductivity trend for carbon blacks and carbon nanotubes based composites are the same, this numerical modelling highlights the benefits of mixing different types of nanofiller to achieve better conductive network. The percolation proportion of the carbon nanotube in the simulation result was about 0.3wt% which is equal to published data [228]. It seems that the dispersion of nano-additives is the key parameter to be considered. In our scenario, as opposed to the aggregation phenomenon, dispersion had the opposite effect while mixing different types of nanofillers such as carbon black and nanotubes. The nanotubes tend to aggregate the carbon blacks along their axis thus

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preventing them from forming larger connecting aggregates, which are the necessary elements to build the conductive network.

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CHAPTER V

ENHANCING THE CELL GROWTH USING CONDUCTIVE SCAFFOLDS

Introduction

Scaffolds were generated as substrate structures for tissue repair and regeneration [229,

230]. Scaffolds can be formed by utilizing biopolymers, conductive materials and polymer based additives which can provide additional features such as surface, mechanical and electrical properties. Synthetic polymers are commonly used for the fabrication of nanofiber scaffolds. In this study, we explored their use as biodegradable materials for scaffolds. These include poly (lactic acid) (PLA), poly (lactic-co-glycolic acid) (PLGA),

Polycaprolactone (PCL), poly (methyl methacrylate) (PMMA), polyglycolic acid(PGA), and polyvinyl alcohol (PVA). Polymer scaffolds can be combined with growth factors.

These polymer scaffolds have been used for numerous applications, including regeneration of blood vessels (i.e. coronary arteries), bone, skin, cartilage, as well as to enhance cell proliferation and differentiation [231-233]. Another material that has shown rapid expansion among biocompatible scaffolds are electroactive materials. These materials hold a great promise for cell growth and tissue repair. Conductive scaffolds have been considered suitable substrates for cell proliferation and cell attachment [234], and they

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enhanced the effect of electrical signals on cell activities [235, 236]. For instance, when biocompatible polypyrrole (PPY) film was applied to rat bone marrow stromal cells in culture, the electron mobility, electrical conductivity and calcium deposition into the extracellular matrix increased due to the highly-branched PPy chains of the film [237].

Furthermore, the electroactive and biodegradable blend polymer (PLLA/ PGTA) was able to differentiate rat C6 glioma cells rapidly [238]. Finally, carbon nanofillers have a broad range of usage in biological applications as scaffolds [239, 240] to enhance cell differentiation [241, 242] due to their compatibility and electrical and mechanical properties [243, 244]. These fillers, in particular, carbon black (CB), carbon nanofiber

(CNF) and graphene, have a variety of characteristics that rely on their crystal structure and geometrical configuration [245]. CB is extensively used as a filler in elastomers, plastic and paints to modify the mechanical, electrical and the optical properties of the materials

[246]. CB has a spherical particle form, obtained by the partial combustion or thermal decomposition of hydrocarbons [247]. It has a large surface area and an aggregate dimension that ranges from tens of nanometers to a few hundred nanometers. When added to another component, it imparts its special features to improve the mechanical and electrical properties of the nanocomposite [248]. In addition, CNF can be primarily fabricated by catalytically vaporizing deposition growth and electrospinning approaches

[249]. CNF has a cylindrical nanostructure with a high aspect ratio, extraordinary thermal conductivity, mechanical, and electrical properties which used as additives in various structural materials. The potential of using carbon-based nanofibers as reinforcement was realized in the 1980s [250-253]. The most reliable filler is graphene which consists of interconnected hexagon carbon atoms and forms lamella. Carbone nanotubes are formed

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by rolling graphene along certain axes. This allows graphene to be structurally linked to many carbon allotropes [254]. In the last ten years, graphene has been one of the most studied materials due to its unique electrical, optical, and mechanical properties as well as for its potential applications [255]. Graphene can be prepared by exfoliation, epitaxial growth and chemical vapor deposition methods [256].

PCL nanocomposite based carbon nanofillers were fabricated by using electrospinning and spin coating techniques. It is known that electrospinning can improve cell proliferation.

Yang et al. studied the behavior of neural stem cells (NSC) with an aligned electrospun nanofiber scaffold of poly (l-lactic acid) (PLLA). The results showed that the direction of

PLLA fibers had a parallel control on the direction of NSC elongation and their neurite outgrowth [257]. Furthermore, to understand the behavior and interaction of cells with scaffolds, the orientation and alignment of the scaffold morphology was studied. For example, Sharma et al. achieved a significant effect of 80 % elongation of cells on scaffold by using micropatterned polymeric films [258]. Moreover, directed axonal and nerve regeneration has been promoted by using micropatterned scaffolds [259, 260]. Zhou et al. demonstrated that a scaffold of electrospun aligned PLLA fibers coated with PGlu-codoped

PPy film significantly enhanced neurite’s extensions by 68% [261]. Recently, numerous research studies have been examining the effects of electrical conductivity and electrical stimulation of the cells. PLLA fibers have also been known to regulate cell attachment, proliferation, and differentiation of nerve cell axonal extension [262], as well as healing of bones [263], cartilage [264], skin, connective tissues [265], cranial, spinal [266, 267] and peripheral nerves [268,269].

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In a study by Schmidt et al., the effect of electrical stimulus through a scaffold film was recorded on muscle and neuronal cells [270]. Polypyrrole (PPy) film appeared to have a slight adverse tissue response compared to poly (lactic acid-co-glycolic acid). Another study used CNT grid as conductive scaffolds to demonstrate the effect of neuronal circuit growth, by significantly increasing the efficacy of neural signal transmission [271]. On the other hand, Keisham et al. used graphene as a noninvasive tool for early cancer diagnosis due to its large quantum capacitance and the electronic properties. The result demonstrated the ability of graphene membrane to differentiate a single hyperactive cancerous cell from a normal cell by integrating brain cells onto graphene substrate [272].

In this work, we explore the effect that scaffold orientation and conductivity has on cell growth. The orientation was altered using processing methods such as electrospinning and spin coating. On the other hand, the conductivity was tailored using three carbon nanofillers

(CNF, CB and graphene) at various concentrations.

Materials and Experimental Methods

1. Materials

Polycaprolactone (PCL), (M̅̅̅̅w̅= 80,000) is a semi crystalline nontoxic hydrophobic biodegradable polyester supplied by Sigma Aldrich Corporation. Nanofillers that used in this study are carbon nanofiber (CNF), carbon black (CB) and graphene. CNF was provided by Pyrograf Products Inc. which were dispersed in a polymer to provide a conductive network by approximately 5 x 10-5 Ω.cm [273]. The average outer diameter of CNF is 125-

150 nm and the average specific surface area is 65-75 m2/g. CB is a high conductive

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(Vulcan XC 72R) powder obtained from Cabot® Corporation with a particle size of 300 nm and 1.9 Ohm-cm volume conductivity at 23 ℃. The electrical conductivity of CB is

9.30 S/cm [274]. Exfoliated graphene produced by thermal shock or rapid temperature change of the intercalated graphite compound, which was previously described [275]. The surface area of the small, medium and large exfoliated graphite is 16.02,15.61 and 15.35 m2/g respectively and has an electrical conductivity of about 2.8–3.2 kS/m [276]. Acetone is a solvent which used to form PCL/nanofiller solution. Eagle’s Minimum Essential

Medium EMEM (ATCC® 30-2003™) and Fetal Bovine Serum (FBS) (ATCC® 30-

2020™) were used as a growth medium for the cell. Human lens epithelial cell B-3

(ATCC® CRL-11421™). Neutral Buffered Formalin (10%) (Thermo Scientific™

Richard-Allan Scientific™), 1X phosphate buffered saline (PBS) and ProLong® Diamond

Antifade Mountant with DAPI (Molecular Probes™ by life technologies) were used to characterize the cell.

2. Fabrication of Conducting Scaffold

Scaffolds were prepared by mixing 14 wt% PCL and nanofiller. Five different weight percentages of nanofiller were dispersed in 5 ml of acetone, and was ultra-sonicated for 2 days. Following the ultrasonication process, a solution of 0.644 g PCL and 5 ml acetone, which was stirred at a temperature of 65°C for 2 hours. A spin coater method

(Speed line P2604 Technologies) was used to produce a PCL/nanofillers thin film scaffold using a Spin speed of 3000 rpm for 90 seconds. The electrospinning method was used to fabricate a PCL/ nanofiller nanofibrous scaffolds and this was performed using a syringe pump (New Era Pump Systems, Inc. NE-300), voltage controller (Stanford research

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systems, Inc. Model PS375), rotator (Dayton® DC Motor, 4Z145), rotator controller

(Mastech, HY3010E), and a syringe (30mL Luer-Lor™ Syringe, BD), 17# needle. The voltage between the needle and the collector was 15kV with a feeding rate of 0.003mL/min, and a rotator speed of 5.7m/s. The PCL/ acetone solution was 14% by weight.

3. Electrical Measurement

Based on our previse work, spin coating film conductivity was tested by using a two-probe method with copper electrodes and a KEITHLEY 2700 multimeter/DATA acquisition system. The thickness of the films were measured by a thermal mechanical analysis (TMA, Q400, TA Universal) at room temperature (~23°C) [277]. The conductivity of the electrospinning fibers does not measure in this work due to unavailable tools to test the conductivity of the single fiber.

4. Cell Culture and Seeding

Transformed human lens epithelial (HLE) cells B-3 (ATCC) were cultured in

Eagle’s Minimum Essential Medium (EMEM) supplemented with 20% fetal bovine serum

(FBS). HLE B-3 frozen cells were thawed in a 37°C water bath with keeping the O-ring and cap out of the water to avoid any contamination for 2 minutes. Once thawed, the cells were aseptically transferred to 50 ml tubes with 10 ml of the culture media and centrifuged at approximately 125 x g for 5-10 minutes to remove cryoprotective agents. The cells were resuspended in 20 ml of fresh growth medium, plated into a 75 cm2 tissue culture flasks and incubated in 5% CO2 at 37°C.

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4.1 Sub-Culturing Procedure

After 5-7 days of incubation, the cells were sub-cultured by separating the cells from the dish using the enzyme Trypsin for less than 30 seconds. The process was repeated for 60 seconds at room temperature. Complete growth medium was then added to neutralize the trypsin and the contents were placed in a centrifuge tube. The contents were centrifuged at approximately 125 x g for 5-10 minutes. The medium and trypsin were aspirated and new media was added to resuspend the cells. At this time, the cells were ready to culture on biomaterial scaffold. After calculating the number of viable cells a dilution ratio was applied to well plates containing the different scaffold along with growth media. The cells were, incubated for 24, 72 and 120 hours.

4.2 Fixing Adherent Cells

Cells grown on scaffolds were fixed with 10% Neutral Buffered formalin for 10 minutes. The scaffolds were then rinsed twice with 1X phosphate buffered saline (PBS).

To stain cell nuclei, the scaffold-cell interfaces were incubated with one drop of prolong® diamond antifade mountant containing DAPI (Life technologies corporation) on microscope slides.

5. Characterization

A Phenom Desktop scanning electron microscope (SEM) (Pro X, Phenom) was used to characterize the morphology of nanofillers and scaffolds. X-ray diffractometer

(Smart lab Rigaku) was used to characterize the crystallinity of the raw materials. A

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fluorescence microscope (MF53, Nikon) was used to characterize cell density. Cell images were analyzed by ImageJ software. The cell density was estimated by counting DAPI+ cells in each dish and calculating the average of the integrated density.

Results and Discussion

We have characterized several scaffolds made up of three types of carbon nanofillers including CB, CNF and graphene that have unique properties to improve cell growth. As shown in Figure 1, the morphology of CB, CNF and graphene was characterized. Using dark field imaging, we show that carbon black consists of spherical nanoparticles in which these particles are arranged in the form of onion like structure (inset: the model of Heidenreich) (Figure 5.1) [278]. These particles have an average dimension of 300 nm. Figure 5.2. shows the morphology of CNF with a diameter of around 150 nm and graphene platelets are made of thin carbon sheets with a majority ranging between 15-

20um in length and width (Figure 5.3).

Figure 5.1. v. Dark field imaging shows the onion like structure of carbon black (CB) [278].

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Figure 5.2. SEM morphology of carbon nanofibers (CNF).

Figure 5.3. SEM morphology of graphene platelets.

All these nanoparticles were mixed into polycaprolactone matrix to fabricate various samples by electrospinning and spin coating methods. The morphology of electrospinning fibers of PCL/1 wt% of CB, CNF and graphene composites is shown in Figure 5.4. All spun fibers were produced with some degree of alignment and different diameters.

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The nanofibers were smaller in size in the case of CB/PCL vs. CNF/PCL and graphene/PCL fibers. The difference in dimension might be due to the nano-additive aspect ratio and their dispersion into PCL.

10 µm 10 µm 10 µm a b c

Figure 5.4. SEM images of electrospinning based fibers of (a) CB/PCL, (b) CNF/PCL, (c) graphene/PCL.

Conversely, spin coating based films of 1 wt% CB/PCL, CNF/PCL, graphene/PCL nanocomposite are shown in Figure 5.5. The ringed shape shown in these pictures represents the nano-additive network. CB/PCL based nanocomposite films show a larger porous area with relatively less aggregates than CNF/PCL. However, graphene/PCL films show the best compromise with better dispersion and a little porosity.

10 µm 10 µm 10 µm

Figure 5.5. SEM images of spin-coating based samples of (a) CB/PCL, (b) CNF/PCL and (c) graphene/PCL

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The crystallinity characterization of the raw materials was measured by X-ray diffraction. X-ray diffractograms were recorded in ranges of 5–90∘ (2휃) angles. As shown in Figure 5.6 (a), the XRD pattern of graphene is characterized by a strong, sharp peak with high intensity at 27.409 which corresponds to (002) crystallographic plane. It indicates a higher ordered structure. Conversely, XRD spectrum of CNF and CB shows less carbon order (Figure 5.6). Both of these nano-additives were made of turbostratic carbons with relatively low crystallinity.

Figure 5. 6. XRD measurements of (a) graphene, (b) CNF and (c) CB.

We wanted to test if the manufactured scaffolds favored cell growth, therefore, we seeded an equal amount of human lens epithelial cells (B-3 cell line) to each of the prepared

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scaffolds. Samples were made by electrospinning and spin coating. Cell growth was carried out for a period of 24, 72 and 120 hours (Figure 5.7). Cells were then visualized using the nuclear stain DAPI under a fluorescent microscope. We noted that for the same concentration and nano-additive type, the cell density was higher in samples made by electrospinning compared to the samples made by spin-coating (Figure 5.7). HLE cells were able to grow well on electrospun scaffolds and seem to grow parallel to the fiber orientation of electrospun scaffolds. Generally, scaffold fibers have remarkable properties such as a diameter in the hundreds of nanometers and highly interconnected pores that are tens of micrometers in diameter [279, 280]. This high surface area–volume ratio of fiber scaffold confirms a suitable area for cell attachment which allows the cells to be directed compared with a nonaligned scaffold [281]. On the other hand, cells grown on spin coated scaffolds (Figure 5.7 (d-f)) display a random pattern and the cell density was less than that of cells grown on electrospun scaffolds. Interestingly spin coated scaffold made with graphene were more favorable for cell growth than ones made with CNF and CB.

(This space intentionally left blank)

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(a) (b) (c)

100 µ 100 µ 100 µ

(a’) (b’) (c’)

100 µ 100 µ 100 µ

(d) (e) (f)

100 µ 100 µ 100 µ

(d’) (e’) (f’)

100 µ 100 µ 100 µ

Figure 5. 7 Fluorescent microscope images of fixed HLE cells stained with DAPI and grown on CB, CNF or graphene fiber-based scaffolds (a), (b), (c) and their bright field corresponding images (a’), (b’) and (c’). Images of DAPI stained cells grown on thin film scaffolds for CB (d), CNF (e) and graphene (f) and their respective bright field images (d’), (e’) and (f’).

Analysis of the cell density during 24, 72 and 120 hours on spin-coated and fiber scaffolds are depicted in Figure 5.8. Using both types of scaffolds, we were able to note an increase

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in cell density that correlated with higher additive concentration. Cell density also increased with increase incubation times. In addition, graphene was more favorable for cell growth than the other two materials. These observations are consistent with a previous study stating the electrical behavior of nanofiller based PCL nanocomposite films as illustrated on Figure 5.9 [277].

We also studied the relationship between cell density and various additives of fiber and film scaffolds during a 24, 72 and 120-hour time period. The concentration of additives was kept constant at 1%wt as displayed in Figure 5.10. The cell density increased with longer incubation times and there was also a gradual increase in cell density for the scaffolds that consisted of graphene, CNF and CB. An increase in scaffold surface conductivity may lead to an efficient absorption and deposition of serum proteins, which can aid in cell attachment and cell growth [282]. Our results support graphene as a superior scaffold for cell growth. The electrical conductivity of the nanofillers, specifically graphene plays an important role in cell growth due to its ability to transport high electrical currents [283]. The higher electrical conductivity of graphene depends on two modes of bonding interactions: Van der Waals and covalent bonds, as well as on the zero-overlap semimetal (with both holes and electrons as charge carriers). In addition, each atom in graphene is connected to three other carbon atoms on the two-dimensional plane, leaving one electron freely available on the third dimension for electronic conduction.

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(a) (a)

(b) (b)

Figure 5. 8. Cell density measured by counting DAPI+ cells grown on electrospun fiber scaffolds (a) 24hr, (b)72hr and (c) 120hr after plating. (left side) and thin film scaffolds (a) 24hr, (b)72hr and (c) 120hr after plating. (right side)

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Figure 5. 9. Relationship between the conductivity & concentration of the nano-additive with PCL systems

(a) (b)

Figure 5.10. Relationship between cell density and time of incubation with 1wt% of (a) fiber and (b) thin film scaffolds

On the other hand, CNF also has covalent and Van der Waals bonds [284, 285] that could be responsible for its relative higher value on conductivity and could explain its role in supporting cell growth. CB, however, has the least favored cell growth properties and this could be due to the spherical onion like geometry and small grain size as well as the control of Van der Waals interactions between two adjacent particles reducing conductivity

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performance of the scaffold.

Conclusion

The biopolymer nanocomposites based on carbon nanofillers have a positive effect on the behavior of cell growth. Regardless of the scaffold shape (film or fiber) and additive’s type, when the concentration of nano-additives is increased, the electrical conductivity and the cell density increased too. For a given nano-additive’s concentration and type, cell density increased in the scaffolds with fiber shape vs. the film. Importantly, as the conductivity of the scaffolds increased, so did the cell density.

As shown in this study, there is close relationship between the electrical conductivity, cell density and scaffold orientation. An increase on conductivity can be achieved in two ways: by molecular orientation or/and by the appropriate selection of nano- additives such as graphene and nanotubes.

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CHAPTER VI

CONCLUSION AND RECOMMENDATIONS

In this work, we fabricated an intelligent scaffold for use in tissue engineering applications. The main idea was to enhance the geometry and the mechanical and electrical properties of scaffolds by using distinct types of nanofillers such as graphene, carbon nanofiber and carbon black. We identified the optimal concentrations of nano-additive in both fibrous and film scaffolds to obtain the highest mechanical and electrical properties without neglecting any of them. Finally, we investigated the performance of these scaffold with cell biology.

To achieve these goals, we first studied the mechanical properties of the scaffold as a function of morphology, concentration and variety of carbon nanofillers. Results showed that there was a gradual increase of the modulus and the fracture strength while using carbon black, carbon nanofiber and graphene, due to the small and strong carbon-to- carbon bonds and the length of interlayer spacing. Furthermore, regardless of the fabrication method, there was an increase in mechanical properties as the concentration of nanofillers increased until a threshold was reached 7%wt of nanofillers film scaffold and

1%wt of fibrous scaffold. Experimental results of carbon black showed a good agreement when compared with data obtained using numerical approaches and analytical models, especially in the case of lower CB fractions.

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Second, we examined the influence of electrical properties of nanofillers based on the concentration and the geometry of carbon nanofillers in the polymer matrix using experimental and numerical simulation approaches. The experimental results showed an increase in conductivity as the amount of nanofiller concentration increased. And regardless of nanofiller type, the trend remained the same. The percolation threshold was around 4-5wt% of nano-additive with PCL and PAN matrices, respectively. However, at the same concentrations, conductivity was higher in graphene-based nanocomposites than for CNF and carbon black-based nanocomposites. The numerical modeling highlighted the effect of nanofillers as constructing a conductive network due to the aggregation phenomenon. The conductivity trend for carbon black and carbon nanotube-based composites by the numerical simulation approach was similar to the experimental approach.

Lastly, we studied the effect of these carbon nanocomposite-based scaffolds on the behavior of cell growth. The results showed that regardless of the scaffold shape (film or fiber) and the additive’s type, when the concentration of nano-additives was increased, electrical conductivity and cell density increased. For a given nano-additive concentration and type, cell density increased in the scaffolds with fiber shape vs. the film. Importantly, as the conductivity of the scaffolds increased, so did the cell density. Consequently, this study has highlighted the close relationship between electrical conductivity, cell density and scaffold orientation. An increase in conductivity can be achieved in two ways: by molecular orientation or by the appropriate selection of nano-additives such as graphene and carbon nanotubes.

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Future work includes constructing tissue scaffolds based on graphene nanocomposite by using a 3D printer for wound recovery and bone implants; testing the fabricated scaffolds on living organisms, testing the scaffolds for cell differentiation and in different types of cells and maybe on organoids, and modeling of mechanical properties of CNF and graphene based nanocomposite. This dissertation might be led to discover a new pathin tissue regeneration.

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REFERENCES

1. Schultheiss, D., Bloom, D. A., Wefer, J., & Jonas, U. (2000). Tissue engineering from

Adam to the zygote: historical reflections. World journal of urology, 18(1), 84-90.

2. Williams, D. F. (2014). The biomaterials conundrum in tissue engineering. Tissue

Engineering Part A, 20(7-8), 1129-1131.

3. Dorati, R., Colonna, C., Genta, I., & Conti, B. (2011). Polymer scaffolds for bone

tissue regeneration. In Active implants and scaffolds for tissue regeneration (pp. 259-

285). Springer Berlin Heidelberg.

4. Perán, M., García, M. A., & Marchal, J. A. (2012). Functionalized nanostructures

with application in regenerative medicine. International journal of molecular

sciences, 13(3), 3847-3886.

5. Nair, L. S., & Laurencin, C. T. (2007). Biodegradable polymers as

biomaterials. Progress in polymer science, 32(8), 762-798. D.W. Hutmacher,

Scaffolds in tissue engineering bone and cartilage, Biomaterials 21 (2000) 2529–

2543

6. Hutmacher, D. W. (2000). Scaffolds in tissue engineering bone and

cartilage. Biomaterials, 21(24), 2529-2543.

141

7. Kim, D. D., Kim, D. H., & Son, Y. J. (2010). Three-dimensional porous scaffold of

hyaluronic acid for cartilage tissue engineering. In Active Implants and Scaffolds for

Tissue Regeneration (pp. 329-349). Springer Berlin Heidelberg.

8. Cai, X., Tong, H., & Hu, J. (2009). Preparation and characterization of homogeneous

chitosan–polylactic acid/hydroxyapatite nanocomposite for bone tissue engineering

and evaluation of its mechanical properties. Acta biomaterialia, 5(7), 2693-2703.

9. Rezwan, K., Chen, Q. Z., Blaker, J. J., & Boccaccini, A. R. (2006). Biodegradable

and bioactive porous polymer/inorganic composite scaffolds for bone tissue

engineering. Biomaterials, 27(18), 3413-3431.

10. Ridzwan, M. I. Z., Shuib, S., & Ibrahim, M. M. (2007). Problem of stress shielding

and improvement to the hip implant designs: a review. J. Med. Sci, 7(3), 460-467.

11. Stella, J. A., D’Amore, A., & Sacks, M. S. (2010). On the biomechanical function of

scaffolds for engineering load-bearing soft tissues. Acta biomaterialia, 6(7), 2365-

2381.

12. Chung, S., & King, M. W. (2011). Design concepts and strategies for tissue

engineering scaffolds. Biotechnology and applied biochemistry, 58(6), 423-438.

13. Carletti, E., Motta, A., & Migliaresi, C. (2011). Scaffolds for tissue engineering and

3D cell culture. 3D Cell Culture: Methods and Protocols, 17-39.

14. Matsuno, T., Hashimoto, Y., & Satoh, T. (2008). Preparation of injectable 3D-formed

β-tricalcium phosphate bead/alginate composite for bone tissue engineering. Dental

materials journal, 27(6), 827-834.

142

15. Badylak, S. F. (2007). The extracellular matrix as a biologic scaffold

material. Biomaterials, 28(25), 3587-3593.

16. Freyman, T. M., Yannas, I. V., Yokoo, R., & Gibson, L. J. (2001). Fibroblast

contraction of a collagen–GAG matrix. Biomaterials, 22(21), 2883-2891.

17. Wang, Y., Kim, U. J., Blasioli, D. J., Kim, H. J., & Kaplan, D. L. (2005). In vitro

cartilage tissue engineering with 3D porous aqueous-derived silk scaffolds and

mesenchymal stem cells. Biomaterials, 26(34), 7082-7094.

18. Nahmias, Y., Schwartz, R. E., Verfaillie, C. M., & Odde, D. J. (2005). Laser‐guided

direct writing for three‐dimensional tissue engineering. Biotechnology and

bioengineering, 92(2), 129-136.

19. Williams, D. F. (2009). On the nature of biomaterials. Biomaterials, 30(30), 5897-

5909.

20. Alvarez, K., & Nakajima, H. (2009). Metallic scaffolds for bone

regeneration. Materials, 2(3), 790-832.

21. Dorj, B., Won, J. E., Kim, J. H., & Kim, H. W. (2013). Robocasting nanocomposite

scaffolds of poly (caprolactone)/hydroxyapatite incorporating modified carbon

nanotubes for hard tissue reconstruction. Journal of Biomedical Materials Research

Part A, 101(6), 1670-1681.

22. Wu, I., Nahas, Z., Kimmerling, K. A., & Elisseeff, J. H. (2012). An injectable adipose

matrix for soft tissue reconstruction. Plastic and reconstructive surgery, 129(6), 1247.

143

23. Stosich, M. S., & Mao, J. J. (2005, August). Stem cell-based soft tissue grafts for

plastic and reconstructive surgeries. In Seminars in Plastic Surgery (Vol. 19, No. 03,

Avenue, New York, NY 10001, USA.

24. Hodde, J. (2006). Extracellular matrix as a bioactive material for soft tissue

reconstruction. ANZ Journal of Surgery; 76(12):1096-100.

25. Ma, P. X. (2008). Biomimetic materials for tissue engineering. Advanced drug

delivery reviews, 60(2), 184-198.

26. Tabata, Y. (2009). Biomaterial technology for tissue engineering

applications. Journal of the Royal Society Interface, 6(Suppl 3), S311-S324.

27. Igwe, J., Amini, A., Mikael, P., & Nukavarapu, S. (2011). Nanostructured scaffolds

for bone tissue engineering. In Active implants and scaffolds for tissue

regeneration (pp. 169-192). Springer Berlin Heidelberg.

28. Tian, H., Tang, Z., Zhuang, X., Chen, X., & Jing, X. (2012). Biodegradable synthetic

polymers: preparation, functionalization and biomedical application. Progress in

Polymer Science, 37(2), 237-280.

29. Jenkins, M. J., & Harrison, K. L. (2006). The effect of molecular weight on the

crystallization kinetics of polycaprolactone. Polymers for advanced

technologies, 17(6), 474-478.

30. Rajagopal, K., Mahmud, A., Christian, D. A., Pajerowski, J. D., Brown, A. E.,

Loverde, S. M., & Discher, D. E. (2010). Curvature-coupled hydration of

144

semicrystalline polymer amphiphiles yields flexible worm micelles but favors rigid

vesicles: polycaprolactone-based block copolymers. Macromolecules, 43(23), 9736.

31. Woodruff, M. A., & Hutmacher, D. W. (2010). The return of a forgotten polymer—

polycaprolactone in the 21st century. Progress in Polymer Science, 35(10), 1217-

1256.

32. Ibim, S. M., Uhrich, K. E., Bronson, R., El-Amin, S. F., Langer, R. S., & Laurencin,

C. T. (1998). Poly (anhydride-co-imides): in vivo biocompatibility in a rat

model. Biomaterials, 19(10), 941-951.

33. Nukavarapu, S. P., Kumbar, S. G., Brown, J. L., Krogman, N. R., Weikel, A. L.,

Hindenlang, M. D., ... & Laurencin, C. T. (2008). Polyphosphazene/nano-

hydroxyapatite composite microsphere scaffolds for bone tissue

engineering. Biomacromolecules, 9(7), 1818.

34. Dreyfus, H. (1935). U.S. Patent No. 2,002,085. Washington, DC: U.S. Patent and

Trademark Office.

35. Ulery, B. D., Nair, L. S., & Laurencin, C. T. (2011). Biomedical applications of

biodegradable polymers. Journal of polymer science Part B: polymer physics, 49(12),

832-864.

36. Zhu, Y., Gao, C., Guan, J., & Shen, J. (2004). Promoting the cytocompatibility of

polyurethane scaffolds via surface photo-grafting polymerization of

acrylamide. Journal of Materials Science: Materials in Medicine, 15(3), 283-289.

145

37. Szycher, M. (1988). Biostability of polyurethane elastomers: a critical

review. Journal of biomaterials applications, 3(2), 297-402.

38. Choudhary, S. (2010). Influence of hydrophobic modification in alginate-based

hydrogels for biomedical applications.

39. Visakh, P. M., Mathew, A. P., & Thomas, S. (2013). Natural polymers: their blends,

composites and nanocomposites: state of art, new challenges and opportunities.

In Advances in Natural Polymers (pp. 1-20). Springer Berlin Heidelberg.

40. Guerzoni, S., Deplaine, H., & Ferrer, G. G. (2014). Combination of silica

nanoparticles with hydroxyapatite reinforces poly (L-lactide acid) scaffolds without

loss of bioactivity. Journal of Bioactive and Compatible Polymers, 29(1), 15-31.

41. Phipps, M. C., Clem, W. C., Catledge, S. A., Xu, Y., Hennessy, K. M., Thomas, V.,

... & Bellis, S. L. (2011). Mesenchymal stem cell responses to bone-mimetic

electrospun matrices composed of polycaprolactone, collagen I and nanoparticulate

hydroxyapatite. PloS one, 6(2), e16813.

42. Williams, D. F. (1999). The Williams dictionary of biomaterials. Liverpool

University Press.

43. Moon, H. T., Lee, Y. K., Han, J. K., & Byun, Y. (2002). Improved blood

compatibility by sustained release of heparin–deoxycholic acid conjugates in a PCL–

PEG multiblock copolymer matrix. Journal of Biomaterials Science, Polymer

Edition, 13(7), 817-828.

146

44. Amiji, M., & Park, K. (1992). Prevention of protein adsorption and platelet adhesion

on surfaces by PEO/PPO/PEO triblock copolymers. Biomaterials, 13(10), 682-692.

45. Jahani, H., Kaviani, S., & Zonoubi, Z. (2012). The effect of aligned and random

electrospun fibrous scaffolds on rat mesenchymal stem cell proliferation. Cell J

(Yakhteh), 14(1).

46. Kim, I. L., Khetan, S., Baker, B. M., Chen, C. S., & Burdick, J. A. (2013). Fibrous

hyaluronic acid hydrogels that direct MSC chondrogenesis through mechanical and

adhesive cues. Biomaterials, 34(22), 5571-5580.

47. Ghasemi‐Mobarakeh, L., Prabhakaran, M. P., Morshed, M., Nasr‐Esfahani, M. H.,

Baharvand, H., Kiani, S., ... & Ramakrishna, S. (2011). Application of conductive

polymers, scaffolds and electrical stimulation for nerve tissue engineering. Journal of

tissue engineering and regenerative medicine, 5(4), e17-e35.

48. Hardy, J. G., Lee, J. Y., & Schmidt, C. E. (2013). Biomimetic conducting polymer-

based tissue scaffolds. Current opinion in biotechnology, 24(5), 847-854.

49. Hazarika, J., & Kumar, A. (2016). Studies of structural, optical, dielectric relaxation

and ac conductivity of different alkylbenzenesulfonic acids doped polypyrrole

nanofibers. Physica B: Condensed Matter, 481, 268-279.

50. Schaffer, H. E., Chance, R. R., Knoll, K., Schrock, R. R., & Silbey, R. (1990). Linear

Optical Properties of a Series of Polyacetylene Oligomers. In Conjugated Polymeric

Materials: Opportunities in Electronics, Optoelectronics, and Molecular

Electronics (pp. 365-376). Springer Netherlands.

147

51. Jin, G., & Li, K. (2014). The electrically conductive scaffold as the skeleton of stem

cell niche in regenerative medicine. Materials Science and Engineering: C, 45, 671-

681.

52. Foulds, N. C., & Lowe, C. R. (1986). Enzyme entrapment in electrically conducting

polymers. Immobilisation of glucose oxidase in polypyrrole and its application in

amperometric glucose sensors. Journal of the Chemical Society, Faraday

Transactions 1: Physical Chemistry in Condensed Phases, 82(4), 1259-1264.

53. Wong, J. Y., Langer, R., & Ingber, D. E. (1994). Electrically conducting polymers

can noninvasively control the shape and growth of mammalian cells. Proceedings of

the National Academy of Sciences, 91(8), 3201-3204.

54. Guimard, N. K., Gomez, N., & Schmidt, C. E. (2007). Conducting polymers in

biomedical engineering. Progress in polymer science, 32(8), 876-921.

55. Brown, M. J., & Loew, L. M. (1994). Electric field-directed fibroblast locomotion

involves cell surface molecular reorganization and is calcium independent. Journal

of Cell Biology, 127(1), 117-128.

56. Schmidt, C. E., Shastri, V. R., Vacanti, J. P., & Langer, R. (1997). Stimulation of

neurite outgrowth using an electrically conducting polymer. Proceedings of the

National Academy of Sciences, 94(17), 8948-8953.

57. Ozawa, H., Abe, E., Shibasaki, Y., Fukuhara, T., & Suda, T. (1989). Electric fields

stimulate DNA synthesis of mouse osteoblast‐like cells (MC3T3‐E1) by a

148

mechanism involving calcium ions. Journal of cellular physiology, 138(3), 477-483.

58. Pullar, C. E., Isseroff, R. R., & Nuccitelli, R. (2001). Cyclic AMP‐dependent protein

kinase A plays a role in the directed migration of human keratinocytes in a DC electric

field. Cytoskeleton, 50(4), 207-217.

59. Li, X., & Kolega, J. (2002). Effects of direct current electric fields on cell migration

and actin filament distribution in bovine vascular endothelial cells. Journal of

vascular research, 39(5), 391-404.

60. Shi, G., Rouabhia, M., Wang, Z., Dao, L. H., & Zhang, Z. (2004). A novel electrically

conductive and biodegradable composite made of polypyrrole nanoparticles and

polylactide. Biomaterials, 25(13), 2477-2488.

61. Mawad, D., Mansfield, C., Lauto, A., Perbellini, F., Nelson, G. W., Tonkin, J., ... &

Furman, J. (2016). A conducting polymer with enhanced electronic stability applied

in cardiac models. Science Advances, 2(11), e1601007.

62. Stenger-Smith, J. D. (1998). Intrinsically electrically conducting polymers.

Synthesis, characterization, and their applications. Progress in Polymer

Science, 23(1), 57-79.

63. Guo, B., & Ma, P. X. (2014). Synthetic biodegradable functional polymers for tissue

engineering: a brief review. Science China Chemistry, 57(4), 490-500.

64. Wang, X., Gu, X., Yuan, C., Chen, S., Zhang, P., Zhang, T., ... & Chen, G. (2004).

Evaluation of biocompatibility of polypyrrole in vitro and in vivo. Journal of

Biomedical Materials Research Part A, 68(3), 411-422.

149

65. Garner, B., Georgevich, A., Hodgson, A. J., Liu, L., & Wallace, G. G. (1999).

Polypyrrole–heparin composites as stimulus‐responsive substrates for endothelial

cell growth. Journal of Biomedical Materials Research Part A, 44(2), 121-129.

66. Hodgson, A. J., John, M. J., Campbell, T., Georgevich, A., Woodhouse, S., Aoki, T.,

... & Wallace, G. G. (1996, February). Integration of biocomponents with synthetic

structures: use of conducting polymer polyelectrolyte composites. In 1996

Symposium on Smart Structures and Materials (pp. 164-176). International Society

for Optics and Photonics.

67. Ateh, D. D., Vadgama, P., & Navsaria, H. A. (2006). Culture of human keratinocytes

on polypyrrole-based conducting polymers. Tissue engineering, 12(4), 645-655.

68. Castano, H., O'Rear, E. A., McFetridge, P. S., & Sikavitsas, V. I. (2004). Polypyrrole

thin films formed by admicellar polymerization support the osteogenic differentiation

of mesenchymal stem cells. Macromolecular bioscience, 4(8), 785-794.

69. Pu, Y., Li, Y., Han, Y., Yuan, C., & Wu, L. (2001). Rat keratinocyte primary cultures

based on conductive polypyrrole primary cell culture technique. Sheng wu yi xue

gong cheng xue za zhi= Journal of biomedical engineering= Shengwu yixue

gongchengxue zazhi, 18(3), 416-418.

70. Guarino, V., Zuppolini, S., Borriello, A., & Ambrosio, L. (2016). Electro-Active

Polymers (EAPs): A Promising Route to Design Bio-Organic/Bioinspired Platforms

with on Demand Functionalities. Polymers, 8(5), 185.

150

71. Xu, H., Holzwarth, J. M., Yan, Y., Xu, P., Zheng, H., Yin, Y., ... & Ma, P. X. (2014).

Conductive PPY/PDLLA conduit for peripheral nerve

regeneration. Biomaterials, 35(1), 225-235.

72. Boddula, R., & Srinivasan, P. (2014). Emeraldine Base Form of Polyaniline

Nanofibers as New, Economical, Green, and Efficient Catalyst for Synthesis of Z-

Aldoximes. Journal of Catalysts, 2014.

73. Balint, R., Cassidy, N. J., & Cartmell, S. H. (2014). Conductive polymers: towards a

smart biomaterial for tissue engineering. Acta biomaterialia, 10(6), 2341-2353.

74. Abidian, M. R., Kim, D. H., & Martin, D. C. (2006). Conducting‐polymer nanotubes

for controlled drug release. Advanced materials, 18(4), 405-409.

75. Guo, B., Sun, Y., Finne-Wistrand, A., Mustafa, K., & Albertsson, A. C. (2012).

Electroactive porous tubular scaffolds with degradability and non-cytotoxicity for

neural tissue regeneration. Acta biomaterialia, 8(1), 144-153.

76. Bose, S., Roy, M., & Bandyopadhyay, A. (2012). Recent advances in bone tissue

engineering scaffolds. Trends in biotechnology, 30(10), 546-554.

77. Durgam, H., Sapp, S., Deister, C., Khaing, Z., Chang, E., Luebben, S., & Schmidt,

C. E. (2010). Novel degradable co-polymers of polypyrrole support cell proliferation

and enhance neurite out-growth with electrical stimulation. Journal of Biomaterials

Science, Polymer Edition, 21(10), 1265-1282.

78. Lee, J. W., Serna, F., Nickels, J., & Schmidt, C. E. (2006). Carboxylic acid-

functionalized conductive polypyrrole as a bioactive platform for cell

151

adhesion. Biomacromolecules, 7(6), 1692.

79. Dai, L. (1999). Advanced syntheses and microfabrications of conjugated polymers,

C60‐containing polymers and carbon nanotubes for optoelectronic

applications. Polymers for advanced technologies, 10(7), 357-420.

80. DAI, L. (1999). Conjugated and fullerene-containing polymers for electronic and

photonic applications: advanced syntheses and microlithographic fabrications.

Macromolecular Science, Part C, 39(2), 273-387.

81. Hatamzadeh, M., Najafi-Moghadam, P., Baradar-Khoshfetrat, A., Jaymand, M., &

Massoumi, B. (2016). Novel nanofibrous electrically conductive scaffolds based on

poly (ethylene glycol) s-modified polythiophene and poly (ε-caprolactone) for tissue

engineering applications. Polymer, 107, 177-190.

82. Saeed, K., Park, S. Y., Lee, H. J., Baek, J. B., & Huh, W. S. (2006). Preparation of

electrospun nanofibers of carbon nanotube/polycaprolactone

nanocomposite. Polymer, 47(23), 8019-8025.

83. Tonelli, F. M., Santos, A. K., Gomes, K. N., Lorencon, E., Guatimosim, S., Ladeira,

L. O., & Resende, R. R. (2012). Carbon nanotube interaction with extracellular

matrix proteins producing scaffolds for tissue engineering. Int. J. Nanomed, 7(4511),

e4529.

84. Pan, L., Pei, X., He, R., Wan, Q., & Wang, J. (2012). Multiwall carbon

nanotubes/polycaprolactone composites for bone tissue engineering

application. Colloids and Surfaces B: Biointerfaces, 93, 226-234.

152

85. Paratala, B. S., & Sitharaman, B. (2011). Carbon nanotubes in regenerative medicine.

In Carbon Nanotubes for Biomedical Applications (pp. 27-39). Springer Berlin

Heidelberg.

86. Mikael, P. E., & Nukavarapu, S. P. (2011). Functionalized carbon nanotube

composite scaffolds for bone tissue engineering: prospects and progress. Journal of

Biomaterials and Tissue Engineering, 1(1), 76-85.

87. Mikael, P. E., Amini, A. R., Basu, J., Arellano-Jimenez, M. J., Laurencin, C. T.,

Sanders, M. M., ... & Nukavarapu, S. P. (2014). Functionalized carbon nanotube

reinforced scaffolds for bone regenerative engineering: fabrication, in vitro and in

vivo evaluation. Biomedical Materials, 9(3), 035001.

88. Sharma, J., Lizu, M., Stewart, M., Zygula, K., Lu, Y., Chauhan, R., ... & Wei, S.

(2015). Multifunctional nanofibers towards active biomedical

therapeutics. Polymers, 7(2), 186-219.

89. Dutta, R. C., Dey, M., Dutta, A. K., & Basu, B. (2017). Competent processing

techniques for scaffolds in tissue engineering. Biotechnology Advances, 35(2), 240-

250.

90. Abdah, M. A. A. M., Zubair, N. A., Azman, N. H. N., & Sulaiman, Y. (2017).

Fabrication of PEDOT coated PVA-GO nanofiber for supercapacitor. Materials

Chemistry and Physics, 192, 161-169.

153

91. Fan, H. S., Wang, H., Zhao, N., Xu, J., & Pan, F. (2014). Nano-porous architecture

of N-doped carbon nanorods grown on graphene to enable synergetic effects of

supercapacitance. Scientific reports, 4, 7426.

92. Golafshan, N., Kharaziha, M., & Fathi, M. (2017). Tough and conductive hybrid

graphene-PVA: Alginate fibrous scaffolds for engineering neural

construct. Carbon, 111, 752-763.

93. Qu, Y., Ao, D., Wang, P., Wang, Y., Kong, X., & Man, Y. (2014). Chitosan/nano-

hydroxyapatite composite electret membranes enhance cell proliferation and

osteoblastic expression in vitro. Journal of Bioactive and Compatible

Polymers, 29(1), 3-14.

94. Silva, E., de Vasconcellos, L. M. R., & Lobo, A. O. (2017). PDLLA honeycomb-like

scaffolds with a high loading of superhydrophilic graphene/multi-walled carbon

nanotubes promote osteoblast in vitro functions and guided in vivo bone

regeneration. Materials Science and Engineering: C, 73, 31-39.

95. Zois, H., Apekis, L., & Mamunya, Y. P. (2003). Dielectric properties and morphology

of polymer composites filled with dispersed iron. Journal of Applied Polymer

Science, 88(13), 3013-3020.

96. Huang, J. C. (2002). Carbon black filled conducting polymers and polymer

blends. Advances in Polymer Technology, 21(4), 299-313.

97. Kaur, G., Adhikari, R., Cass, P., Bown, M., & Gunatillake, P. (2015). Electrically

conductive polymers and composites for biomedical applications. RSC

154

Advances, 5(47), 37553-37567.

98. Brigandi, P. J., Cogen, J. M., & Pearson, R. A. (2014). Electrically conductive

multiphase polymer blend carbon‐based composites. Polymer Engineering &

Science, 54(1), 1-16.

99. Tanasa, F., Zanoaga, M., & Mamunya, Y. (2015). CONDUCTIVE

THERMOPLASTIC POLYMER NANOCOMPOSITES WITH ULTRALOW

PERCOLATION THRESHOLD. Scientific Research & Education in the Air Force-

AFASES, 2.

100. Stankovich, S., Dikin, D. A., & Ruoff, R. S. (2006). Graphene-based composite

materials. nature, 442(7100), 282-286.

101. Fraczek-Szczypta, A., Stodolak-Zych, E., Jurdziak, S., & Blazewicz, M. (2012).

Polymer Nanocomposite Scaffolds Modified With Carbon Nanotubes for Tissue

Regeneration. In Materials Science Forum (Vol. 714, pp. 245-253). Trans Tech

Publications.

102. Firkowska, I. and Polczyn Z. (2009) Carbon Nanotube Substrates for Tissue

Applications: Analysis of surface nanotopography, cellular adhesion, and elasticity.

Diss. Rheinischen Friedrich-Wilhelms-Universität. Bonn: Rheinischen Friedrich-

Wilhelms-Universität.

103. Kolambkar, Y. M., Bajin, M., Wojtowicz, A., Hutmacher, D. W., García, A. J., &

Guldberg, R. E. (2013). Nanofiber orientation and surface functionalization modulate

human mesenchymal stem cell behavior in vitro. Tissue Engineering Part A, 20(1-2),

398-409.

155

104. Koh, B., & Cheng, W. (2015). The Impact of Sonication on the Surface Quality of

Single‐Walled Carbon Nanotubes. Journal of pharmaceutical sciences, 104(8), 2594-

2599.

105. Shi, X., Sitharaman, B., Pham, Q. P., Liang, F., Wu, K., Billups, W. E., ... & Mikos,

A. G. (2007). Fabrication of porous ultra-short single-walled carbon nanotube

nanocomposite scaffolds for bone tissue engineering. Biomaterials, 28(28), 4078-

4090.

106. Xu, P., Loomis, J., King, B., & Panchapakesan, B. (2012). Synergy among binary

(MWNT, SLG) nano-carbons in polymer nano-composites: a Raman

study. Nanotechnology, 23(31), 315706.

107. Song, Z., Yang, Z., Yang, J., Liu, Z., Peng, Z., Tang, R., & Gu, Y. (2013). Repair of

abdominal wall defects in vitro and in vivo using VEGF sustained-release multi-

walled carbon nanotubes (MWNT) composite scaffolds. PloS one, 8(5), e64358.

108. Dai, J. F., Wang, G. J., Ma, L., & Wu, C. K. (2015). Surface properties of graphene:

relationship to graphene-polymer composites. Rev. Adv. Mater. Sci, 40, 60-71.

109. Abdal-hay, A., Khalil, K. A., Hamdy, A. S., & Al-Jassir, F. F. (2017). Fabrication of

highly porous biodegradable biomimetic nanocomposite as advanced bone tissue

scaffold. Arabian Journal of Chemistry, 10(2), 240-252.

110. Nayak, T. R., Andersen, H., Makam, V. S., Khaw, C., Bae, S., Xu, X., ... & Özyilmaz,

B. (2011). Graphene for controlled and accelerated osteogenic differentiation of

human mesenchymal stem cells. arXiv preprint arXiv:1104.5120.

156

111. Potas, J. R., Haque, F., Maclean, F. L., & Nisbet, D. R. (2015). Interleukin-10

conjugated electrospun polycaprolactone (PCL) nanofibre scaffolds for promoting

alternatively activated (M2) macrophages around the peripheral nerve in

vivo. Journal of immunological methods, 420, 38-49.

112. Abdal-hay, A., Hamdy, A. S., & Khalil, K. A. (2015). Fabrication of durable high-

performance hybrid nanofiber scaffolds for bone tissue regeneration using a novel,

simple in situ deposition approach of polyvinyl alcohol on electrospun nylon 6

nanofibers. Materials Letters, 147, 25-28.

113. Abdal-Hay, A., Oh, Y. S., Yousef, A., Pant, H. R., Vanegas, P., & Lim, J. K. (2014).

In vitro deposition of Ca-P nanoparticles on air jet spinning Nylon 6 nanofibers

scaffold for bone tissue engineering. Applied Surface Science, 307, 69-76.

114. Harilall, S. L., Choonara, Y. E., Tomar, L. K., Tyagi, C., Kumar, P., du Toit, L. C.,

... & Pillay, V. (2015). Development and in vivo evaluation of an implantable nano-

enabled multipolymeric scaffold for the management of AIDS dementia complex

(ADC). International journal of pharmaceutics, 496(2), 863-877.

115. Béchard, S. R., Levy, L., & Clas, S. D. (1995). Thermal, mechanical and functional

properties of cellulose acetate phthalate (CAP) coatings obtained from neutralized

aqueous solutions. International Journal of Pharmaceutics, 114(2), 205-213.

116. Ma, L., Zhao, J., Wang, X., Chen, M., Liang, Y., Wang, Z., ... & Hedden, R. C.

(2015). Effects of carbon black nanoparticles on two-way reversible shape memory

in crosslinked polyethylene. Polymer, 56, 490-497.

157

117. Ravichandran, R., Venugopal, J. R., Sundarrajan, S., Mukherjee, S., & Ramakrishna,

S. (2013). Cardiogenic differentiation of mesenchymal stem cells on elastomeric poly

(glycerol sebacate)/collagen core/shell fibers. World J Cardiol, 5(3), 28-41.

118. McCool, J. M., Rodriguez, I. A., Sell, S. A., Han, Y., & Bowlin, G. L. (2014). A

preliminary study on amelogenin-loaded electrospun scaffolds. Journal of Bioactive

and Compatible Polymers, 29(1), 32-49.

119. Lai, G. J., Shalumon, K. T., & Chen, J. P. (2015). Response of human mesenchymal

stem cells to intrafibrillar nanohydroxyapatite content and extrafibrillar

nanohydroxyapatite in biomimetic chitosan/silk fibroin/nanohydroxyapatite

nanofibrous membrane scaffolds. International journal of nanomedicine, 10, 567.

120. Debelak, B., & Lafdi, K. (2007). Use of exfoliated graphite filler to enhance polymer

physical properties. Carbon, 45(9), 1727-1734.

121. Wikipedia. (2017). Graphene. Retrieved from https://en.wikipedia.org/wiki/Graphene.

122. Huang, X. (2009). Fabrication and properties of carbon fibers. Materials, 2(4), 2369-

2403.

123. Lu, W., Zu, M., Byun, J. H., Kim, B. S., & Chou, T. W. (2012). State of the art of

carbon nanotube fibers: opportunities and challenges. Advanced materials, 24(14),

1805-1833.

124. Rodriguez, N. M. (1993). A review of catalytically grown carbon nanofibers. Journal

of materials research, 8(12), 3233-3250.

125. Donnet, J. B. (Ed.). (1993). Carbon black: science and technology. CRC Press.

158

126. Suryanto, B. H., & Zhao, C. (2016). Surface-oxidized carbon black as a catalyst for

the water oxidation and alcohol oxidation reactions. Chemical

Communications, 52(38), 6439-6442.

127. Mitsubishi Chemical Corporation. (2006). Three Main Properties of Carbon Black.

Retrieved from http://www.carbonblack.jp/en/cb/tokusei.html.

128. Cueto, E., Ma, A. W. K., Chinesta, F., & Mackley, M. R. (2008). Numerical

simulation of spin coating processes involving functionalised carbon nanotube

suspensions. International Journal of Material Forming, 1(2), 89.

129. Toolan, D. T., & Howse, J. R. (2013). Development of in situ studies of spin coated

polymer films. Journal of Materials Chemistry C, 1(4), 603-616.

130. Leng, Y. (2009). Materials characterization: introduction to microscopic and

spectroscopic methods. John Wiley & Sons.

131. Rigaku Corporation and its Global Subsidiaries. (2017). Intelligent X-ray diffraction

(XRD) system. Retrieved from https://www.rigaku.com/en/products/xrd/smartlab.

132. Inphotonics. (1999). An Introduction to Raman for the Infrared Spectroscopist.

Technical Note #11. Retrieved from http://www.inphotonics.com/technote11.pdf

133. Izwan B., M. (2014). Raman Spectrometer (Renishaw InVia Raman Microscope).

Science and Engineering Research Centre (SERC). Retrieved from

http://serc.eng.usm.my/index.php/en/shared-facilities-instruments/shared-research-

instruments/71-raman-spectrometer-renishaw-invia-raman-microscope.

159

134. Swapp, S. (2017, April 30). Scanning Electron Microscopy (SEM). University of

Wyoming. Retrieved from

http://serc.carleton.edu/research_education/geochemsheets/techniques/SEM.htl

https://www.phenom-world.com/microscopes/phenom-prox.

136. LinkedIn Corporation. (2015, July 6). Inverted fluorescence microscope MF53/ MF50.

Retrieved from https://www.slideshare.net/microshot/inverted-fluorescence-

microscope-mf53-mf50.

137. Al-Saleh, M. H., & Sundararaj, U. (2011). Review of the mechanical properties of

carbon nanofiber/polymer composites. Composites Part A: Applied Science and

Manufacturing, 42(12), 2126-2142.

138. Bortz, D. R., Merino, C., & Martin-Gullon, I. (2011). Carbon nanofibers enhance the

fracture toughness and fatigue performance of a structural epoxy system. Composites

Science and Technology, 71(1), 31-38.

139. Bal, S. (2010). Experimental study of mechanical and electrical properties of carbon

nanofiber/epoxy composites. Materials & Design (1980-2015), 31(5), 2406-2413.

140. Lu, H., Liu, Y., Gou, J., Leng, J., & Du, S. (2010). Synergistic effect of carbon

nanofiber and carbon nanopaper on shape memory polymer composite. Applied

Physics Letters, 96(8), 084102.

141. Huang, Y. C., & Huang, Y. Y. (2006). Tissue engineering for nerve

repair. Biomedical Engineering: Applications, Basis and Communications, 18(03),

100-110. 160

142. Janković, B., Pelipenko, J., Škarabot, M., Muševič, I., & Kristl, J. (2013). The design

trend in tissue-engineering scaffolds based on nanomechanical properties of

individual electrospun nanofibers. International journal of pharmaceutics, 455(1),

338-347.

143. Markowski, J., Magiera, A., Lesiak, M., Sieron, A. L., Pilch, J., & Blazewicz, S.

(2015). Preparation and characterization of nanofibrous polymer scaffolds for

cartilage tissue engineering. Journal of Nanomaterials, 16(1), 45.

144. Discher, D. E., Mooney, D. J., & Zandstra, P. W. (2009). Growth factors, matrices,

and forces combine and control stem cells. Science, 324(5935), 1673-1677.

145. Reilly, G. C., & Engler, A. J. (2010). Intrinsic extracellular matrix properties regulate

stem cell differentiation. Journal of biomechanics, 43(1), 55-62.

146. Lee, C., Wei, X., Kysar, J. W., & Hone, J. (2008). Measurement of the elastic

properties and intrinsic strength of monolayer graphene. science, 321(5887), 385-

388.

147. Zhang, Y. Z., Venugopal, J., Huang, Z. M., Lim, C. T., & Ramakrishna, S. (2005).

Characterization of the surface biocompatibility of the electrospun PCL-collagen

nanofibers using fibroblasts. Biomacromolecules, 6(5), 2583-2589.

148. Hashin, Z., & Shtrikman, S. (1963). A variational approach to the theory of the elastic

behaviour of multiphase materials. Journal of the Mechanics and Physics of

Solids, 11(2), 127-140.

149. Beran, M., & Molyneux, J. (1966). Use of classical variational principles to

161

determine bounds for the effective bulk modulus in heterogeneous media. Quarterly

of Applied Mathematics, 24(2), 107-118.

150. Bergström, J. S., & Boyce, M. C. (1998). Constitutive modeling of the large strain

time-dependent behavior of elastomers. Journal of the Mechanics and Physics of

Solids, 46(5), 931-954.

151. Naito, M., Muraoka, K., Azuma, K., & Tomita, Y. (2008). 3D modeling and

simulation of micro-to macroscopic deformation behavior of filled rubber.

In CONSTITUTIVE MODELS FOR RUBBER-PROCEEDINGS- (Vol. 5, p. 127).

Balkema.

152. Laiarinandrasana, L., Meo, S., and Verron, E., Eds., Proc. of the 5th European Confer.

On Consitutive Models for Rubber, Paris, France, 4-7 Sept 2007, pp. 141–146,

London, Taylor and Francis, 2007.

153. Jean, A. (2011). Large scale computations of effective elastic properties of rubber

with carbon black fillers. International Journal for Multiscale Computational

Engineering.

154. Djebara, Y., El Moumen, A., Kanit, T., Madani, S., & Imad, A. (2016). Modeling of

the effect of particles size, particles distribution and particles number on mechanical

properties of polymer-clay nano-composites: Numerical homogenization versus

experimental results. Composites Part B: Engineering, 86, 135-142.

155. Omnès, B., Thuillier, S., Pilvin, P., Grohens, Y., & Gillet, S. (2008). Effective

properties of carbon black filled natural rubber: experiments and

162

modeling. Composites Part A: Applied Science and Manufacturing, 39(7), 1141-

1149.

156. Laiarinandrasana, L., Jean, A., Jeulin, D., & Forest, S. (2012). Modelling the effects

of various contents of fillers on the relaxation rate of elastomers. Materials &

Design, 33, 75-82.

157. Heidenreich, R. D., Hess, W. M., & Ban, L. L. (1968). A test object and criteria for

high resolution electron microscopy. Journal of Applied Crystallography, 1(1), 1-19.

158. Mori, T., & Tanaka, K. (1973). Average stress in matrix and average elastic energy

of materials with misfitting inclusions. Acta metallurgica, 21(5), 571-574.

159. Smallwood, H. M. (1944). Limiting law of the reinforcement of rubber. Journal of

applied physics, 15(11), 758-766.

160. Guth, E., & Gold, O. (1938). On the hydrodynamical theory of the viscosity of

suspensions. Phys. Rev, 53(322), 2-15.

161. Milton, G. W. (1981). Bounds on the electromagnetic, elastic, and other properties of

two-component composites. Physical Review Letters, 46(8), 542.

162. Torquato, S. (1991). Random heterogeneous media: microstructure and improved

bounds on effective properties. Appl. Mech. Rev, 44(2), 37-76.

163. Jeulin, D., & Ostoja-Starzewski, M. (Eds.). (2001). Mechanics of random and

multiscale microstructures (pp. 33-91). Wien-New York: Springer.

164. Christensen, R. M., & Lo, K. H. (1979). Solutions for effective shear properties in

three phase sphere and cylinder models. Journal of the Mechanics and Physics of

163

Solids, 27(4), 315-330.

165. Ma, H., Hu, G., & Huang, Z. (2004). A micromechanical method for particulate

composites with finite particle concentration. Mechanics of Materials, 36(4), 359-

368.

166. Jean, A., Jeulin, D., Forest, S., Cantournet, S., & N'GUYEN, F. (2011). A multiscale

microstructure model of carbon black distribution in rubber. Journal of

microscopy, 241(3), 243-260.

167. El Moumen, A., Kanit, T., Imad, A., & Minor, H. E. (2013). Effect of overlapping

inclusions on effective elastic properties of composites. Mechanics Research

Communications, 53, 24-30.

168. El Moumen, A., Kanit, T., Imad, A., & El Minor, H. (2015). Effect of reinforcement

shape on physical properties and representative volume element of particles-

reinforced composites: statistical and numerical approaches. Mechanics of

Materials, 83, 1-16.

169. El Moumen, A., Kanit, T., Imad, A., & El Minor, H. (2015). Computational thermal

conductivity in porous materials using homogenization techniques: Numerical and

statistical approaches. Computational Materials Science, 97, 148-158.

170. De La Fuente, J. (2017, April 19). Graphene Applications & Uses Retrieved from

https://www.graphenea.com/pages/graphene-properties#.WOUkgIjytaQ.

171. Liu, Y., Xie, B., Zhang, Z., Zheng, Q., & Xu, Z. (2012). Mechanical properties of

graphene papers. Journal of the Mechanics and Physics of Solids, 60(4), 591-605.

164

172. Khodaverdi, F., Hemati, M., Shekarian, E., Tarighaleslami, A.H. (2014).

Morphology, Thermal and Mechanical properties of carbon Black/High Density

Polyethylene (CB/HDPE) Composite. Advances in Environmental Biology, 8(11),

1262-65.

173. Heidenreich, R. D., Hess, W. M., & Ban, L. L. (1968). A test object and criteria for

high resolution electron microscopy. Journal of Applied Crystallography, 1(1), 1-19.

174. Das, N. C., Khastgir, D., Chaki, T. K., & Chakraborty, A. (2000). Electromagnetic

interference shielding effectiveness of carbon black and carbon fibre filled EVA and

NR based composites. Composites part A: applied science and

manufacturing, 31(10), 1069-1081.

175. Cappa, C. D., Onasch, T. B., Massoli, P., Worsnop, D. R. et al. (2012). Radiative

absorption enhancements due to the mixing state of atmospheric black

carbon. Science, 337(6098), 1078-1081.

176. Hu, C. C., Chang, S. S., & Liang, N. Y. (2016). Preparation and characterization of

carbon black/polybutylene terephthalate/polyethylene terephthalate antistatic fiber

with sheath–core structure. The Journal of The Textile Institute, 107(8), 976-984.

177. Yin, X., Capsal, J. F., & Guyomar, D. (2014). A comprehensive investigation of

poly (vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) terpolymer

nanocomposites with carbon black for electrostrictive applications. Applied

Physics Letters, 104(5), 052913.

178. Al-Saleh, M. H., Saadeh, W. H., & Sundararaj, U. (2013). EMI shielding

effectiveness of carbon based nanostructured polymeric materials: a comparative

165

study. Carbon, 60, 146-156.

179. Rodriguez, N. M. (1993). A review of catalytically grown carbon

nanofibers. Journal of materials research, 8(12), 3233-3250.

180. Fei, L., Williams, B. P., Yoo, S. H., Carlin, J. M., & Joo, Y. L. (2016). A general

approach to fabricate free-standing metal sulfide@ carbon nanofiber networks as

lithium ion battery anodes. Chemical Communications, 52(7), 1501-1504.

181. Li, Y., Zou, B., Hu, C., & Cao, M. (2016). Nitrogen-doped porous carbon

nanofiber webs for efficient CO 2 capture and conversion. Carbon, 99, 79-89.

182. US Pat. (2016). US20160024262A1.

183. D'Alessandro, A., Pisello, A. L., Sambuco, S., Ubertini, F., Asdrubali, F.,

Materazzi, A. L., & Cotana, F. (2016, April). Self-sensing and thermal energy

experimental characterization of multifunctional cement-matrix composites with

carbon nano-inclusions. In SPIE Smart Structures and Materials+

Nondestructive Evaluation and Health Monitoring (pp. 98000Z-98000Z).

International Society for Optics and Photonics.

184. Novoselov, K. S., Geim, A. K., & Firsov, A. A. (2004). Electric field effect in

atomically thin carbon films. science, 306(5696), 666-669.

185. Liu, H., Kameoka, J., Czaplewski, D. A., & Craighead, H. G. (2004). Polymeric

nanowire chemical sensor. Nano letters, 4(4), 671-675.

186. Harfenist, S. A., Cambron, S. D., Nelson, E. W., Berry, S. M. et al. (2004). Direct

drawing of suspended filamentary micro-and nanostructures from liquid

166

polymers. Nano Letters, 4(10), 1931-1937.

187. Chen, I. H., Wang, C. C., & Chen, C. Y. (2010). Fabrication and structural

characterization of polyacrylonitrile and carbon nanofibers containing plasma-

modified carbon nanotubes by electrospinning. The Journal of Physical

Chemistry C, 114(32), 13532-13539.

188. Coleman, J. N., Khan, U., Blau, W. J., & Gun’ko, Y. K. (2006). Small but strong:

a review of the mechanical properties of carbon nanotube–polymer

composites. Carbon, 44(9), 1624-1652.

189. Wang, J. N., Zhao, Y. Z., & Niu, J. J. (2007). Preparation of graphitic carbon

with high surface area and its application as an electrode material for fuel

cells. Journal of Materials Chemistry, 17(21), 2251-2256.

190. Winter, M., & Besenhard, J. O. (1999). Lithiated Carbons, Handbook of Battery

Materials, ed J. O. Besenhard, Wiley-VCH Verlag GmbH, Weinheim, Germany,

17, DOI: 10.1002/9783527611676.

191. Hess, M., Lebraud, E., & Levasseur, A. (1997). Graphite multilayer thin films: a

new anode material for Li-ion microbatteries synthesis and

characterization. Journal of power sources, 68(2), 204-207.

192. Alig, I., Lellinger, D., Engel, M., Skipa, T., & Pötschke, P. (2008). Destruction

and formation of a conductive carbon nanotube network in polymer melts: In-

line experiments. Polymer, 49(7), 1902-1909.

193. Gelves, G. A., Al-Saleh, M. H., & Sundararaj, U. (2011). Highly electrically

167

conductive and high-performance EMI shielding nanowire/polymer

nanocomposites by miscible mixing and precipitation. Journal of Materials

Chemistry, 21(3), 829-836.

194. Alig, I., Potschke, P., Pegel, S., Dudkin, S., & Lellinger, D. (2007). Verbunde

von Kunststoffen mit Kohlenstoff-Nanorohren (Carbon Nanotubes). Gummi

Fasern Kunststoffe, 60(5), 280-283.

195. Muñoz, E., Suh, D. S., Collins, S., Selvidge, M., Dalton, A. B. et al. (2005).

Highly conducting carbon nanotube/polyethyleneimine composite

fibers. Advanced Materials, 17(8), 1064-1067.

196. Skakalova, V., Dettlaff-Weglikowska, U., & Roth, S. (2005). Electrical and

mechanical properties of nanocomposites of single wall carbon nanotubes with

PMMA. Synthetic metals, 152(1-3), 349-352.

197. Feng, C., & Jiang, L. (2013). Micromechanics modeling of the electrical

conductivity of carbon nanotube (CNT)–polymer nanocomposites. Composites

Part A: Applied Science and Manufacturing, 47, 143-149.

198. Seidel, G. D., & Lagoudas, D. C. (2009). A micromechanics model for the

electrical conductivity of nanotube-polymer nanocomposites. Journal of

Composite Materials, 43(9), 917-941.

199. Wang, Z., & Ye, X. (2013). A numerical investigation on piezoresistive

behaviour of carbon nanotube/polymer composites: mechanism and optimizing

principle. Nanotechnology, 24(26), 265704.

168

200. Vargas-Bernal, R., Herrera-Pérez, G., Calixto-Olalde, M. E., & Tecpoyotl-

Torres, M. (2013). Analysis of DC electrical conductivity models of carbon

nanotube-polymer composites with potential application to nanometric electronic

devices. Journal of Electrical and Computer Engineering, 2013.

201. Li, C., Thostenson, E. T., & Chou, T. W. (2007). Dominant role of tunneling

resistance in the electrical conductivity of carbon nanotube–based

composites. Applied Physics Letters, 91(22), 223114.

202. Morishita, T., Matsushita, M., Katagiri, Y., & Fukumori, K. (2011). A novel

morphological model for carbon nanotube/polymer composites having high

thermal conductivity and electrical insulation. Journal of Materials

Chemistry, 21(15), 5610-5614.

203. Dalmas, F., Dendievel, R., Chazeau, L., Cavaillé, J. Y., & Gauthier, C. (2006).

Carbon nanotube-filled polymer composites. Numerical simulation of electrical

conductivity in three-dimensional entangled fibrous networks. Acta

materialia, 54(11), 2923-2931.

204. Tripol’skii, A. I., Serebrii, T. G., Lemesh, N. V., Khavrus’, V. A., Ivashchenko,

T. S., & Strizhak, P. E. (2009). Fractal analysis of carbon nanotube agglomerates

obtained by chemical vapor decomposition of ethylene over nickel

nanoparticles. Theoretical and Experimental Chemistry, 45(2), 103-107.

205. Vera‐Reveles, G., Simón, J., Briones, E., & González, F. J. (2012). Single walled

carbon nanotube bolometer coupled to a Sierpinski fractal antenna for the

detection of megahertz radiation. Microwave and Optical Technology

169

Letters, 54(5), 1251-1253.

206. Chiang, Y. C., & Lee, C. Y. (2009). Changes in material properties and surface

fractality of multi-walled carbon nanotubes modified by heat and acid

treatments. Journal of materials science, 44(11), 2780-2791.

207. Yin, Y., Zhang, T., Yang, F., & Qiu, X. (2008). Geometric conditions for fractal

super carbon nanotubes with strict self-similarities. Chaos, Solitons &

Fractals, 37(5), 1257-1266.

208. Lu, H., & Min Huang, W. (2013). Synergistic effect of self-assembled carboxylic

acid-functionalized carbon nanotubes and carbon fiber for improved electro-

activated polymeric shape-memory nanocomposite. Applied Physics

Letters, 102(23), 231910.

209. Lu, H., Yao, Y., & Lin, L. (2013). Carbon-based reinforcement in shape-memory

polymer composite for electrical actuation. Pigment & Resin Technology, 43(1),

26-34.

210. Liu, L., Wang, Z., Feng, J., & Ye, X. (2013). Benzene sensors based on multi-

walled carbon nanotube networks decorated with metal nanoclusters. Journal of

nanoscience and nanotechnology, 13(2), 989-992.

211. Severin, E. J., Doleman, B. J., & Lewis, N. S. (2000). An investigation of the

concentration dependence and response to analyte mixtures of carbon

black/insulating organic polymer composite vapor detectors. Analytical

chemistry, 72(4), 658-668.

212. Feller, J. F., Guézénoc, H., Bellégou, H., & Grohens, Y. (2005, March). Smart 170

poly (styrene)/carbon black conductive polymer composites films for styrene

vapour sensing. In Macromolecular Symposia (Vol. 222, No. 1, pp. 273-280).

WILEY‐VCH Verlag.

213. Wang, Z. F., Yang, J. M., Ye, X. Y., Liu, L. T., & Xie, X. M. (2011).

Characterization of contact and bulk piezoresistive properties of carbon

nanotube/styrene-butadiene-styrene composite. In Key Engineering

Materials (Vol. 483, pp. 537-541). Trans Tech Publications.

214. Ansari, S., & Giannelis, E. P. (2009). Functionalized graphene sheet—Poly

(vinylidene fluoride) conductive nanocomposites. Journal of Polymer Science

Part B: Polymer Physics, 47(9), 888-897.

215. Wang, F., Gu, H., & Swager, T. M. (2008). Carbon nanotube/polythiophene

chemiresistive sensors for chemical warfare agents. Journal of the American

Chemical Society, 130(16), 5392-5393.

216. Becerril, H. A., Mao, J., Liu, Z., Stoltenberg, R. M., Bao, Z., & Chen, Y. (2008).

Evaluation of solution-processed reduced graphene oxide films as transparent

conductors. ACS nano, 2(3), 463-470.

217. Hu, Y., Zhao, T., Zhu, P., Zhu, Y., Shuai, X., Liang, X., ... & Wong, C. P. (2016).

Low cost and highly conductive elastic composites for flexible and printable

electronics. Journal of Materials Chemistry C, 4(24), 5839-5848.

218. Georgakilas, V., Tiwari, J. N., Kemp, K. C., Perrnan, J. A., Bourlinos, A. B.,

Kim, K. S., & Zboril, R. (2016). Noncovalent functionalization of graphene and

graphene oxide for energy materials, biosensing, catalytic, and biomedical

171

applications.

219. Debelak, B., & Lafdi, K. (2007). Use of exfoliated graphite filler to enhance

polymer physical properties. Carbon, 45(9), 1727-1734.

220. Park, M. S., Joo, W., & Kim, J. K. (2006). Porous structures of polymer films

prepared by spin coating with mixed solvents under humid

condition. Langmuir, 22(10), 4594-4598.

221. Kirkpatrick, S. (1973). Percolation and conduction. Reviews of modern

physics, 45(4), 574.

222. Wang, Y., Alsmeyer, D. C., & McCreery, R. L. (1990). Raman spectroscopy of

carbon materials: structural basis of observed spectra. Chemistry of

Materials, 2(5), 557-563.

223. Tuinstra, F., & Koenig, J. L. (1970). Raman spectrum of graphite. The Journal

of Chemical Physics, 53(3), 1126-1130.

224. Jawhari, T., Roid, A., & Casado, J. (1995). Raman spectroscopic characterization

of some commercially available carbon black materials. Carbon, 33(11), 1561-

1565.

225. Chen, P. H., & Chung, D. D. L. (2014). Thermal and electrical conduction in the

compaction direction of exfoliated graphite and their relation to the

structure. Carbon, 77, 538-550.

226. Endo, M., Koyama, T., & Hishiyama, Y. (1976). Structural improvement of

carbon fibers prepared from benzene. Japanese Journal of Applied

172

Physics, 15(11), 2073.

227. Rey-Raap, N., Calvo, E. G., Bermúdez, J. M., Cameán, I., García, A. B.,

Menéndez, J. A., & Arenillas, A. (2014). An electrical conductivity translator for

carbons. Measurement, 56, 215-218.

228. Guadagno, L., Raimondo, M., Vittoria, V., Vertuccio, L., Lafdi, K., De Vivo, B.

et al. (2013). The role of carbon nanofiber defects on the electrical and

mechanical properties of CNF-based resins. Nanotechnology, 24(30), 305704.

229. Czarnecki, J. S., Blackmore, M., Jolivet, S., Lafdi, K., & Tsonis, P. A. (2014). Bone

growth on Reticulated Vitreous Carbon foam scaffolds and implementation of

Cellular Automata modeling as a predictive tool. Carbon, 79, 135-148.

230. Dorati, R., Colonna, C., Genta, I., & Conti, B. (2011). Polymer scaffolds for bone

tissue regeneration. In Active implants and scaffolds for tissue regeneration (pp. 259-

285). Springer Berlin Heidelberg.

231. Ravichandran, R., Venugopal, J. R., Sundarrajan, S., Mukherjee, S., & Ramakrishna,

S. (2013). Cardiogenic differentiation of mesenchymal stem cells on elastomeric poly

(glycerol sebacate)/collagen core/shell fibers. World J Cardiol, 5(3), 28-41.

232. McCool, J. M., Rodriguez, I. A., Sell, S. A., Han, Y., & Bowlin, G. L. (2014). A

preliminary study on amelogenin-loaded electrospun scaffolds. Journal of Bioactive

and Compatible Polymers, 29(1), 32-49.

233. Lai, G. J., Shalumon, K. T., & Chen, J. P. (2015). Response of human mesenchymal

stem cells to intrafibrillar nanohydroxyapatite content and extrafibrillar

173

nanohydroxyapatite in biomimetic chitosan/silk fibroin/nanohydroxyapatite

nanofibrous membrane scaffolds. International journal of nanomedicine, 10, 567.

234. Ghasemi-Mobarakeh, L., Prabhakaran, M. P., Morshed, M., Nasr-Esfahani, M. H., &

Ramakrishna, S. (2009). Electrical stimulation of nerve cells using conductive

nanofibrous scaffolds for nerve tissue engineering. Tissue Engineering Part

A, 15(11), 3605-3619.

235. Li, M., Guo, Y., Wei, Y., MacDiarmid, A. G., & Lelkes, P. I. (2006). Electrospinning

polyaniline-contained gelatin nanofibers for tissue engineering

applications. Biomaterials, 27(13), 2705-2715.

236. Jeong, S. I., Jun, I. D., Choi, M. J., Nho, Y. C., Lee, Y. M., & Shin, H. (2008).

Development of Electroactive and Elastic Nanofibers that contain Polyaniline and

Poly (L‐lactide‐co‐ε‐caprolactone) for the Control of Cell

Adhesion. Macromolecular bioscience, 8(7), 627-637.

237. Li, C., Hsu, Y. T., & Hu, W. W. (2016). The Regulation of Osteogenesis Using

Electroactive Polypyrrole Films. Polymers, 8(7), 258.

238. Liu, Y., Hu, J., Zhuang, X., Zhang, P., Chen, X., Wei, Y., & Wang, X. (2011).

Preparation and characterization of biodegradable and electroactive polymer blend

materials based on mPEG/tetraaniline and PLLA. Macromolecular

bioscience, 11(6), 806-813.

239. Bendrea, A. D., Cianga, L., & Cianga, I. (2011). Review paper: progress in the field

of conducting polymers for tissue engineering applications. Journal of biomaterials

174

applications, 26(1), 3-84.

240. Silva, G. A. (2006). Neuroscience nanotechnology: progress, opportunities and

challenges. Nature Reviews Neuroscience, 7(1), 65-74.

241. Nayak, T. R., Andersen, H., Makam, V. S., & Özyilmaz, B. (2011). Graphene for

controlled and accelerated osteogenic differentiation of human mesenchymal stem

cells. arXiv preprint arXiv:1104.5120.

242. Bajaj, P., Khang, D., & Webster, T. J. (2006). Control of spatial cell attachment on

carbon nanofiber patterns on polycarbonate urethane. international Journal of

nanomedicine, 1(3), 361.

243. Menaa, F., Abdelghani, A., & Menaa, B. (2015). Graphene nanomaterials as

biocompatible and conductive scaffolds for stem cells: impact for tissue engineering

and regenerative medicine. Journal of tissue engineering and regenerative

medicine, 9(12), 1321-1338.

244. Fan, H., Wang, L., Zhao, K., Li, N., Shi, Z., Ge, Z., & Jin, Z. (2010). Fabrication,

mechanical properties, and biocompatibility of graphene-reinforced chitosan

composites. Biomacromolecules, 11(9), 2345-2351.

245. Naofumi, A. O. K. I., Akasaka, T., Watari, F., & Yokoyama, A. (2007). Carbon

nanotubes as scaffolds for cell culture and effect on cellular functions. Dental

materials journal, 26(2), 178-185.

246. Donnet, J. B. (Ed.). (1993). Carbon black: science and technology. CRC Press.

247. Ivan, C. (1963). U.S. Patent No. 3,073,681. Washington, DC: U.S. Patent and

175

Trademark Office.

248. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans (2010)

Carbon Black, Titanium Dioxide, and Talc, world health organization international

agency for research on cancer 39:43-191.

249. Feng, L., Xie, N., & Zhong, J. (2014). Carbon nanofibers and their composites: a

review of synthesizing, properties and applications. Materials, 7(5), 3919-3945.

250. Tibbetts, G. G. (1989). Vapor-grown carbon fibers: status and

prospects. Carbon, 27(5), 745-747.

251. Wangxi, Z., Jie, L., & Gang, W. (2003). Evolution of structure and properties of PAN

precursors during their conversion to carbon fibers. Carbon, 41(14), 2805-2812.

252. Vilaplana, J. L., Baeza, F. J., Galao, O., Zornoza, E., & Garcés, P. (2013). Self-

sensing properties of alkali activated blast furnace slag (BFS) composites reinforced

with carbon fibers. Materials, 6(10), 4776-4786.

253. Baeza, F. J., Galao, O., Zornoza, E., & Garcés, P. (2013). Multifunctional cement

composites strain and damage sensors applied on reinforced concrete (RC) structural

elements. Materials, 6(3), 841-855.

254. Geim, A. K., & Novoselov, K. S. (2007). The rise of graphene. Nature

materials, 6(3), 183-191.

255. Wang, X., & Shi, Y. (2014). Fabrication Techniques of Graphene Nanostructures.

Royal society of chemistry, doi:10.1039/9781782623380-00001.

176

256. Krane, N. (2011). Preparation of graphene. Selected Topics in Physics: Physics of the

Nanoscale.

257. Yang, F., Murugan, R., Wang, S., & Ramakrishna, S. (2005). Electrospinning of

nano/micro scale poly (L-lactic acid) aligned fibers and their potential in neural tissue

engineering. Biomaterials, 26(15), 2603-2610.

258. Sharma, A. D., Zbarska, S., Petersen, E. M., Marti, M. E., Mallapragada, S. K., &

Sakaguchi, D. S. (2016). Oriented growth and transdifferentiation of mesenchymal

stem cells towards a Schwann cell fate on micropatterned substrates. Journal of

bioscience and bioengineering, 121(3), 325-335.

259. Miller, C., Shanks, H., Witt, A., Rutkowski, G., & Mallapragada, S. (2001). Oriented

Schwann cell growth on micropatterned biodegradable polymer

substrates. Biomaterials, 22(11), 1263-1269.

260. Rutkowski, G. E., Miller, C. A., Jeftinija, S., & Mallapragada, S. K. (2004).

Synergistic effects of micropatterned biodegradable conduits and Schwann cells on

sciatic nerve regeneration. Journal of Neural Engineering, 1(3), 151.

261. Zou, Y., Qin, J., Huang, Z., Yin, G., Pu, X., & He, D. (2016). Fabrication of Aligned

Conducting PPy-PLLA Fiber Films and Their Electrically Controlled Guidance and

Orientation for Neurites. ACS applied materials & interfaces, 8(20), 12576-12582.

262. Kotwal, A., & Schmidt, C. E. (2001). Electrical stimulation alters protein adsorption

and nerve cell interactions with electrically conducting

biomaterials. Biomaterials, 22(10), 1055-1064.

263. Ciombor, D. M., & Aaron, R. K. (1993). Influence of electromagnetic fields on 177

endochondral bone formation. Journal of cellular biochemistry, 52(1), 37-41.

264. Aaron, R. K., & Ciombor, D. M. (1993). Therapeutic effects of electromagnetic fields

in the stimulation of connective tissue repair. Journal of cellular biochemistry, 52(1),

42-46.

265. Goldman, R., & Pollack, S. (1996). Electric fields and proliferation in a chronic

wound model. Bioelectromagnetics, 17(6), 450-457.

266. Politis, M. J., & Zanakis, M. F. (1989). The short-term effects of delayed application

of electric fields in the damaged rodent spinal cord. Neurosurgery, 25(1), 71-75.

267. Zanakis, M. F. (1990). Differential effects of various electrical parameters on

peripheral and central nerve regeneration. Acupuncture & electro-therapeutics

research, 15(3-4), 185-191.

268. Pomeranz, B., & Campbell, J. J. (1993). Weak electric current accelerates

motoneuron regeneration in the sciatic nerve of ten-month-old rats. Brain

research, 603(2), 271-278.

269. Sisken, B. F., Walker, J., & Orgel, M. (1993). Prospects on clinical applications of

electrical stimulation for nerve regeneration. Journal of cellular biochemistry, 51(4),

404-409.

270. Schmidt, C. E., Shastri, V. R., Vacanti, J. P., & Langer, R. (1997). Stimulation of

neurite outgrowth using an electrically conducting polymer. Proceedings of the

National Academy of Sciences, 94(17), 8948-8953.

271. Lovat, V., Pantarotto, D., Lagostena, L., Cacciari, B., Grandolfo, M., Righi, M. et al.

178

(2005). Carbon nanotube substrates boost neuronal electrical signaling. Nano

letters, 5, 1107-1110.

272. Keisham, B., Cole, A., Nguyen, P., Mehta, A., & Berry, V. (2016). Cancer Cell

Hyperactivity and Membrane Dipolarity Monitoring via Raman Mapping of

Interfaced Graphene: Toward Non-Invasive Cancer Diagnostics. ACS Applied

Materials & Interfaces, 8(48), 32717-32722.

273. Guadagno, L., Raimondo, M., Vittoria, V., Vertuccio, L., Lafdi, K., De Vivo, B. et

al. (2013). The role of carbon nanofiber defects on the electrical and mechanical

properties of CNF-based resins. Nanotechnology, 24(30), 305704.

274. Rey-Raap, N., Calvo, E. G., Bermúdez, J. M., Cameán, I., García, A. B., Menéndez,

J. A., & Arenillas, A. (2014). An electrical conductivity translator for

carbons. Measurement, 56, 215-218.

275. Debelak, B., & Lafdi, K. (2007). Use of exfoliated graphite filler to enhance polymer

physical properties. Carbon, 45(9), 1727-1734.

276. Chen, P. H., & Chung, D. D. L. (2014). Thermal and electrical conduction in the

compaction direction of exfoliated graphite and their relation to the

structure. Carbon, 77, 538-550.

277. Al Habis, N., Liu, C., Dumuids, J. B., & Lafdi, K. (2016). Intelligent design of

conducting network in polymers using numerical and experimental approaches. RSC

Advances, 6(97), 95010-95020.

179

278. Heidenreich, R. D., Hess, W. M., & Ban, L. L. (1968). A test object and criteria for

high resolution electron microscopy. Journal of Applied Crystallography, 1(1), 1-19.

279. Sill, T. J., & von Recum, H. A. (2008). Electrospinning: applications in drug delivery

and tissue engineering. Biomaterials, 29(13), 1989-2006.

280. Liang, D., Hsiao, B. S., & Chu, B. (2007). Functional electrospun nanofibrous

scaffolds for biomedical applications. Advanced drug delivery reviews, 59(14), 1392-

1412.

281. Lim, S. H., & Mao, H. Q. (2009). Electrospun scaffolds for stem cell

engineering. Advanced drug delivery reviews, 61(12), 1084-1096.

282. Yang, H., Zhu, G., Huang, Y., Shi, X., & Wang, Y. (2016). The stimulation of the

differentiation of pheochromocytoma (PC12-L) cells into neuron-like cells by

electrically conductive nanofibre mesh. Applied Materials Today, 5, 215-222.

283. Gruber, E., Wilhelm, R. A., Pétuya, R., Smejkal, V., Kozubek, R. et al. (2016).

Ultrafast electronic response of graphene to a strong and localized electric

field. Nature Communications, 7.

284. Kang, I., Heung, Y. Y., Kim, J. H., Lee, J. W., Gollapudi, R. et al. (2006).

Introduction to carbon nanotube and nanofiber smart materials. Composites Part B:

Engineering, 37(6), 382-394.

285. Vander Wal, R. L., Miyoshi, K., Street, K. W., Tomasek, A. J. et al. (2005). Friction

properties of surface-fluorinated carbon nanotubes. Wear, 259(1), 738-743.

180