SUPERCAPACITORS BASED ON CARBON NANOTUBE FUZZY FABRIC STRUCTURAL COMPOSITES. Dissertation. Submitted to. The School of Engineering of the

Transcription

1 SUPERCAPACITORS BASED ON CARBON NANOTUBE FUZZY FABRIC STRUCTURAL COMPOSITES Dissertation Submitted to The School of Engineering of the UNIVERSITY OF DAYTON In Partial Fulfillment of the Requirements for The Degree of Doctor of Philosophy in Materials Engineering By Bakheet Awad Alresheedi UNIVERSITY OF DAYTON Dayton, Ohio December, 2012

2 SUPERCAPACITORS BASED ON CARBON NANOTUBE FUZZY FABRIC STRUCTURAL COMPOSITES Name: Alresheedi, Bakheet APPROVED BY: Khalid Lafdi, Ph.D. Advisory Committee Chairman Wright Brothers Institute Endowed Chair in Nanomaterials Professor, Chemical and Materials Engineering Department P. Terrence Murray, Ph.D. Committee Member Professor and Research Scientist, Chemical and Materials Engineering Department Donald Klosterman, Ph.D. Committee Member Associate Professor, Chemical and Materials Engineering Department Muhammad Usman, Ph.D. Committee Member Assistant Professor, Department of Mathematics John G. Weber, Ph.D. Associate Dean School of Engineering Tony E. Saliba, Ph.D. Dean, School of Engineering & Wilke Distinguished Professor ii

3 ABSTRACT SUPERCAPACITORS BASED ON CARBON NANOTUBE FUZZY FABRIC STRUCTURAL COMPOSITES Name: Alresheedi, Bakheet University of Dayton Research Advisor: Dr. Khalid Lafdi Supercapacitors used in conjunction with batteries offer a solution to energy storage and delivery problems in systems where high power output is required, such as in fully electric cars. This project aimed to enhance current supercapacitor technology by fabricating activated carbon on a substrate consisting of carbon nanotubes (CNTs) grown on a carbon fiber fabric (fuzzy fabric). The fuzzy surface of CNTs lowers electrical resistance and increases porosity, resulting in a flexible fabric with high specific capacitance. Experimental results confirm that the capacitance of activated carbon fabricated on the fuzzy fiber composite is significantly higher than when activated carbon is formed simply on a bare carbon fiber substrate, indicating the usefulness of CNTs in supercapacitor technology. The fabrication of the fuzzy fiber based carbon electrode was fairly complex. The processing steps included composite curing, stabilization, carbonization and activation. iii

4 Ratios of the three basic ingredients for the supercapacitor (fiber, CNT and polymer matrix) were investigated through experimentation and Grey relational analysis. The aim of Grey relational analysis was to examine factors that affect the overall performance of the supercapacitor. It is based on finding relationships in both independent and interrelated data series (parameters). Using this approach, it was determined that the amount of CNTs on the fiber surface plays a major role in the capacitor properties. An increased amount of CNTs increases the surface area and electrical conductivity of the substrate, while also reducing the required time of activation. Technical advances in the field of Materials and Structures are usually focused on attaining superior performance while reducing weight and cost. To achieve such combinations, multi-functionality has become essential; namely, to reduce weight by imparting additional functions simultaneously to a single material. In this study, a structural composite with excellent capacitive energy properties was successfully prepared. Moreover, after carbon nanotube growth the fuzzy fabric gained tangible energy storage properties without any structural degradation to the carbon fiber. These results represent a state-of-the-art advancement for multifunctional structural composites and warrant further development. iv

5 To my supportive parents (Awad and Mustorah) And My brothers and sisters (Khalid, Mubark, Dalal, Barak, Fahad, Abdualaziz, Manal, and Zidan) v

6 ACKNOWLEDGMENTS ALLAH (My God), the best name to start with. I am very grateful to you for providing me with blessings and faith throughout my life. Without your strength, I would not have been able to finish this dissertation. You taught us that those who do not thank people do not thank God. I wish thank Professor Khalid Lafdi, my advisor, for providing the time and equipment necessary to accomplish the work contained herein. I truly appreciate the guidance and direction you gave me for this research; and for bringing it to its conclusion with patience and expertise. Professor Lafdi was not only my academic advisor, but also my counselor in everything. I simply don t have the words to describe how grateful I am to him. Really, thank you Professor Lafdi. In addition, I must extend my heartfelt thanks to my committee members: Professor Terry Murray, Professor Donald Klosterman, and Professor Muhammad Usman. I am very grateful to them for their guidance and enthusiastic support of this work. I would also like to express my appreciation to several others who have helped me along the way. This includes Dr. Lingchuan Li who offered invaluable support and advice and gave so generously of his time. I also thank Matt Boehle, Robyn Bradford, and Nuha Al Habis. vi

7 I extend special thanks to my sponsor at the University of Dayton Ministry of Higher Education in Saudi Arabia. Thanks to Dr. Mohmmad Aleissa, the Cultural Attaché for the Saudi Arabian Cultural Mission to the U.S. and Mr. Rashed Alsedran for their guidance during my tenure here at UD. Thanks to all my friends. Last but not least, I thank my parents for their constant and unconditional support and my sister Dalal. God is blessing all of you. vii

8 TABLE OF CONTENTS ABSTRACT...iii DEDICATION...v ACKNOWLEDGMENTS...vi LIST OF FIGURES...xii LIST OF TABLES... xvii LIST OF ABBREVIATIONS AND NOTATIONS.... xix CHAPTER 1 MOTIVATION CHAPTER 2 LITERATURE REVIEW Introduction Supercapacitor Traditional Capacitors The Electrical Double Layer Design of Supercapacitors viii

9 2.2.4 Pseudocapacitance Supercapacitors in Comparison with Batteries Traditional Electrode Materials based Supercapacitors Recent Materials based Supercapacitors Carbon based Supercapacitors Carbon Nanotube based Supercapacitive Capacitor Design for Carbon Nanotube Supercapacitors Optimizing the Performance of Supercapacitors Liquid Electrolytes Used in Supercapacitors Solid Electrolyte Used in Supercapacitors Bibliography CHAPTER 3 THEORETICAL STUDIES FOR EXPERIMENTAL METHODES Backgrounds for the Theoretical Studies Theoretical Design Parameter Selection Grey Relational Model Grey Systems Relational Grade Analysis Statistic Model on effect of CNT, PAN and Activation Time Factors Selection Linear Models with One Independent Variable Linear Models with Two or More Independent Variable ix

10 Nonlinear Models Data Specifications Extra Recorded Data Response Variable Control Variables Fixed Variable Uncontrollable Nuisance Factors Statistic Run Design Steps Test Matrix and Procedure Conclusions Bibliography CHAPTER 4 EXPERIMENTAL SETUP Sample Preparation Prepare Polymer Precursor Solution Coating and Dry Samples Stabilization Process Carbonization Process Activation Process Preparation Liquid and Solid Electrolyte Supercapacitor Construction and Testing Characterization Tools x

11 4.4.1 Brunauer, Emmett and Teller (BET) Scanning Electron Microscopy (SEM) Bibliography CHAPTER 5 RESULTS AND DICUSSION Calculated Results Based on Grey Relational Model from Experimental Entry Grey Relational Model Results Discussion Conclusion Statistic Model on effect of CNT, PAN and Activation Time Statistic Model Results Analysis of First ANOVA Step Nuisance Factors Analysis Qualitative Observations Variance Analysis (ANOVA TEST) First Design: Factors A, B, C, AB, AC, and BC are Included with No Transformation Second Design: First Model: Factor A, B, C, AB, and BC are Included with No Transformation Second Model: Factor A, B, C & AB are Included Third Design: Using a Natural Log Transformation Best Model xi

12 5.2.2 Conclusion Numerical Optimizations Recommendations Materials Characterization at Various Processing Steps Liquid Eelectrolyte Based Electrodes Solid Electrolyte Based Electrodes Conclusions Bibliography CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS Conclusions Recommendations..139 xii

13 LIST OF FIGURES Figure 1: The Flow of electrons during the charging of a traditional capacitor..6 Figure 2: Exponential decay of voltage during capacitor discharge... 8 Figure 3: Electrode electrolyte interface at a negatively charged pore Figure 4: Electrode electrolyte interface at a positively charged pore Figure 5 : An Electrical double layer capacitor cell which is submersed in an electrolyte solution Figure 6: Cover page of Becker's patent Figure 7: Picture of Rightmire s device from his patent Figure 8: Prototype of a 5V-5F supercapacitor Figure 9: Steps to form 3D electrodes Figure 10: Rolled-up structure for supercapacitor Figure 11: Sandwich structure of supercapacitor Figure 12: Trend in batteries performance Figure 13: Different materials for supercapacitor Figure 14: Typical specific capacitance for different supercapacitor materials...27 Figure 15: A Single walled carbon nanotube.30 xiii

14 Figure 16: An electrical double layer supercapacitor Figure 17: Cubic diagram to illustrate the high and low levels responses of each independent variable Figure 18: PAN solution used for coating samples Figure 19: Vacuum oven model 282A from Fisher scientific used for treating the PAN coated fabric samples Figure 20: Fiber sample Figure 21: Fuzzy fabric (Fiber + CNT) sample Figure 22: Fiber composite (Fiber + PAN) sample before thermal process Figure 23: Fuzzy fabric composite (Fiber + CNT + PAN) sample before thermal process Figure 24: Fiber composite (Fiber + PAN) sample after thermal process Figure 25: Fuzzy fabric composite (Fiber + CNT + PAN) Sample after thermal process 71 Figure 26: Oven utilized for stabilization prior to the carbonization step Figure 27: Tube furnace for carbonization Figure 28: Capacitor construction Figure 29: Experimental setup of the supercapacitor immersed in a 1M H 2 SO 4 electrolyte solution and connected to electrochemical workstation Figure 30: Model 600C series electrochemical workstation from HCH instruments Figure 31: Brunauer, Emmett and Teller (BET) instrument Figure 32: Scanning Electron Microscopy (SEM) Figure 33: Scatterplot of surface area vs weight after activation xiv

15 Figure 34: Shows that having high level of CNT in the four runs out of eight runs gives higher surface area Figure 35: Shows that having high Level of PAN in the four runs out of eight runs gives higher surface area Figure 36: Shows that having high level of activation time which in this case is four gives higher surface area Figure 37: Predicted vs actual values of surface area Figure 38: Contour surface representation of the effects of CNT and PAN Figure 39: Contour surface representation of the effects of CNT and activation time Figure 40: Contour surface representation of the effects of PAN and activation Time. 111 Figure 41 : 3D Surface representation of the effects of CNT and PAN Figure 42: 3D Surface representation of the effects of CNT and activation time Figure 43: 3D Surface representation of the effects of PAN and activation time Figure 44: Numerical optimization 3D graph Figure 45: Carbon fiber substrate Figure 46: Carbon nanotubes grown on carbon fibers Figure 47: Activated carbon fabricated on carbon fibers Figure 48: Activated carbon fabricated on carbon fibers covered with CNTs Figure 49: (a) Cyclic voltammogram of the fiber +PAN composite samples cycled from V to +0.5 V at various activation times (b) Charge/discharge curves of fiber +PAN composite samples at various activation times xv

16 Figure 50: (a) Cyclic voltammogram of fiber+ 30% CNT+ PAN composite samples cycled from -0.5 V to +0.5 V at various activation times(b) Charge/discharge curves of Fiber+ CNT+ PAN composite samples at various activation time Figure 51: Cyclic voltammogram of fiber+ 30% CNT +PAN composite samples (30%CNT) and fiber +PAN samples with 4 hours activation at 100 mv/s scan rate Figure 52: BET results for surface area Figure 53: The effect of activation time on specific capacitance for a) CNT-free carbon coated fabric; b) Carbon/CNT coated fabric with different ratio of CNT Figure 54: Cyclic voltammogram fiber +PAN composite with solid electrolyte with several of activation time at 5 mv/s scan rates Figure 55: Cyclic voltammogram of fiber+ CNT +PAN composite with solid electrolyte with several activation times at 5mV/S Scan Rate xvi

17 LIST OF TABLES Table 1: Comparative data of battery and electrochemical capacitor [18] Table 2: Factor level definitions Table 3: Initial standard order test matrix..62 Table 4: Definition of variables.85 Table 5: Application of the first step Table 6: Comparison with the output 87 Table 7: Calculation of ζ and γ.. 88 Table 8: Experiment results...91 Table 9: Nuisance factors...92 Table 10: Effects and contribution of each factor in the experiment in non Transformation model Table 11: First model ANOVA table (factors Included are A, B, C, AB, AC, B. 99 Table 12: Second model ANOVA table (factors Included are A, B, C, AB, BC) Table 13: Second model ANOVA table factors Included are A, B, C, AB) Table 14: Effect and contribution of the factors in Logit transformation xvii

18 Table 15: Third design ANOVA table.105 Table 16: Coefficient estimates of each factor of the most parsimonious Table 17: Numerical optimization table Table 18: Fiber + PAN and fiber +CNT+ PAN composite samples at various activation times with different scan rate Table 19: Fiber +CNT +PAN composite (30% CNT) samples and fiber composite samples with 5 hours activation Table 20: Different ratio of fiber+ CNT +PAN composite samples with same amount of PAN with various activation times at scan rate of 5 mv/s..131 xviii

19 LIST OF ABBREVIATIONS AND NOTATIONS RuO 2 PbO 2 KOH TiO 2 H 2 SO 4 CO 2 Pt Ti PANI PAN CNT MWNT SWCNT BET nm cm 2 E C Ruthenium Dioxide Lead Peroxide Potassium Hydroxide Titanium Dioxide Sulfuric Acid Carbon Dioxide Platinum Titanium Polyaniline Polyacrylonitrile Carbon Nanotube Multiwall Nanotube Single Walled Carbon Nanotube Brunauer Emmett and Teller Nanometer Centimeter Squared Energy Capacitance xix

20 t discharge P E max P max DMF PC CAN AC X i X 0 ζ i k Min Time of Discharge Power Maximum Energy Maximum Power Dimethyleformamide Propylene Carbonate Acetonitrile Activated Carbon Inputs Outputs Grey Relational Coefficient Parameter Number Trial Number Minimum Values of i and k of Max Maximum values of i and k of σ ε U Stress Strain Applied Voltage xx

21 CHAPTER 1 MOTIVATION A supercapacitor is a high energy density capacitor that utilizes specific material properties to separate charges rather than using a large dielectric substance. In a traditional capacitor, material such as air is placed between two metal plates so that electrons cannot flow across, creating an electric potential and a source of energy. In a supercapacitor, however, the inherent physical and electrical properties of the substrate are the basis for charge separation and the consequent electric potential. Thus, the additional dielectric material between substrates may be eliminated, resulting in the ability to compact the material and make a capacitor that has the ability to store more energy per volume of material. Such supercapacitors could have enormous implications as high-energy batteries in a wide range of applications. The degree to which a supercapacitor performs is determined by the three fundamental concepts of high electrical conductivity, high surface area, and the type of electrolyte. Current supercapacitor technology is based on activated carbon which utilizes its extremely high surface area to separate charge. Although these supercapacitors can store more energy than traditional capacitors, they sacrifice electrical conductivity because they are composed of a non-graphitic form of carbon. Graphite is comprised of individual graphene sheets stacked on top of one another. These planar graphene sheets consist solely of carbon atoms joined together by sp 2 hybridized bonds in which each 1

22 carbon is bonded to three others, resulting in electron delocalization. Electrons are thus not restricted to a single atom and can move along the plane in which the carbon atoms lie, resulting in extremely high electrical and thermal conductivities in this plane. Activated carbon is not composed of these graphene sheets and thus has a much smaller electrical conductivity, but it is still used because of its incredibly high surface area. Carbon nanotubes offer a possible solution to optimizing the performance of supercapacitors by possessing both high surface area and high electrical conductivity. A single-walled carbon nanotube (SWCNT) can basically be thought of as a graphene sheet rolled up to construct a hollow cylinder of carbon. The tubular form allows for a very large surface area to volume ratio. CNTs have many advantages including an outer radius of around 10 Angstroms. This incredibly small scale, coupled with electron delocalization properties of the graphene sheets from which they are constructed due to the nature of the sp 2 hybridized bonds, lead to high levels of electrical conductivity along the tube wall. Another problem with current supercapacitors is that the material used is in powder form. Powder is not very versatile because binders have to be employed to glue the powder to make the electrodes. In contrast, the tubular structure of carbon nanotubes offers extraordinary mechanical properties that greatly increase the adaptability of a supercapacitor. Therefore, binders can be avoided if the CNTs grow on a fabric-like substrate. In addition, carbon nanotubes could create a supercapacitor as thin as a piece of paper while still retaining incredible flexibility and strength. 2

23 The applications of such a supercapacitor battery would have a tremendous impact on the fields of electronics and energy storage. The goals of this project, therefore, are: (1) To use carbon nanotubes grown on a fabric substrate, to perform surface treatments through successive processes of stabilization, carbonization and activation. These multiples processes are used to increase supercapacitive properties. (2) To test the electrical properties of the resulting material to determine if carbon nanotubes grown on a fabric substrate can serve as an adequate supercapacitor. (3) To use the Grey relational analysis to investigate factors that affect the overall system. It is based on finding relationships in both independent and interrelated data series (parameters). Using the calculations based on the Grey relational grades will determine parameters that affect capacitor performance. (4) To explore the fuzzy fiber approach in solid electrolyte based capacitors. Chapter 2 provides a comprehensive literature review of the three hi-tech materials used in the design of supercapacitors. Chapter 3 deals with a detailed description of the system design and its components as well as describes the numerical study done by using Grey relational analysis for capacitor performance. Chapter 4 focuses on experimental analysis and fabrication of supercapacitors. Finally, Chapter 5 provides some conclusions from the present study and highlights various implications on ongoing and future energy applications. 3

24 CHAPTER 2 LITERATURE REVIEW 2.1 Introduction The energy problems of the world are related to increased energy consumption due to life improvement in highly populated countries and a lack of energetic raw materials. From these two points, we have identified two problems: energy production and energy storage. Many solutions have been found to produce energy, but few solutions have been found to store it. The current energy crisis has generated much interest in novel techniques for producing and storing energy. In particular, dwindling oil reserves and environmental hazards related to the use of oil in combustion engines has prompted the desire for fully electric cars. The new 2011 Nissan Leaf is the first fully electric car on the market, powered only by laminated compact lithium-ion batteries. One current disadvantage of these automobiles, however, stems from the low power density of electrochemical batteries. As a result, these cars are unable to produce enough force to drive the car during rapid acceleration or towing. Nissan conveniently states that they do not have a 0 to 60 mph acceleration specification for the Leaf, claiming instead that it has surprisingly quiet and effortless acceleration and a maximum speed of 90 mph. The engine in the Leaf is only capable of outputting a maximum of 90 kw, which is less than most four cylinder combustion engines. Nissan even recommends that its Leaf owners 4

25 avoid towing with their new electric car [1]. Thus, although these new cars provide exciting solutions to the current issues surrounding combustion engines, an improved power output is required to apply these emerging technologies to larger vehicles where the power requirements are much greater. 2.2 Supercapacitor Capacitors offer a solution to this dilemma because of their extremely high power density, capable of releasing a large amount of energy in a short period of time. Ideally, capacitors could be used in conjunction with batteries to satisfy the power requirements in electric vehicle systems by combining the high energy density of batteries with the high power density of capacitors. The battery could power the vehicle and electrically charge the capacitors during normal operation, while the capacitors could deliver large amounts of power when needed, such as during rapid acceleration. Requirements for such capacitors would include a high energy density, very high recyclability, sustained power densities greater than those of batteries at the same operating voltage, and reliable discharge characteristics [2]. Practically speaking, traditional capacitors lack the energy capacity to deliver the sustained, high-powered output needed during the acceleration of automotive vehicles. The goal of supercapacitors is to greatly enhance the energy density of such capacitor devices so that a high-powered output can be obtained for a sufficient period of time. Supercapacitors store much larger amounts of energy per unit volume of material by eliminating dielectric materials and vastly increasing the usable surface area. 5

26 Traditionally, supercapacitor technology has been based off of activated carbon and carbon powders due to their extremely high surface area Traditional Capacitors In a traditional capacitor, a non-conducting material such as air is placed between two metal plates so that electrons cannot flow across. When an electric current is applied to the capacitor, positive and negative charges are forced onto the opposing metal plates, creating an electric potential. This potential energy can be released by removing the electrical stress used to initially create the potential. Thus capacitors are a way in which electrical energy can be accumulated and stored until it is needed. Figure 1: The flow of electrons during the charging of a traditional capacitor. 6

27 Because the stored energy is simply in the form of positive and negative charges on the metal plates, the energy release is fairly rapid, resulting in the high power densities of capacitors. The energy density of capacitors is inherently low, however, due to the fact that energy is stored only at the surface of the plates, resulting in a small amount of stored energy per unit volume of material. Traditional electrochemical batteries, on the other hand, store energy as chemical potential energy that must be released through Faradaic oxidation and reduction reactions. The rate at which energy can be released from a battery is limited to the kinetics of such reactions, resulting in a low power density. The energy stored in the chemical components of such a cell, however, is twice that of a capacitor of the same charge and voltage. Thus, capacitors can do a large amount of work in a given amount of time but can only output this energy for a short period, whereas batteries can store a large amount of energy but only release it at a limited rate [2]. The actual energy (E) stored in a capacitor can be expressed as a function of capacitance (C) and applied voltage (U) as illustrated in Equation 1. [3, 4]. Because charged particles are continuously leaving the surface of the capacitor during discharge, the voltage (U) decreases with time as shown in Figure 2. 7

28 Figure 2: Exponential decay of voltage during capacitor discharge [2-4]. The energy stored within the capacitor is thus quickly dissipated after the removal of the electrical stress used to originally force the charges onto the plates. In the case of a capacitor, the electrical work done is equivalent to the energy (E) released during time of discharge (, and thus the power delivered (P) by the capacitor can be illustrated as in Equation 2. Capacitors can thus deliver a high-powered output for a brief period before their energy is depleted, and they must be recharged before further use. In contrast, the chemical reactions of batteries rely on a thermodynamic potential that is independent of an external electric potential, and consequently the power output from batteries is constant but much lower than capacitors [2]. 8

29 2.2.2 The Electrical Double Layer In contrast to traditional capacitors, a supercapacitor utilizes the specific material properties of an electrode and an electrolyte to separate charges rather than using a large dielectric substance. When an electric current is applied to the system, an electric potential is created in a manner similar to a traditional capacitor. This potential, however, exists between the surface of the substrate and the ions of an electrolyte solution. The solvent acts as the dielectric medium in between. This dielectric space, called the Helmholtz layer, is only one or two molecules thick, consisting only of the monolayer of adsorbed solvent on the electrode and the water of hydration of the electrolyte ions. This region can be separated into the inner Helmholtz layer, which consists of a monolayer of solvent and ion molecules adsorbed on the electrode surface, and the outer Helmholtz layer, which incorporates the solvated ions of opposite charge. These layer distinctions arise as a result of the different sizes of cations and anions. Anions are usually smaller than the solvated cations and consequently the distance between them and the positive electrode is smaller than the space separating the hydrated cations from the negative electrode. The capacitance at the positive electrode, therefore, is usually twice that of the negatively charged electrode. Beyond the Helmholtz regions is a diffuse layer consisting of a distribution of ionic charge [2]. 9

30 Figure 3: Electrode electrolyte interface at a negatively charged pore [2]. Figure 4: Electrode electrolyte interface at a positively charged pore [2]. 10

31 Theoretically, one electrode and electrolyte interface creates a fully functioning equivalent of a traditional capacitor. Practically speaking, however, there must be two electrodes so that an electric potential may be applied, and there are thus two of these layered regions within a supercapacitor. This configuration, shown in Figure 5, is aptly called an electrical double layer capacitor. Figure 5 : An electrical double layer capacitor cell submersed in electrolyte solution [4]. The porous electrodes are placed on metal current collectors that are connected to a power source. A non-conducting separator is placed between the two electrodes to prevent current flow between them. The apparatus is immersed in an electrolyte solution, and voltage is applied to the electrodes. Charges accumulate on the surface of the pores within the electrode and attract the oppositely charged ions within the solution, creating an interface of charge separation in each electrode. 11

32 Two factors contribute to the extremely high specific capacitance values found in the electrical double layer of supercapacitors. First, as illustrated by Equation 3, an inverse relationship exists between capacitance and the distance between the separated charges (where ɛ is electrolyte permittivity, S is surface area of electrode, and d is the distance between separated charges) [4]: As the distance between separated charges increases, the attractive force between the oppositely charged particles is diminished. The driving force for storing the electrical energy at the surface of the electrode decreases, and a lower capacitance is observed as a result. Because the positive and negative charges in a supercapacitor are only separated by a few layers of solvent molecules, the attractive pull between opposing charges on either side of the Helmholtz layer is extremely strong. For a 1 V potential difference applied to a double layer thickness of 0.38 nm, for example, the resulting electric potential would be approximately 2.9 x 107 V/cm 2. This incredibly strong electrical potential results in high capacitance values. Second, specific capacitance increases with increased electrode surface area because the electrical charge is stored mainly at the electrode/dielectric interface. In traditional capacitors, most of the material is not utilized in the storage of energy because only a fraction of the total volume is exposed. The incredibly large surface area-tovolume ratio in highly porous electrodes, however, yields a large amount of usable surface in which electrical charge can be stored, increasing the capacitance per unit volume of material. Additionally, the large dielectric material used in traditional 12

33 capacitors may be eliminated, resulting in supercapacitors that can obtain substantially higher capacitance values with the same volume of electrode material Design of Supercapacitors Supercapacitor performance is partially dependent on system design. The design evolution started from the first patent filed in 1957 by H.I. Becker. It consists of a vial containing two electrodes and a liquid electrolyte [5-7]. Figure 6: Cover page of Becker's patent [5]. 13

34 The actual form of supercapacitor was published in a patent five years after R.A. Rightmire created a one piece device made of two electrodes of porous graphite and a current collector. The electrodes were immersed in the electrolyte and separated by an insulating layer restraining the occurrence of electrical current. Figure 7: Picture of Rightmire s device from his patent [6]. Starting with this kind of cell unit, more complex designs were conceived. To allow high electrical potential, a structure combining several supercapacitors has been proposed by Khandpekar et al. [8]. They succeeded in creating a 5 V device. 14

35 Figure 8: Prototype of a 5 V-5 F supercapacitor [8]. Another aspect of this design is the use of a solid electrolyte. It reduces the overall weight of the device and decreases the power rate by limiting ion movement. Recently, other designs have been developed to improve the surface of the electrodes while optimizing the volume of the device. One of these designs made by Shen et al. used a micro supercapacitor with a special design [9]: Figure 9: Steps to form 3D electrodes [7]. 15

36 This design is called interdigital channels. It was built on a silicon substrate in order to be integrated on a chip. Other designs for micro supercapacitors include the rolled-up or sandwich structures [9, 10]: Figure 10: Rolled-up structure for supercapacitor [9, 10]. Figure 11: Sandwich structure of supercapacitor [9, 10]. 16

37 All these researchers considerably developed the volume efficiency of supercapacitors. Despite the structure, the materials also have a fundamental influence on the properties of supercapacitors. Indeed, the performance of supercapacitors is determined by three parameters: electrical conductivity, surface area and the nature of the electrolyte. The material which constitutes the electrode is therefore very important [11-13] Pseudocapacitance In a supercapacitor, charge is mainly stored electrostatically at the interface of the electrode and electrolyte as previously described. This type of charge storage is described as non-faradaic and is characterized by the lack of electron transfer across the electrode interface. In an alternate situation, electrons are transferred across the interface of the electrode and electrolyte. These Faradaic mechanisms are redox reactions that are dependent upon the surface chemistry of the electrode and electrolyte materials. Hence, the surface molecules of these materials are altered as their oxidation states change. Pseudocapacitance is a situation between these two extremes in which Faradaic charge transfer occurs, but the electrode potential is a continuous function of the amount of charge. Thus, as potential increases, the amount of charge transferred and stored at the surface of the electroactive materials also increases, resulting in a form of capacitance. Although accounting for only a small portion of the overall capacitance, 17

38 pseudocapacitance nevertheless contributes a non-negligible fraction of the charge storage capacity of a supercapacitor [3, 14]. The edges within activated carbon contain unsaturated carbon atoms that can subsequently bond with other available molecules, such as oxygen and nitrogen. Since activated carbon has a high surface area, there are many places for this chemisorption phenomenon to occur. These surface functional groups can partake in Faradaic redox reactions and thus increase the overall capacitance of the capacitor. This oxidation of surface carbons also causes an increase in wettability due to the increase in polar oxygen molecules. These functional groups cause an increase in leakage current, however, and thus may not be beneficial above a certain concentration [15]. Nitrogen added to carbon nanotubes, for example, has been experimentally shown to yield a marked increase in specific capacitance. The presence of nitrogen in concentrations in excess of 15 %, however, decreases the conductivity and the cycle ability of the capacitor [2] Supercapacitors in Comparison with Batteries Electrochemical rechargeable batteries are energy storage devices. A variety of rechargeable batteries is now available commercially. As an example, lithium batteries are quite popular because of their excellent properties like weight/energy ratio and low self-discharge rates [16-17]. 18

39 Figure 12: Trend in battery performance [16]. Scientists are interested in supercapacitors because they offer solutions to energy storage and delivery applications in systems where a high power output is required, such as in fully electric cars. They present a low energy density and a high power density, as compared to batteries which have high energy density and low power density. Moreover, supercapacitors provide a long cycle life [16-17] and quick ability to discharge and charge. Other advantages include simple operating principles and modes of construction as well as cheap materials. Supercapacitors combine state-of-the-art charge indication (Q=f(V)) and can be combined with rechargeable batteries for hybrid applications. However, they can only be used at low working voltages [18]. 19

40 Table 1: Comparative Data of Batteries and Electrochemical Capacitors [18]. Electrical Characteristics Thermodynamic Behavior Energy Density Batteries Behavior is not capacitive: chemical reactions of the anode and cathode materials are included with phase changes Usually not reversible A thermodynamic potential exists as long as the two components of the electroactive material remain coexisting. Thus, the potential difference (electromotive force) of the battery cell is ideally constant throughout the discharge or recharge cycle Poor: from 1 to 10 Wh/kg Supercapacitors Behavior is capacitive: No chemical changes are involved Recharge and discharge curves are mirror images in cyclic voltammetry High degree of reversibility Potential is thermodynamically related to Q. Every additional element of charge that is added has to do electrical work against the charge density already accumulated on the plates, progressively increasing the inter electrode potential difference. Moderate or good: from 10 to 100 Wh/kg Power Density Good: 104 W/kg Relatively poor: < 103 Cyclability Excellent: 106 cycle life 103 cycle life due to irreversibility of redox and phase-change processes Life Time Electrolyte Conductivity Long, except for corrosion of current collectors Can diminish on charging due to ion adsorption Poor, due to degradation or reconstruction of active materials Can decrease or increase on charging, depending on chemistry of cell reactions 20

41 2.2.6 Traditional Electrode Materials Based Supercapacitors In 1957, Backer described a basic supercapacitor concept in a patent [7, 19]. He used a high surface area carbon electrode and an aqueous H 2 SO 4 electrolyte to fabricate the supercapacitors. Also, in 1971, NEC (Japan) developed aqueous electrolyte for power saving units in electronics [19]. A supercapacitor consists of three important parts: the electrodes, the electrolyte, and the separator. The electrodes are an important element for charge/discharge delivery and were used to determine energy and power densities of a supercapacitor. Supercapacitors have been evaluated using three principal types of electrode materials which are high-surface-area activated carbons [20], electroactive polymers [21], and transition metal oxides [22]. The basic structure of a supercapacitor depends on high surface area and porous carbon electrodes. For example, charge separation in the double layer capacitor technology stores energy in the interface between the solid electrode surface and the liquid electrolyte. The ions which moved to form the double-layers are transferred between the electrodes by diffusion through the electrolyte [23]. The application of transition metal oxides and electroactive polymers are providing higher energy densities for capacitors but each type has limitations. For the first one, the problem is high cost; and for the second, the problem is stability [24]. However, high surface area activated carbons are still the predominant electrode material for supercapacitor applications in the world market. 21

42 The maximum energy (E max ) and maximum power (P max ) of a supercapacitor are given by: E max = (CU 2 )/2 (4) P max = U 2 / (4R) (5) Where C is capacitance, U is cell voltage, and R is total equivalent series resistance (ESR) of the capacitor in equations 4 and 5 [23]. The physical properties of both the electrode and the electrolyte material can determine the overall performance of the supercapacitor. This path has benefits like low cost, commercial availability, and well-established electrode production technologies. So, activated carbon (AC) has high surface area for major supercapacitors but practically obtained values for specific capacitance are a few tens of F/g. The electrolyte has poor accessibility to the carbon surface of AC [23, 25]. This is the most important reason for the absence of proportionality between specific capacitance and surface area for these materials. There are three classes of pore sizes according to the International Union of Pure and Applied Chemistry (IUPAC) classification that can be distinguished within the electrode material. The smallest of these are the micropores, which have a width of less than 2 nm. Pores with a width ranging from 2 to 50 nm are deemed mesopores, while holes exceeding 50 nm are called macropores [24]. These different pore sizes play various roles within the electrical double layer. The AC surface after the activation process is characterized by measuring micropores [20]. 22

43 Developing ion accessibility to increase the capacitance of carbon materials is preferable. So, increased surface area is achieved with mesopore sizes [26-28]. That means the balance between the surface area and the mesoporosity of a carbon material is the key to achieve high capacitance. In fact, AC has low mesoporosity structures that lead to low electrolyte accessibility which in turn increases ESR [20], limits capacitance, and results in poor power density for the capacitor. Accordingly, fabricating electrodes from these activated carbon materials gives supercapacitors a limited energy density and a limited power density [25]. An ideal electrode material should have important properties such as the ability to overcome the drawbacks of the presently used activated carbon electrode materials, high surface area, high electrical conductivity, high mesoporosity, and high electrolyte accessibility. CNTs have been considered as materials for supercapacitor electrodes to develop storage energy. 23

44 2.2.7 Recent Materials Based Supercapacitors Several ways have been investigated in order to obtain high capacitance. Three kinds of material were explored. The first one is based on depositing several layers of metallic oxides. The fabrication process is fairly complex and requires more attention to avoid contaminants. Yoon et al. reported a good supercapacitive behavior using ruthenium oxide layers; however, performance was limited because of low ionic mobility [11]. In this case, the supercapacitor requires a silicon substrate, a TiO 2 layer for bonding and a Pt layer as current collector. Moreover, two layers of RuO 2 are necessary. Yu et al. created a hybrid supercapacitor with PbO 2 deposited on a Ti electrode and obtained a capacitance value of 71.5 F/g [12]. But an intermediate layer of Sn was necessary. The other electrode was made of activated carbon. Conversely, a value of 65.5 F/g was reached using 3 thin films of cupric oxide and polyacrilic acid [13]. The problem is how energy is stored. A part is done by Faradaic reactions which gives a low charge-discharge cycling life. Wang et al. reported a value of 77 F/g by using a Co-Al compound on a nickel grid [27]. The preparation and the deposition of this compound required multiple processing steps, such as stirring during 48h at 70 C and centrifugation which made the fabrication process very costly. These examples illustrate the major issues of using metallic oxides: the complexity of the process and the Faradaic reactions at the electrodes. A second type of material used composites based on conductive polymers with either carbon compound or metallic oxides. These compounds have a high electrical conductivity but a low surface area. Tests have been done with an electrode made of polyaniline (PANI) and doped with lithium powder to increase electrical conductivity 24

45 [28]. After an important preparation process, a specific capacitance of 100 F/g was reached. A solid poly (vinylidene fluoride-co-hexafluoropropylene) was used as electrolyte. Polyaniline was also used in combination with poly vinyl sulfonic acid and carbon black to obtain 98 F/g [31]. The same polymer combined with carbon nanotubes (CNT) showed a capacitance of 328 F/g, which means a 200% increase in capacitance compared to previous studies [32]. Moreover, this study compares the behavior of pure PANI and PANI/CNT and clearly shows an improvement by the addition of this carbon compound [33]. Synthetized activated carbon/polyaniline reached a specific capacitance of 273 F/g and polypyrrole mixed with carbon nanofiber composite showed a capacitance of 545 F/g. In another article, polypyrrole associated with conducting mica had a good supercapacitor behavior and reached a capacitance of 197 F/g [34]. However, the most important problem with conductive polymer based supercapacitors is their low cycling life, which happens with pseudocapacitors during charge or discharge [35]. The third kind of supercapacitor is based on activated material. The surface of carbon-based composite materials with resin is physically or chemically activated by using high temperatures during thermal processes in order to improve the contact surface area between the electrolyte and the electrodes. Activation consists of creating porosities so that electrolyte ions can move. Various types of carbon can be activated. For example anthracite, common or high-performance carbon fibers have been chemically or physically activated [36]. The best result was a capacitance of 320 F/g by chemically activating anthracite in the form of powder with KOH. Carbon activated powders can also be used and a capacitance value of 290 F/g can be reached [37]. The problem with carbon powder is that capacitance is limited by the contact resistance between particles 25

46 which appeared to be critical in decreasing the overall electrode electrical conductivity. Mixes of PAN and carbon nanotubes that were chemically or physically activated have been tested by Jagannathan et al. and they obtained a value of 250 F/g with KOH chemical activation [38-41]. These kinds of supercapacitors seem very easy to manufacture and exhibit promising capacitance values with long life stability. So, the major drawback is low conductivity created by the high concentration of porosities. Figure 13: Different materials for supercapacitors [34, 42]. As shown Figure 13, materials used only for double-layer capacitance exhibit a long cycling life [34, 42]. They are mostly based on carbon or activated carbon. But their capacitive value is expected to be lower because of the high value of pseudocapacitance. 26

47 Figure 14: Typical specific capacitance for different supercapacitor materials [34, 42] Carbon Based Supercapacitors Carbon has traditionally been the material of choice for supercapacitor electrodes because it can be arranged into several different forms, each of which yields a very high surface area and consequently a high capacitance. Commercial supercapacitors utilizing carbon materials from companies such as Maxwell Technologies and Panasonic have capacitances in the 2,000 to 3,000 farad range, although specific capacitances are usually between 5 and 10 F/g. In the laboratory, researchers have achieved specific capacitances of over 200 F/g, but these materials have not yet been turned into commercially viable products [32-36]. The oldest and most popular of these supercapacitor materials is activated carbon due to its low cost and ease of fabrication. The process of creating activated carbon begins with an organic precursor, such as coal, wood, coconut shells, 27

48 pitch, or polymers such as polyacrylonitrile (PAN). It is subjected to a procedure known as carbonization, where it is heated to temperatures above 800 C in an inert atmosphere. These high temperatures cause the decomposition and subsequent expulsion of all noncarbon elements as gaseous products. The remaining carbon atoms rearrange themselves and bond to each other. They do so in an irregular fashion, however, so that every carbon is not connected to another on all sides. Physical gaps result at the edges of these rings, causing many small pores throughout the material. The material is then subjected to the activation process, where the sample is heated to high temperatures under an oxidizing atmosphere, such as steam or carbon dioxide. Redox reactions occur at the edges of the aromatic carbon rings, causing existing pores to enlarge and new ones to form. The temperature and oxidizing agent, as well as the time that the material is exposed to them, contribute to pore size and distribution throughout the material. As discussed earlier, pore size is extremely important in determining the attainable capacitance of a particular electrode. Therefore, the specific experimental conditions of the carbonization and activation steps must be tuned for a particular precursor material so that optimum pore morphology and consequently the highest possible capacitance are achieved. Carbon powders, such as carbon blacks, are also materials that have been used in supercapacitor electrodes. Carbon black materials are characterized by their colloidal sized spherical particles that are produced by the combustions of hydrocarbons. These particles are compressed together using a binder to create electrodes. The fineness of the particle size determines the overall porosity and consequently the capacitance. Capacitances of up to 250 F/g have been achieved, although a much higher amount of binder is often required to make practical electrodes mechanically stable. A commercial 28

49 electrode would thus have a large volume and suffer from low electrical conductivity, and therefore alternative materials are sought [29]. Carbon fiber and carbon nanotubes are two alternate forms of carbon that have received attention as possible supercapacitor electrode materials. Commercial carbon fibers are fabricated by extruding a melt of PAN or pitch, which are subsequently woven into a fabric. Each individual fiber has a diameter of roughly 10 µm. These fibers are activated to create pores, which form mainly on the outside of each strand due to the slender dimensions of the fibers. This edge porosity allows easy access of the pores to the electrolyte, and thus most of the available surface area can be used to store charge. These boundary pores are more susceptible to oxidation, however, which increases their size and decreases the overall surface area. One advantage of activated carbon fibers over activated carbon is the enhanced ability to control pore size and distribution, which is crucial in supercapacitor optimization [29, 37]. Carbon Nanotubes (CNTs) are cylindrical structures composed completely of aromatic carbon rings connected to one another in a tube-like fashion. As shown in Figure 15, each carbon is bonded to three others in these aromatic rings via sp 2 hybridized bonds, enabling electrons to move along the plane in which the carbon atoms lie. This electron delocalization results in extremely high electrical and thermal conductivities along the length of the tube. Electrical and thermal properties in the direction perpendicular to the tube are very poor, however, since electrons are restricted to the axial plane. In other words, electrons cannot simply jump across the hollow center of the tube. 29

50 Figure 15: A single-walled carbon nanotube [29-37]. Chemical Vapor Deposition (CVD) is the most common fabrication method for CNTs. In this process, an energy source is used to crack gaseous molecules containing carbon, such as CO, into atomic reactive carbon. These carbon atoms then migrate to a catalyst-coated substrate, where the catalyst causes layered growth of nanotubes. The resulting cylindrical structures have nanometer scale diameters, but lengths of up to 18 cm 2 have been achieved [35]. These extremely large length-to-width ratios, along with their excellent electrical and thermal properties have caused CNTs to be the subject of much interest in electronics research. Chemical vapor deposition produces mainly multiwalled carbon nanotubes, which consist of several single-walled nanotubes encapsulated in one another. Although single-walled nanotubes are desirable for certain applications, CVD is the method that is most easily scaled-up for commercial production [38-40]. 30

51 Carbon nanotubes have been used in two different ways in supercapacitor research. The first technique uses them as the actual electrodes by taking advantage of their unique tubular structure. When pressed together into pellets, the CNTs form a meshlike material that has a high surface area due to both their entangled morphology and the hollow central canal of each tube. Specific capacitances of around 80 F/g have been achieved with purified CNTs, although this number can be increased with oxidative surface treatments [29]. In a second technique, CNTs are used as an additive in an electrically conductive polymer electrode, such as polyaniline or polypyrrole, in order to enhance its electrical conductivity as well as provide mechanical stability. The internal resistance of the electrode is decreased, thus increasing capacitance [35] Carbon Nanotube Based Supercapacitors Carbon nanotubes (CNTs) were discovered by Iijima in 1991 [43]. CNTs possess good properties in electronic and electrochemical materials and are a graphene sheet rolled up into a nanoscale tube form. Also, it can have many forms like single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) [44]. A wide range of approaches have been developed to manufacture CNTs. They possess good electrical conductivity, high thermal conductivity, high thermal stability, and good mechanical properties [45, 46]. Also, CNTs have high surface area for an electrode [47]. All these properties are reasons to use CNTs in many applications such as sensors [48], energy storage [49], and supercapacitors [50]. 31

52 CNTs have high electrical conductivity, a moderate specific surface area, high charge transport capability, high mesoporosity, and high electrolyte accessibility. These properties lead researchers to consider CNTs as a good-looking electrode material for developing high-performance supercapacitors [50]. A lot of studies have been made to develop different types of CNT electrode materials and to combine them with various electrolytes to improve the performance of supercapacitors. CNT is easy to fabricate for supercapacitor applications. The results of a lot of studies in these applications reported that CNT has higher capacitance (102 F/g for MWNTs) than activated carbon (10 F/g). Although, activated carbon has high surface area compare to CNT which is possess a moderate one [47]. This point leads us to think about the important of mesopores size for activated carbon. For this point we can say that poor mesoporosity of activated is a major reason to get low capacitance. So, CNT has been used to improve performance of supercapacitors and get higher capacitance. Also, a lot of works show this result. Excellent electrical conductivity, high mesoporosity, and high electrolyte accessibility of CNTs, resulting in a high charge transport capability, are responsible for this significance [40]. In the recent years, a lot of research show that aligned CNTs are a good structure material for supercapacitors and provide a more mesoporous and more accessible surface [22]. Aligned CNTs have greater effective surface area which is determined by the open space between entangled fibrils. So, these aligned structures should provide improved charge storage / delivery properties as each of the constituent aligned tubes can be connected directly onto a common electrode which means an excellent power density for the capacitor. In this field a good result has been obtained which is high capacitance in 1 32

53 M H 2 SO 4 for an aligned CNT array electrode (365 F/g) prepared by chemical vapor deposition (CVD) in the template of porous anodic aluminum oxide [23]. In general, CNTs have a lower surface area compared with activated carbon. Nevertheless, CNTs have a higher electrical conductivity, higher charge transport capability, higher mesoporosity, and higher electrolyte accessibility. This comparison leads researchers to combine activated carbons with CNTs to manufacture composites having the combined advantages from these two components. The resultant nanocomposites would possess an improved conductivity and an appropriate balance between the specific surface area and the mesoporosity, resulting in a higher capacitance than CNTs and a higher rate capability than activated carbons. Protet et al. mixed activated carbon/cnt and a polymer binder to improve capacitive behavior. The capacitance successful balance between the surface area and the mesoporosity leads to a high performance of these activated carbon- and CNTincorporated composites which is a key for this work (study) [24]. Also, Liu et al. mixed SWNT with a polyacrylonitrile (PAN) dimethyleformamide (DMF) solution to fabricate a composite film electrode [25]. PAN is a copolymer which is used to produce activated carbon with high specific surface area and high porosity [26, 27]. In this work, the specific capacitance of SWNT/AC/PAN composites was higher than that of a pure SWNT bulky paper electrode due to their higher specific surface area than pure SWNT. Moreover, power and energy densities and specific capacitance of heat-treated SWNT/PAN composite film with CO 2 activation are higher than film without activation process. 33

54 In the recent years, many attempts to manufacture new composite electrode materials combining the high energy storage capability of these redox materials with the high-power-delivery capability of CNTs to improve capacitance and rate capability of electroactive polymers (e.g.,polyaniline, polypyrrole, and polythiophene) discovered in 1977 [31]. These copolymers are considered as new organic electrochemical materials which have the capability to store and release charge during redox process. Also, they have been investigated for energy storage technologies including supercapacitors [52, 43]. The advantages of electroactive polymers are light weight, low cost, high energy storage capability over high-surface-area activated carbons, and good process feasibility over transition metal oxides. Because of these properties have been developed electroactive polymers and CNTs to fabricate nanocomposites to improve specific capacitance of supercapacitors. Electroactive polymers can be obtained both electrochemically and chemically. So, CNT / electroactive polymer nanocomposites have enhanced capacitance and rate performance related to high electrical conductivity and high mesoporosity of CNTs [53] Capacitor Design for Carbon Nanotube Supercapacitors As shown in Figure 16, a double layer supercacitors consists of the CNT / activated carbon composites and the electroactive polymer / CNT or metal oxide / CNT composites [23]. This technique is one way to improved capacitance and rate capability of the CNT / activated carbon composites. Recently, this technique had a good result for energy and power densities, better than with the conventional activated carbon-based capacitors. So, 34

55 using CNTs in these electroactive electrode materials enhanced the power performance for supercapacitors [23]. In a symmetrical design, specific capacitance is only one fourth of the one electrode s. To solve this problem, asymmetric designs have been developed by replacing one of the previous electrodes by an electroactive using metal oxide [54-56]. Khomenko s study shows that using both symmetrical and symmetrical design help to provide accurate test data [21]. Figure 16: An electrical double layer supercapacitor [21]. 35

56 Optimizing the Performance of Supercapacitors Electrode pore size is of utmost importance when maximizing specific capacitance. A linear relationship would be expected between surface area and capacitance, but this correlation only holds true to a certain threshold. Barbieri et al suggest that a saturation point can be attributed to the fact that as a pore wall approaches a width of about 1nm, the overall capacitance decreases because the space charge regions inside begin to overlap. Through their analysis, they conclude that the activation of carbon is good in one respect because it increases the specific surface area of the material. On the other hand, the activation process also creates an increased amount of pore volume, which has a negative effect on the capacitance due to this charge overlap effect. They conclude that for surface areas above 1200 m 2 /g, the ratio of these two opposing effects is such that no increase in capacitance is observed. The authors conclude that the limit in capacitance is not due to the inability of ions to access pores or inaccuracy in Brunauer-Emmett-Teller (BET) surface area measurements, but rather to a limited amount of space to accumulate charge within the pore walls [11]. Three types of pore sizes can be distinguished within the electrode material. The smallest of these are the micropores, which have a width of less than 2nm. Pores with a width ranging from 2 to 50 nm are deemed mesopores, while holes exceeding 50 nm are called macropores [12]. The different pore sizes play varying roles within the electrical double layer. Micropores are keys to the adsorption and retention of ions within the double layer, and thus are the main source of charge accumulation. Macropores and mesopores must be present, however, to facilitate rapid ion movement throughout the bulk of the material. These larger pores serve as the passageway of electrons through the electrode to 36

57 the surface of the micropores. If an electrode lacks an adequate amount of these larger pores, it experiences a greater resistance to electron flow during charging and discharging. As illustrated by Equation 6, an increased internal resistance negatively affects the attainable power output. ( ) Therefore, an optimization of the amount of mesopores and micropores is crucial to the performance of high capacitance electrodes [10]. Other important factors in the performance of supercapacitors involve the accessibility of these pores to the electrolyte and the wettability of the electrode. Frackowiak et al state that activated carbon materials with a greater percentage of larger pores are better for practical applications despite the fact that they can store less total energy. They can deliver a large amount of energy at a higher rate because the larger pores allow the electrolyte to penetrate into the electrode and access the surface of the smaller pores [13]. Additionally, the ability of the solvent molecules to adhere to the electrode surface to create the double layer affects the potential drop and consequently the capacitance across this space. The unsaturated carbon atoms at pore edges in activated carbon allows for the binding of polar functional groups, particularly those involving oxygen, which create a more hydrophilic and consequently more wet-table surface [12]. Thus, even though a material may have an incredibly high surface area, the capacitance will be low if the electrolyte cannot access the surface of the electrode. As exhibited by Equation 4, the power of a supercapacitor is directly related to the input voltage applied to the electrodes. The greater operating voltage it will the higher the 37

58 attainable power output. Non-aqueous electrolytes can operate in the 3 to 5 V range, but they suffer from low conductivities, increasing the internal resistance of the capacitor and reducing its overall performance. In aqueous electrolytes, a practical limit exists due to the decomposition of water at voltages above 1.23 V [3]. The operating voltage usually cannot exceed 0.8 V when using an aqueous solution of electrolyte [10]. Because of this voltage limit, the maximum obtainable power and energy is constrained, as illustrated by Equations 1 and 4. The maximum power can only be improved by reducing the overall equivalent series resistance (ESR) of the capacitor. Contributing resistance sources of the ESR include the electrode material itself, the interface of the electrode and current collector, the diffusion of ions into the electrode pores and across the separator, and the electrolyte [29]. Decreasing any of these resistances will cause an increase in the power of the capacitor. By combining these Equations, it can be seen that the capacitance is also negatively affected by a high ESR. Thus both the choice of the electrode materials as well as the electrolyte will affect the capacitance and subsequently the power of the supercapacitor [30, 32]. 38

59 The energy density of a capacitor can be improved by increasing the capacitance. As discussed earlier in Equation 3, a supercapacitor accomplishes this objective by decreasing the distance between separated charges and increasing the surface area. Much of the research efforts in supercapacitor technology look to improve their energy densities by increasing this usable surface area. Electrolyte permittivity measured by its ability to polarize in response to an electric field. Also, affects the capacitance. A highly conductive electrolyte salt that has the maximum degree of mobility within its solvent will provide the highest permittivity and thus result in the highest capacitance. The most commonly used electrolytes in electrical double layers that fit these criteria are low concentration solutions of H 2 SO 4 and KOH [31]. 2.3 Liquid Electrolytes Used in Supercapacitors The electrolyte plays an important role in the capacitive performance, the safety, and the life time of a supercapacitor. It is a critical component for charge transport between the positive and negative electrodes. Three types of electrolytes are traditionally used. The first one is an aqueous electrolyte which has a high ionic conductivity but a small electrochemical window (1.2 V). The electrochemical window is the potential below which the electrolyte is neither reduced nor oxidized at an electrode. Examples of these aqueous electrolytes are commonly H 2 SO 4 and KOH. The second kind is an organic electrolyte which has a bigger electrochemical window (3 V) and higher energy storage capacity, but problems of depletion and toxicity. Examples of this aqueous electrolytes are used mostly Propylene Carbonate (PC) and Acetonitrile (ACN) electrolytes [54, 55]. 39

60 The last one is ionic liquids composed of organic cations and inorganic anions. Their liquid phase range is large, so is their electrochemical window (6 V) [56, 57]. The problem is their high viscosity which reduces the ions migration. Combined with aligned CNT, the supercapacitor shows higher performances [58]. 2.4 Solid Electrolyte Used in Supercapacitors A few studies have been reported on solid electrolyte based supercapacitors. The critical factor in the use of solid polymer electrolytes (as found in lithium battery technology) is to achieve sufficient conductivity at ambient temperatures. This is particularly important for electrochemical capacitors where good power delivery capability is an essential feature. This requirement means that very thin-film technology must be employed in fabrication of capacitor device. For the manufacturing and reliability issues, solid electrolytes are preferred instead of liquid electrolytes. As a matter of fact, they present advantages such as lightweight [59], easy handling, reliability without electrolyte leakage [60], small size and small bulk because of the absence of containment [61], sustainable and robust over periods of time [62]. Well, we have to compare results of specific capacitance between solid electrolyte and liquid electrolyte to see if we can reach a value for solid electrolyte as higher as supercapacitors with liquid electrolyte. Nowadays, solid-state electrochemical devices such as sensors, lithium batteries and supercapacitors are extensively studied. Poly (Ethylene Oxide) (PEO) is widespread because of the suitable distance between ether oxygen side groups, which is very 40

61 important in ions transfer [63]. A thin-film, solid polymer electrolyte technology, based on polyether as solvent and lithium or R 4 N + salts as electrolytes (as for solid polymer electrolyte lithium batteries), has been described by Baudry et al. (Electricité de France and Bolloré Technologies) (Baudry et al., FES 1994). This system behaves as a nonaqueous electrolyte with moderately high operating voltage limited, in the case of Li + salts, by the potential for Li discharge at carbon. The double layer capacitive material was activated carbon giving 40 to 100 F/g. However, at room temperature, PEO are hindered by a low ionic conductivity. It gives an ionic conductivity between 10-6 and 10-5 S.cm -1 [64]. 41

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67 [39] Sudhakar Jagannathan, Han Gi Chae, R ahul Jain, Satish Kumar, Structure and electrochemical properties of activated polyacrylonitrile based carbon fibers containing carbon nanotubes, Journal of Power Sources 185 (2008) [40] Bin Xu, Feng Wu, Renjie Chen, Gaoping Cao, Shi Chen, Zhiming Zhou, Yusheng Yang, highly mesoporous and high surface area carbon: A high capacitance electrode material for EDLCs with various electrolytes, Electrochemistry Communications 10 (2008) [41] J.L. Hu, J.H. Huang, Y.K. Chih, C.C. Chuang, J.P. Chen, S.H. Cheng, J.L. Horng, Effects of thermal treatments on the supercapacitive performances of PAN-based carbon fiber electrodes, Diamond & Related Materials 18 (2009) [42] Bin Xu, Feng Wu, Shi Chen, Cunzhong Zhang, Gaoping Cao, Yusheng Yang, activated carbon fiber cloths as electrodes for high performance electric double layer capacitors, Electrochimica Acta 52 (2007) [43] T.V. Sreekumar, S. Kumar, Macroscopic fiber comprising single-wall carbon nanotubes and acrylonitrile based polymer and process for making the same, US Patent 6,852,410, [44] F. Ko, Y. Gogotsi, A. Ali, N. Naguib, H. Ye, G.L. Yang, C. Li, P. Willis, electrospinning of continuous carbon nanotube filled nanofiber yarns, Adv. Mater. 15 (2003)

68 [45] H. Ye, H. Lam, N. Titchenal, Y. Gogotsi, F. Ko, reinforcement and rupture behavior of carbon nanotubes polymer nanofibers, Appl. Phys. Lett. 85 (2004) [46] S. Prilutsky, E. Zussman, Y. Cohen, the effect of embedded carbon nanotubes on the morphological evolution during the carbonization of poly(acrylonitrile) nanofibers Nanotechnology 19 (2008) [47] L. Vaisman, E.Wachtel, H.D.Wagner, G. Marom, polymer nanoinclusion interactions in carbon nanotube based polyacrylonitrile extruded and electrospun fibers, Polymer 48 (2007) [48] D.K. Kim, S.H. Park, B.C. Kim, B.D. Chin, S.M. Jo, D.Y. Kim, Electrospun polyacrylonitrile-based carbon nanofibers and their hydrogen storages Macromol. Res. 13 (2005) 521. [49] Beguin F., Szostak K., Lota G. and Frackowiak E., a self-supporting electrode for supercapacitors prepared by one-step pyrolysis of carbon nanotube polyacrylonitrile blends, Adv. Mater., 17, (2005). [50] H. Hou, J.J. Ge, J. Zeng, Q. Li, D.H. Reneker, A. Greiner, S.Z.D. Cheng, electrospun polyacrylonitrile nanofibers containing a high concentration of well aligned multiwall carbon nanotubes Chem. Mater. 17 (2005) [51] V. Khomenko, E. Frackowiak, F. Beguin, determination of the specific capacitance of conducting polymer/nanotubes composite electrodes using different cell configurations, Electrochim. Acta, 50 (2005)

69 [52] Q. Bao, S. Bao, C.M. Li, X. Qi, C. Pan, J. Zang, Z. Lu, Y. Li, D.Y. Tang, S. Zhang, K. Lian, supercapacitance of solid carbon nanofibers made from ethanol flames, J. Phys. Chem. C 112 (2008) [53] C. Kim, K.S. Yang, Electrochemical properties of carbon nanofiber web as an electrode for supercapacitor prepared by electrospinning, Appl. Phys. Lett. 83 (2003) [54] F.C.Wu, R.L. Tseng, C.C. Hu, C.C.Wang, the capacitive characteristics of activated carbons comparisons of the activation methods on the pore structure and effects of the pore structure and electrolyte on the capacitive performance, J. Power Sources 159 (2006) [55] J.G. Lee, J.Y. Kim, S.H. Kim, effects of microporosity on the specific capacitance of polyacrylonitrile based activated carbon fiber, J. Power Sources 160 (2006) [56] H. Teng, Y. J. Chang, C. T. Hsieh, Performance of electric double-layer capacitors using carbons prepared from phenol formaldehyde resins by KOH etching. Carbon 39 (2001) [57] R.C. Bansal, J.B. Donnet, H.F. Stoeckli: Active Carbon (Marcel Dekker, New York 1988). [58] J.B. Donnet, R.C. Bansal: Carbon Fibers (Marcel Dekker, New York 1984). [59] YUKO IKEDA, elastomeric poly(oxyethylene) matrixes for ion conduction, Journal of Applied Polymer Science 78 (2000) [60] Bin Xua, Feng Wu, Renjie Chen, Gaoping Cao, Shi Chen, Yusheng Yang, mesoporous activated carbon fibers as electrode material for high performance 49

70 electrochemical double layer capacitors with ionic liquid electrolyte, Journal of Power Sources 195 (2010) [61] Jeffrey W. Fergus, Ceramic and polymeric solid electrolytes for lithium-ion batteries, Journal of Power Sources 195 (2010) [62] Bong Gill Choi, Jinkee Hong, Won Hi Hong, Paula T. Hammond, and HoSeok Park, facilitated ion transport in all solid state flexible supercapacitors, ASCNANO 5 (2011) [63] Jianying Ji, Bin Li, Wei-Hong Zhong, simultaneously enhancing ionic conductivity and mechanical properties of solid polymer electrolytes via copolymer multi-functional filler, Electrochimica Acta 55 (2010) [64] G.P. Pandey, Yogesh Kumar, S.A. Hashmi, Ionic liquid incorporated PEO based polymer electrolyte for electrical double layer capacitors: A comparative study with lithium and magnesium systems, Solid State Ionics 190 (2011)

71 CHAPTER 3 THEORETICAL STUDIES FOR EXPERIMENTAL MATHODES 3.1 Backgrounds for the Theoretical Studies The production and the storage of energy are important and very challenging. While numerous solutions have been found to produce energy, fewer are used to store it, among which batteries and supercapacitors are the two commonly utilized electrochemical energy storage devices. Batteries have good energy density, but their low power capacity and short cycling life are among the main issues for many applications. In contrast to batteries, conventional electrical capacitors have excellent power density and cycling capability, but very low energy density. Supercapacitors have a position filling the gap between batteries and conventional capacitors. In comparison with batteries, supercapacitors give higher power density and possess longer cycling life, while compared with conventional capacitors they can store more energy. Because of this position, supercapacitors intend to become a way to solve some energy storage problems, including those in hybrid devices [1-3]. The manufacturing of these supercapacitors can be complex and the influence of each parameter should be determined to have the best capacitance performance. To optimize the processes, the traditional way is based on the one-factor-at-a-time method. It consists of making several trials and modifying only one parameter each time. This method needs a lot of experiments and its realization is 51

72 possible only if all parameters are independent. A smarter economical approach is the Design of Experiments (DOE). The use of DOE is selective approach complex experimental setup. Several methods have been developed during the last decades. For example, linear and second degree models can be used and statistically determined to find the best composition of ceramics for firing shrinkage and water absorption [4]. Without trying to find a model, Taguchi s methods can be providing the influence of the different parameters on the growth of CNT and the optimization of a thermal CVD-system [5]. A third way, can be using for Yate s method which is optimization of a medium where cells can growth [4, 6]. These methods needed complex calculations to get the influence of each parameter by creating complex and approximated formula linking inputs and outputs. Refers to the process of planning an experiment so that appropriate data (which can be analyzed by statistical methods) will be collected, resulting in valid and objective conclusions. Our Basic Premise: All experiments are designed experiments, some are poorly designed, and some are well-designed. Well-designed experiments enable one to obtain reliable results faster, easier and with fewer resources. 3.2 Theoretical Design Parameter Selection For the calculation, we consider that we start with samples just before activation. In our experiments, we only consider the influence of four parameters: the proportions of fiber, CNTs, carbon coming from the carbonization of the polymer precursor and the activation time. The objective is to improve the value of capacitance built with this composite. 52

73 3.2.2 Grey Relational Model Since the eighties, a method named Grey Relational Model or Relation Grade Analysis has been developed to find effectively the influence of experimental parameters. It can determine the best combination of parameters in order to get the best results with a minimum number of tests. This method has shown great results in for the formulation of automotive friction based materials [7]. This theory has been combined with Tagushi s orthogonal arrays to determine the best way to optimize metal injection based processes [8]. Also, it has been used to create a practical diagnosis model to automatically check if a situation is normal or abnormal [9]. Another application is the determination of the most influent parameter in the laser cutting process [10].In this work, Relation Grade Analysis was used to find out what are the most influential parameters responsible for supercapacitors performance Grey Systems The theory of Grey systems is based on the fact that our universe is full of elements and interactions in which we do not have precise information (white systems) or we do not have any information (black systems). The systems around us are made mainly of greys [11]. Since the 1980 s, this theory has been developed, in order to find a way to solve complex problems with little information. In our work, the influence of the proportion of each constituent (carbonized polymer, carbon nanotubes and fibers) and 53

74 subsequent process such as activation time and temperature are not clearly defined. They are a part of grey system Relational Grade Analysis The Relational Grade Analysis or Grey Relational Numerical Method is a way to determines how a system works from raw inputs. A number of trials are needed. The parameters and the results do not have the same nature. In order to compare them, all the data from each ones are divided by the mean of these values. The sequences will be the inputs and the output. After this modification, the next step is the calculation of the Grey Relational Coefficient for each parameter and trial: (8) (9) Where i is the parameter number, k the trial number and with and minimum and maximum values on i and k of respectively. The coefficients shows how close two sequences are at k Є [0, 1] are coefficients which weaken the effect of Δ max on the Grey relational coefficient. In this work the value taken is 0.5. Then, in order to compare the influence of each input, we calculate each Grey Relational Grade: (10) 54

75 This coefficient is the average of the Grey Relational Coefficients and by this way two sequences can be compared globally. If that means is better to more than. So, we choose to increase the first parameter in order to get a higher value of our output [11, 12] Statistic Model on effect of CNT, PAN and Activation Time The objective of this part is to find the best factor that promotes the largest specific BET surface area in order to get the greatest capacitance of a supercapacitor. To develop a large surface area, the following factors described below were selected Factors Selection These factors will be changing in two levels (high and low). - CNT Existence (with & without) - Pan Existence (with & without) - Activation Time (1 & 4 hours) In this experiment, experimental values of BET for surface area were used along with the software tools to handle the analysis. (Software: Student trial version of Design- Expert , Minitab 14, and MS.) 55

76 Linear Models with One Independent Variable This model was carried out when there is only one variable or factor in the design and the resulting equation will look like: y = ax + b. Where y is the response, x is the dependent variable, and a, b are the parameters that are going to be determined. The method used here is the uses of the least square, just like the trend line in excel [13] Linear Models with Two or More Independent Variables This model is very simplistic because only the effects of single parameter and cross interaction are concerned. A simple equation of this kind can be used: z = ax + by + c. Where a, b, and c are the determined parameters and x, y, and z are the pre-determined parameters with z being the response variable. This is called two level factorial designs which are 2 2 = 4 possible combinations of the factors where they will be a combination of the low and high levels of each factor and their effect on the response [14]. The determined parameters (c, b, and a) can simply be defined by the following these equations: (11) 56

77 (12) (13) where c represent the mean of all the responses and a, b are the averages of the responses for each variable. Three independent variables were taken and were tested. Giving each one of them a low and high response makes them have 8 points. This can be put in a cubic diagram to illustrate the high and low levels responses of each independent variable as shown in Figure 17. Figure 17: Cubic diagram to illustrate the high and low levels responses of each independent variable [14] Nonlinear Models Data can be fitted in more complicated method like the use of the natural log if they don t show significant result with the linear method [14]. 57

78 Data Specifications Extra Recorded Data To insure all needed data is present at the time of the calculations, the following list of data was recorded at each run: Initial Weight. Weight after Stabilization. Weight after Carbonization. Weight after Activation Response Variable One response variable is recorded here, which is the surface area is calculated by T technology and it uses an average of three samples just because the device that measures surface area needs at least these three samples to detect a significant change in the volume of nitrogen and then be able to give the exact BET specific surface area [14]. 58

79 Control Variables There are three variables that will be modified in which the key factors will be determined at the end of the plan of experiment and the non-affecting variables will be removed if they were not significant. These variables are presented as follows: Table 2: Factor level definitions. Factor Low Level (-1) High Level (+1) A: CNT Without With (30% CNT) B: PAN Without With (5% Concentration) C: Activation 1 hour 4 hour Fixed Variable These variables are held constant throughout the experiment: Activation temperature is set to be at 850 o C Existence of Fiber in all samples. Oven Furnace Operator 59

80 Uncontrollable Nuisance Factors not: These factors are recorded to check if they have any effect on the experiment or Initial Weight Weight after Stabilization Weight after Carbonization Weight after Activation Statistic Run Design Steps In this experiment, there will be three design steps used for analysis. i. Build a 2 3 factorial designs. Use the run of random order and ANOVA test will be the method to determine the significance and interactions between each factor. ii. Factor Screening Design: Given the results of the first step and the effective factors, this model will be build up. So if there was no 60

81 significance and no interactions in one of the variables, the model will still be 2 3 factorial but with lower number of interaction factors used. iii. Use a log transformation to show the effect of the growth data response. An explanation of the reason on using this method is represented in section Test Matrix and Procedure Table 3: describes the test matrix for 2 3 full factorial design for the basic matrix and the meanings of the -1, and 1 here are low and high level sets respectively as described in the right three columns. CNT ranges from (0-30) % as the high level. Similarly, PAN is represented between (0 5) %. And Activation time is set from one hour activation to 4 hour activation. 61

82 Table 3: Initial standard order test matrix. C C Standard Order Design Point A (CNT) B (PAN) Activation A (CNT) B (PAN) Activation Time Time (hours) without Without 1 2 A with Without 1 3 B without With 1 4 AB with With 1 5 C without Without 4 6 AC with Without 4 7 BC without With 4 8 ABC with With 4 62

83 3.3 Conclusions Using Gray Relational Analysis approach will facilitate our processing formulation. We will be in a position to determine what composition and activation time are required to achieve the best supercapacitor performance. We believe this parallel approach based on experimental and numerical will determine the best processing scenario for the fabrication of an optimized electrode capacitance. 63

84 3.4 Bibliography [1] Erik Schaltz, Alireza Khaligh and Peter Omand Rasmussen, influence of battery ultracapacitor energy storage sizing on battery lifetime in a Fuel Cell Hybrid Electric Vehicle, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 58 (2009) 8. [2] Phatiphat Thounthong, Viboon Chunkag, Panarit Sethakul, Suwat Sikkabut, Serge Pierfederici, Bernard Davat, Energy management of fuel cell/solar cell/supercapacitor hybrid power source, Journal of Power Sources 196 (2011) [3] S.L. Correia, D. Hotza, A.M. Segadães, Simultaneous optimization of linear firing shrinkage and water absorption of triaxial ceramic bodies using experiments design, Ceramics International 30 (2004) [4] S. Porro, S. Musso, M. Giorcelli, A. Chiodoni, A. Tagliaferro, Optimization of a thermal CVD system for carbon nanotube growth, Physica E 37 (2007) [5] J. A. Casas, S. Garcia de Lara, F. Garcia-Ochoa, Optimization of a synthetic medium for Candida bombicola growth using factorial design of experiments, Enzyme and Microbial Technology 21 (1997) [6] Y. Lu, a golden section approach to optimization of automotive friction materials, Journal of Materials Sciences 38 (2003)

85 [7] Mohd H.I. Ibrahim, Norhamidi Muhamad, Abu B. Sulong, Khairur R. Jamaludin, Nor H.M. Nor, Sufizar Ahmad Chiang, Optimization of micro metal injection molding with multiple performance characteristics using grey relational grade, Mai J. Sci. 2011; 38(2): [8] Yong-Huang Lin, Pin-Chan Lee, Ta-Peng Chang, practical expert diagnosis model based on the grey relational analysis technique. Expert Systems with Applications Expert Systems with Applications 36 (2009) [9] Ulas Caydas, Ahmet Hascalık, Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics, Optics & Laser Technology 40 (2008) [10] David K. W. Ng, Grey system and grey relational model, ACM SIGICE Bulletin 20 (1994) 2-9. [11] J. Drbohlav, W. T. K. Stevenson, The oxidative stabilization and carbonization of a synthetic mesophase pitch, part I: The oxidative stabilization process, Carbon 33 (1995) [12] J. Drbohlav, W. T. K. Stevenson, The oxidative stabilization and carbonization of a synthetic mesophase pitch, part II: The carbonization process, Carbon 33 (1995) [13] Energy density. wikipedia. [Online] Jan 25, [Cited: Jan 26, 2012.] 65

86 [14] Design of Experiments. Washington State University. N.p., n.d. [Online] [Cited: June 21, 2012.] 66

87 CHAPTER 4 EXPERIMENTAL SETUP 4.1 Sample Preparation Prepare Polymer Precursor Solution Polyacrylonitrile (PAN) powder (MW 150,000) purchased from Polysciences Inc. was used as the polymer precursor for deposition of activated carbon on the substrate. Specific amounts of PAN powder was first mixed with dimethylformamide (DMF) in a beaker agitated with a magnetic stir bar. The mixture was heated on a hot plate until a homogenous clear solution was reached, as it is shown in Figure 18. Figure 18: PAN solution used for coating sample. 67

88 4.1.2 Coating and Dry Samples Carbon fabric and its corresponding carbon fabric grown with carbon nanotubes were used as the substrates. Samples were cut into 1-2cm 2 square pieces from the fabric materials, before being weighted using an analytic balance. The samples were immersed into the solution of 5% PAN in DMF, followed by being moved out and heated over a hot plate to evaporate the solvent. The coating procedure was repeated three to nine times until the desired PAN thicknesses were achieved. The coated samples were then placed in a vacuum oven and a pressure reaching 6 in of Hg was executed, while temperature of the oven was maintained at 55 o C for 30 min (Figure 19), and finally the samples were taken out and weighted to determine the mass of the precursor coated on the samples. Figure 19: Vacuum oven model 282A from Fisher scientific used for treating the PAN coated fabric samples. 68

89 Figure 20: Fiber sample. Figure 21: Fuzzy fabric (Fiber + CNT) sample. 69

90 Figure 22: Fiber composite (Fiber + PAN) sample before thermal process. Figure 23: Fuzzy fabric composite (Fiber + CNT + PAN) sample before thermal process 70

91 Figure 24: Fiber composite (Fiber + PAN) sample after thermal process Figure 25: Fuzzy fabric composite (Fiber + CNT + PAN) sample after thermal process 71

92 4.1.3 Stabilization Process The stabilization step was performed by heating the PAN-coated samples in an oven (Lindbergh / Blue M) (Figure 26) at 215 o C in an environment of flowing air at the rate of 2 L/min for 20 hrs. The thermal process is for reducing reactivity of the material to prevent unwanted reactions. Temperature of 215 o C was selected, for a lower temperature may give results of insufficient stabilization while higher temperature can cause unwanted over oxidation that may result in structural defects and cyclization of the nitrile groups in PAN and formation of a cross-linked ladder polymer. After finishing the stabilization step, the samples were removed and or weighted to monitor the change of weight. Figure 26: Oven utilized for stabilization prior to the carbonization step Carbonization Process After completing the stabilization step, samples were placed in a quartz tube that was placed in a tube furnace (Lindbergh / Blue M) (Figure 27). The quartz tube was then 72

93 purged with argon (Ar) using a flow of 800 ml/min for 10 min. This was followed by reducing Ar flow to 200 ml/min and arising furnace temperature from room temperature to 850 o C ₒ at rate of 10 o C/min, and keeping the samples at 850 o C for 1 hr. Finally, power of the furnace was turn off, and the samples were let to cool down naturally and the samples were removed and weighted. The carbonization step was used in order to convert the organic precursor into a carbon the decomposition of the material included dehydrogenation, condensation, and isomerization reactions. The resulting compound should have around 90% carbon yield by weight. Figure 27: Tube furnace for carbonization 73

94 4.1.5 Activation Process The activation step was carried out in a similar manner as carbonization step. Samples were heated from room temperature to 800 o C at a rate of 10 o C/min under the protection of Ar flow. When temperature reached 800 o C, 200 ml/min carbon dioxide gas was introduced into the reaction tube and the samples were kept at that temperature for various defined periods. At the end of the activation, Ar was introduced to replace carbon dioxide and the furnace was cooled down naturally. 4.2 Preparation Liquid and Solid Electrolyte Aqueous sulfuric acid solution (H 2 SO 4 ) with 1 M concentration was used as the liquid electrolyte for the supercapacitor studies. The electrolyte was prepared by diluting a concentrated sulfuric acid (98%). Conversely, in the case of a solid electrolyte, a mixture of polyethylene oxide (PEO) powder (average Mv 400,000) purchased from Sigma-Aldrich and potassium hydroxide was used. To prepare the solid electrolyte, a defined amount of water was added into the mixture of PEO and potassium hydroxide to form a paste. The paste was then applied on the carbon fabric electrodes. The samples were left in the vacuum oven at 55 o C for 30 min while vacuum level was kept at 6 in of Hg. 74

95 4.3 Supercapacitor Construction and Testing The samples were cut into approximately 1 by 0.3 cm strips. Configuration of a supercapacitor cell had two carbon fabric samples sandwiching a porous glass fiber paper, which was acting as the separator for preventing electrical shortening during the test valuation (Figure 28). Two pieces of titanium plates having identical size were used to clamp the cell. The titanium plates performed also as the current collectors of the supercapacitor cell. The carbon electrodes were placed at one end of larger metal plates so that they could be immersed in the liquid electrolyte solution while keeping the wires at the other end very dry. An electrochemical workstation Model 600C Series from HCH Instruments was employed to conduct the supercapacitor test, as shown in Figure 29. Typical techniques utilized to characterize the supercapacitors included cyclic voltammetry and charge/discharge. For carrying out the test using the liquid electrolyte, the lower half of the capacitor containing the carbon electrodes was submersed in 1 M H 2 SO 4 solution. The wires attached to the Titanium current collectors were attached to the positive and negative leads of a potentiostat. For cyclic voltammetry measurement, a 1 V range was used, cycling from +0.5 V to -0.5 V. Each sample was tested using eight different potential scan rates, ranging from to 1 V/s. 75

96 Figure 28: Capacitor construction. Figure 29: Experimental setup of the supercapacitor immersed in a 1M H 2 SO 4 electrolyte solution and connected to electrochemical workstation 76

97 Figure 30: Model 600C Series Electrochemical Workstation from HCH Instruments In a cyclic voltammogram the current I that flows through an electrochemical cell is plotted versus the voltage V that is swept over a given voltage range. A linear voltage ramp was used in the sweep. Often, a cyclic voltammogram test will repetitively sweep the voltage between the two limiting potentials. A pair of voltage sweeps in opposite directions gave a cycle. A voltage sweep applied to the capacitor created a current given by Equation: 77

98 dv/dt is the scan rate of the linear voltage ramp. The specific capacitance was calculated using the integrated area of the CV curve to obtain the charge (Q), and subsequently dividing the charge by the mass of the electrode active material (m) and the width of the potential window (ΔV): Cs=Q/b (mδv) (15) Q=1/u ʃ v2 v1 I (V)*dV (16) Where u is the scanning rate. Galvanostatic charge/discharge cycling was also performed at constant current densities. The obtained chronopotentiograms could be used for determination of specific capacitance from the slope of the V = f (t) curves, using the following equation: C =I/ (dv/dt) (17) where C is the capacitance of the cell in farad, I the discharge current in ampere (A) and dv/dt is the slope in volt per second (V s - 1). The specific capacitance Cs in farad per gram of activates material (F g - 1) is related to the capacitance of the cell C by: Cs =2C/m (18) 78

99 Where m is the weight (g) per electrode of activate material, i.e. activated carbon and carbon nanotubes [1-3]. 4.4 Characterization Tools Brunauer, Emmett and Teller (BET) BET stands for the family initials of Brunauer, Emmett and Teller, the scientists who developed this technique. The instrument used for the BET measurement is shown in Figure 41. The BET theory is commonly used to evaluate the gas adsorption data and generate a specific surface area result expressed in units of area per mass of a sample (m 2 /g). The amount of gas adsorbed, at a given pressure allows to determine the surface area. Gas used in the BET is nitrogen in its liquid form [4] 79

100 Figure 31: Brunauer, Emmett and Teller (BET) instrument. The methodology of the BET technique is that a clean solid surface adsorbs the surrounding gas molecules. The physical adsorption of a gas over the entire exposed surface of a material and the filling of pores is called physisorption. Physisorption is used to measure total surface area and pore size [5]. Pore size analysis is usually done using traditional kelvin equation models which is a relationship between σ stress, ε strain and their rates of change: (19) 80

101 More surface area develops better supercapacitor, it was found out that having high surface area stores more energy and therefore makes the supercapacitor more feasible. In addition, we used Nitrogen gas as the adsorbed species and we can use other gases like Carbon dioxide and Helium when we have sample possess a high amount of micro porosity. Nitrogen is used because it is available in high purity at a reasonable cost and the molecular size [6] Scanning Electron Microscopy (SEM) Scanning Electron Microscopy (SEM) is an electron microscopy technique that can provide some information on the sample morphology and surface characteristics (Figure 32). Figure 32: Scanning Electron Microscopy (SEM). 81

102 4.5 Bibliography [1] Zhen Fan, Jinhua Chen, Bing Zhang, Bo Liu, Xinxian Zhong, Yafei Kuang, high dispersion of γ-mno2 on well-aligned carbon nanotube arrays and its application in supercapacitors, Diamond & Related Materials 17 (2008) [2] Li-Jie Sun, Xiao-Xia Liu, electrodepositions and capacitive properties of hybrid films of polyaniline and manganese dioxide with fibrous morphologies, European Polymer journal 44 (2008) [3] Wei-Chih Chen, Ten-Chin Wen, Electrochemical and capacitive properties of polyaniline-implanted porous carbon electrode for supercapacitors, J Power Sources 117 (2003) [4] BET Theory. Wikipedia. [Online] [5] BET Surface Area & Gas Adsorption. Quantachrome. [Online] [6] Equipment for Measuring the Specific Surface Area of Cryo Materials. BET, Surface Adsorption. [Online] [Cited: Mar 12, 2012.] [7] McMullan, D., scanning electron microscopy , Scanning 17 (1995) [8] McMullan, D., von Ardenne and the scanning electron microscope. Proc Roy Microsc Soc 23 (1988)

103 [9] Knoll, Max., a ufladepotentiel und Sekundäremission elektronenbestrahlter Körper, Zeitschrift für technische Physik 16 (1935) [10] Von Ardenne M., Improvements in electron microscopes. GB , convention date (Germany) 18 Feb 1937 [11] Von Ardenne, Manfred, Das Elektronen-Rastermikroskop, Theoretische Grundlagen (in German). Zeitschrift für Physik 109 (1938) [12] Von Ardenne, Manfred, Das Elektronen-Rastermikroskop, Praktische Ausführung (in German). Zeitschrift für technische Physik 19 (1938) [13] Zworykin VA, Hillier J, Snyder RL, a scanning electron microscope. ASTM Bull 117(1942) [14] McMullan, D., an improved scanning electron microscope for opaque specimens. Proc Inst Electr Engrs 100 (1953) [15] Oatley CW, Nixon WC, Pease RFW, scanning electron microscopy. Adv Electronics Electron Phys 21 (1965) [16] Smith KCA, Oatley, CW, the scanning electron microscope and its fields of application Br J Appl Phys 6 (1955) [17] Wells OC, the construction of a scanning electron microscope and its application to the study of fibres. PhD Dissertation (1957) Cambridge University. 83

104 CHAPTER 5 RESULTS AND DISCUSSION 5.1 Calculated Results Based on Grey Relational Model from Experimental Entry Grey Relational Model Results A number of samples were prepared following the steps of coating, stabilization, carbonization and activation with variables from the carbon fiber substrates, polymeric precursor, carbon nanotubes, and the conditions of stabilization, carbonization, and activations, as listed in Tables 4. Also, it included the capacitance values determined from the electrochemical tests carried out in the 1 M H 2 SO 4 electrolyte. Tables 5-7 are showing results from applying Grey Relational Model and calculations. It is shown that although a thicker layer was obtained, increasing the amounts of the polymeric precursor, would actually lead to a larger specific surface area and consequently a higher value of specific capacitance. While increasing the amount of the polymeric precursor, amount of the carbon nanotubes should also be increased to keep the capacitance to its high value. It was also seen that decreasing time of activation was needed to achieve higher capacitance when the amounts of carbon nanotubes in samples were increased. 84

105 Table 4: Definition of variables. Variables Fiber g CNT g Polymer (PAN) Activation Time Hour/s Specific Capacitance F/g Sample No Average X 1 X 2 X 3 X 4 X

106 Table 5: Application of the first step. Variables Fiber g CNT g Polymer (PAN) Activation Time Hour/s Specific Capacitance F/g Sample No. X 1 /X 1 X 2 /X 2 X 3 /X 3 X 4 /X 4 X 0 /X 0 Avg Avg Avg Avg Avg

107 Table 6: Comparison with the output. Variables Fiber g CNT g Polymer (PAN) Activation Time Hour/s Sample No. X 0 -X 1 X 0 -X 2 X 0 -X 3 X 0 -X 4 Max Min

108 Table 7: Calculation of ζ and γ. Variables Fiber CNT Polymer (PAN) Activation Time Sample No Gamma

109 5.1.2 Discussion As shown in the tables 4-7, the calculation leads to two conclusions: the first one is that we need to increase the amount of polymer, in order to obtain a thicker layer of carbonized polymer with porosities. These results of the activation process allow a great increase of the specific surface area, and consequently higher specific capacitance. At the same time, we are supposed to increase the amount of CNT by using more coated veil. CNTs permit an increase of specific surface area and electrical conductivity percolation. Conversely, we need to decrease the activation time in order to reach higher capacitance while increasing the amount of CNT in the pristine sample. For the sake of statistical data, many samples were made and numerous tests with long cycles were carried out to check for reproducibility and more accurate results. Finally, the best we capacitance value was about F/g. 89

110 5.1.3 Conclusion The use of the Grey Systems Theory was to optimize the value of supercapacitors based on fuzzy fiber composite. Based on this approach, it appears that the numerical prediction was in agreement with the experimental data. Indeed, the higher amount of CNT in the activated composites, the better specific capacitance. In another word, CNT provide both high conductivity and higher surface area and higher coefficient of diffusion of the electrolytes. So, the use of the Grey Systems Theory provides a good comprehension of the influence of each parameter on the specific capacitance. 90

111 5.2 Statistic Model on effect of CNT, PAN and Activation Time Statistic Model Results Table 8 shows the results of the eight runs with the change in surface area by using surface area. Table 8: Experiment results. Standard Order Design Point A CNT B PAN C Activation Time A CNT B PAN C Activation Time (hours) Response Surface Area (m 2 /g) without Without A with Without B without With AB with With C without Without AC with Without BC without With ABC with With

112 From this table one can observe that having CNT, PAN and more activation time gives the highest surface area. However, which factor has the highest impact and how could that affect be calculated as a surface area result is what is aimed after the following study Analysis of First ANOVA Step In this step, ANOVA is to be used to determine the significant factors and interactions between all given factors that might have an effect on the surface area Nuisance Factors Analysis Table 9: Nuisance factors Standard Order Design Point Surface Area (m 2 /g) Initial Weight Stabilization Weight (g) Carbonization Weight (g) Activation Weight (g) A B AB C AC BC ABC

113 The variance (ANOVA) test for the captured nuisance factors have been tested by Minitab. The difference on weight after each step (stabilization, carbonization, and activation) is the factor that has been tested because it is the deriving factor. The following effects have been noticed: One-way ANOVA: Surface Area, Weight after Stabilization Source DF SS MS F P Factor Error Total S = R-Sq = 10.51% R-Sq(adj) = 4.12% - This ANOVA test shows that there is no significant influence of stabilization weight on the surface area. One-way ANOVA: Surface Area, Weight after Carbonization Source DF SS MS F P Factor Error Total S = R-Sq = 10.51% R-Sq(adj) = 4.09% - This ANOVA test shows that there is no significant influence of carbonization weight on the surface area. 93

114 One-way ANOVA: Surface Area, Weight after Activation Source DF SS MS F P Factor Error Total S = R-Sq = 10.51% R-Sq(adj) = 4.11% This ANOVA test shows that there is no significant influence of activation weight on the surface area Scatterplot of Surface Area vs Weight After Activation 1500 Surface Area Weight After Activation Figure 33: Scatterplot of surface area vs. weight after activation. 94

115 Figure 33 shows the scatterplot of the surface area and weight after activation. It is clear that the weight does not follow any kind of behavior with respect to the surface area response and the ANOVA test earlier is the statistical proof for that. However, it is know that activation time has a big effect on making more surface area. An explanation for this is due to the fact that this comparison is not only between different activation times, but also with the presence of CNT and PAN. One could easily notice that when PAN is not present, weight after activation increases but surface area response does not. This is because the activation time is done to pure CNT and that the sample is being wasted more than being activated because it is already in nano state pores and has minimum connections between particles. Therefore, there are no affect for these nuisance factors in the final surface area response factor Qualitative Observations Table 8 shows the results of the eight runs of the experiment. In this section, Observation discussions of Figures on the largest and lowest responses will be done as a starting point of the analysis: 95

116 Design-Expert Software Correlation: Color points by Run S u rfa c e A re a A:CNT Figure 34: Shows that having high level of CNT in the four runs out of eight runs gives higher surface area. The largest change on surface area for only one high level factor is when CNT was added and acts as the only high level factor and that is reasonable for Carbon-Nano- Tubes which having a high surface area because of being in the Nano scale. Design-Expert Software Correlation: Color points by Run S u rfa c e A re a B:PAN Figure 35: Shows that having high level of PAN in the four Runs out of eight runs gives higher surface area. 96

117 The largest surface area when two factors are set to their high level is when there is CNT and PAN added. Design-Expert Software Correlation: Color points by Run S u rfa c e A re a C:Activation Figure 36: Shows that having high level of activation time which in this case is four gives higher surface area. It is also obvious the effect of the third factor which is activation along with adding the two factors CNT and PAN. When there exists CNT in the sample there is only a chance to have a high SURFACE AREA when there is PAN in the sample and it has the highest surface area when having 4 hour activation time too Variance Analysis (ANOVA TEST) Table 10 shows the effect and contribution of each factor along with the relationship between the factors for Non-Transformation Model. Both factors a means CNT and B means PAN here show the highest effects and factor C means Activation time also shows a reasonable effect that cannot be neglected. The contribution is another easier way of 97

118 looking at the effect of these factors and the predicted relationship between them. This table is not accurate and will change as the transformation change and will be represented in section as the transformation will change to log transformation. The following are subsections of step by step procedure to find the most parsimonious model for the largest surface area noticing that the highest order term (ABC) will not be included because, if it were to be used, there will be no degrees of freedom left for the ANOVA analysis. Table 10: Effects and contribution of each factor in the experiment in nontransformation model Term Effect Sum Square % Contribution A (CNT) x B (PAN) x C (activation Time) x AB x AC x BC x ABC x

119 First Design: Factors A, B, C, AB, AC, and BC are Included with No Transformation Table 11: First model ANOVA table (factors included are A, B, C, AB, AC, BC) Source Sum of Squares Degrees of Freedom Mean Square F Value p-value Probabili ty > F Model 2.524x x not significant A (CNT) 5.488x x B (PAN) 6.098x x C (Activation Time) 3.066x x AB 5.158x x AC 2.42x x BC 3.014x x Residual 2.377x x10 5 Cor Total 2.762x Std. Dev R-Squared Mean Adj R-Squared C.V. % Pred R-Squared PRESS 1.251x10 7 Adeq Precision

120 Table 11 shows that this model has a 51.93% chance that it occurs just randomly. This result extends to all of the other results of removing a factor or two. A solution to fix this and get a significant results statistically is to first remove one or more interaction factor like AC since it has the lowest contribution and effect to the surface area response and if that does not work use a log transformation to get a more accurate results. 100

121 Second Design: First Model: Factor A, B, C, AB, and BC are Included with No Transformation Table 12: second model ANOVA table (factors included are A, B, C, AB, BC) Source Sum of Squares Degrees of Freedom Mean Square F Value p-value Probabilit y > F Model 2.28E E not significant A (CNT) 5.49E E B (PAN) 6.10E E C (Activati on Time) 3.07E E AB 5.16E E BC 3.01E E Residual 4.80E Cor Total 2.76E+06 7 Std. Dev R-Squared Mean Adj R-Squared C.V. % Pred R-Squared PRESS Adeq Precision

122 Table 12 shows a better result than with using all the factors that can be seen from reducing the noise factor which is the percentage that shows how random is the result from above 50% to 37.93%. However, this result is still too high to be trusted and used as our results. A further reduction of the second low effect factor BC might resolve this issue Second Model: Factor A, B, C & AB are Included Table 13: Second model ANOVA table (factors included are A, B, C, AB) Source Sum of Squares Degrees of Freedom Mean Square F Value p-value Probabilit y > F Model 1.98E E not significant A (CNT) 5.49E E B (PAN) 6.10E E C (Activatio n Time) 3.07E E AB 5.16E E Residual 7.81E Cor Total 2.76E+06 7 Std. Dev R-Squared Mean Adj R-Squared C.V. % Pred R-Squared PRESS Adeq Precision

123 This model shows a small improvement but still not significant to be trusted as a result of the nuisance factor Third Design: Using a Natural Log Transformation Log transformation is commonly used in size data. It basically depends on taking the natural log of each response. In this case a lower and upper bound to limit the responses between zero and 1900 is used. This kind of transportation is used because the response is ranged between these two values and in general is used when these values have a high range between them. Table 14: Effect and contribution of the factors in Logit transformation Term Effect Sum Square % Contribution A (CNT) B (PAN) C (Activation Time) AB AC BC ABC

124 Table 14 shows a more accurate contribution of the given factors than in table 10. As will be seen in the figures 38 to 40, CNT is the highest contribution of 41.69% toward increasing surface area. Next factor is the PAN that has also a high contribution of 35.23% in the surface area. And then, the activation time is the lowest between them to have 11.36% contribution to the surface area. 104

125 Table 15: Third design ANOVA table. Source Sum of Squares Degrees of Freedom Mean Square F Value p-value Probabilit y > F Model 9.90E E significant A-CNT 4.13E E B-PAN 3.49E E C- Activation Time 1.12E E AB 3.54E E AC 2.24E E BC 8.03E E Residual 1.13E Cor Total Std. Dev R-Squared Mean Adj R-Squared C.V. % Pred R-Squared PRESS Adeq Precision This design shows a significant result of the ANOVA test with a 2% chance of being a result of a random or noise effect. The Predicted R-Squared value is close enough from the Adjusted R-Squared and therefore a more analysis on this successful result is shown in the next section. 105

126 Best Model As a result of the previous models and by the ANOVA test, it is clear that the third model that used the natural log transformation provides the most promising model and it is therefore chosen to be the most satisfied model for our analysis. Table 16: Coefficient estimates of each factor of the most parsimonious Factor Coefficient Estimate Degrees of Freedom Standard Error 95% CI Low 95% CI High VIF Intercept A (CNT) B (PAN) C (Activation Time) AB AC BC

127 * CNT * PAN * Activation * CNT * PAN * CNT * Activation * PAN * Activation (20) Equation 20: of Surface area estimate of the most parsimonious model. Now, using this equation and between only the parameters given in this experiment of low point to high point, we can find the surface area result and play with the parameters to maximize it. Low level of CNT means no CNT present in the sample and high level means that there is 30% CNT in the sample. Similarly, low level of PAN means no PAN present in the sample and high level means that the sample has 5% present PAN. For activation time, low level is one hour activation time and high level means four hour activation. Figure 37 shows that all the runs are perfectly fitted along the predicted line which means that the estimate found is a good one for the tested runs. 107

128 Design-Expert Software Surface Area Original Scale (median estimates) Color points by value of Surface Area: Predicted vs. Actual P re d ic te d Actual Figure 37: Predicted vs. actual values of surface area. Figures 38 to 40 shows the resulted interaction between two factors of the three factors with the third one in each figure set to be mid-point between low and high level. The result in figure 45 shows that the maximum surface area result that can be obtained with 2.5 hours is 1288 m 2 /g and that is found when there is 30% CNT and 5% PAN. It is also noted that with 2.5 hour activation, increasing the amount of CNT and PAN do not affect the surface area a lot in the beginning; that is to say the surface area increased from 0 to 100 m 2 /g when we added 10% of CNT and 3.33% of PAN but after that the surface area started to change quickly as we reached 1288 m 2 /g response with 15% CNT and 5% PAN. 108

129 Design-Expert Software Factor Coding: Actual Original Scale (median estimates) Surface Area Surface Area X1 = A: CNT X2 = B: PAN Actual Factor C: Activation = 0.00 B : P A N A: CNT Figure 38: Contour surface representation of the effects of CNT and PAN Figure 38 shows the effect between CNT and Activation time when PAN level is set to be 37.5% mid-point. This graph shows a different effect than figure 37. It shows that, there is hardly any effect of activation when there is no CNT present in the sample which can be seen in the left side of the graph when CNT in its low level meaning no CNT at all is added and the surface area response starts from 1 to 8.5 m 2 /g and that is only the effect of activation on the 2.5% PAN present on the sample and as can be seen is worthless without CNT. However, as CNT is added from the left of the graph to the right it is shown that activation does increase the surface area. That can clearly be seen in the graph on the right hand side when CNT is in its high level (15% in the sample) the 109

130 sufrace area response starts from 72 m 2 /g surface area when there is only one hour activation to about 600 m 2 /g for four hour activation. Another impression from this figure is that the maximum surface area that could be achieved with 2.5% PAN was 600 m 2 /g which combairing with Figure 38 means that PAN had a stronger effect on its abcense than the abcense effect of activation. Design-Expert Software Factor Coding: Actual Original Scale (median estimates) Surface Area X1 = C: Activation X2 = A: CNT Surface Area Actual Factor B: PAN = 0.00 A : C N T C: Activation Figure 39: Contour surface representation of the effects of CNT and activation time. Figure 40 shows the effect between the PAN amount and activation time when CNT is fixed in the sample to be 7.5% mid-level. 110

131 First impression from this figure is that the maximum surface area response is 945m 2 /g which also shows that the contribution of the presence of PAN is high combairing with activation time because of how low the surface area response became combaired with Figure 39. With having 7.5% of CNT it is also clear that PAN and Activation have very small contribution if they are alone as can be seen if one of them is set to be minimum and the other is a variable. However, when they both unite, they represent a high contribution to the sample to give a high sufrace area response. Design-Expert Software Factor Coding: Actual Original Scale (median estimates) Surface Area Surface Area X1 = B: PAN X2 = C: Activation Actual Factor A: CNT = 0.00 C : A c tiv a tio n B: PAN Figure 40: Contour surface representation of the effects of PAN and activation time. Now that the contour plots has been shown and explained, a clearer picture can be shows in the 3D Figures

132 Figure 41 : 3D Surface representation of the effects of CNT and PAN. 112

133 Figure 42: 3D Surface representation of the effects of CNT and activation time. 113

134 Figure 43: 3D Surface representation of the effects of PAN and activation time Conclusion Surface area response shows the best comparative results in high level of the three given parameters; CNT amount, PAN amount, and activation time. Equation given in section shows the response between low and high points only. Graphs in the same section support that the surface area is maximized in the high levels of tested variables. However, it is known that more activation of this material makes the surface area to increase to its maximum and then it decays. This is not shown in this test because the tested activation time was not high enough to show such response. 114

135 Numerical Optimizations Using Numerical Optimization to maximize the surface area response, the following table 17 is presented and a linearization for the CNT, PAN and Activation factors were carried out so that it would be easier to observe the effect of each factor.. The table 17 has 21 different solutions. Eighteen of these solutions fall into the 90% desirability of maximizing the surface area to have a magnitude of to m 2 /g. As the study earlier have shown that activation process does not act as strong as the other two factors, CNT and PAN.As shown in the Figure 44 is that the peak is approaching a steady level of surface area response in the red area. It is known from the literature that after this peak, the surface area response will tend decrease. To prevent this cause of losing surface area when trying to maximize it by applying more activation time, it is recommended but not conclusive to stay within the 90% desirability and not go all the way to the maximum. Figure 44: Numerical optimization 3D graph. 115

136 Table 17: Numerical optimization table. Solutions Number Linearized Factors CNT PAN Activation SURFACE AREA Desirability % 5.00% % % 5.00% % % 5.00% % % 4.98% % % 5.00% % % 5.00% % % 5.00% % % 5.00% % % 5.00% % % 5.00% % % 5.00% % % 5.00% % % 4.70% % % 5.00% % % 5.00% % % 5.00% % % 4.33% % % 5.00% % % 5.00% % % 5.00% % % 5.00% % 116

137 Recommendations The use of a broader range along with center points is highly recommended to get accurate measurements in between and to know the effect of each factor after and before the set high and low levels in this experiment. 5.3 Materials Characterization at Various Processing Steps Liquid Eelectrolyte based Electrodes Figures show SEM images of the capacitor samples at different steps in the fabrication process. As shown in Figure 45, the carbon fabric was made of textured carbon fibers with a diameter around seven micrometers. The gaps among these fibers left essentially space for easy deposition and penetration of the polymer solution. Figure 46 showed the carbon fibers grown with the carbon nanotubes. It was found that depositing activated carbon layers on the carbon fabrics gave different morphologies, depending on if the deposition was carried on the plain carbon fabrics or on those grown with the carbon nanotubes. Figure 47 clearly shows that the activated carbon formed on the plain carbon fabrics was smoother and more compact, while that on the CNT-grown fabrics had rough and porous surface characteristics. 117

138 Figure 45: Carbon fiber substrate. Figure 46: Carbon nanotubes grown on carbon fibers. 118

139 Figure 47: Activated carbon fabricated on carbon fibers. Figure 48: Activated carbon fabricated on carbon fibers covered with CNTs. 119

140 First of all, the electrochemical performance of the carbon fabric and the activated carbon deposited carbon fabric samples were investigated. The samples used for the investigation were the carbon coated carbon fabric prior to the activation process, and those activated for 1 and 4 hrs. Figure 49 (a) and (b) shows their cyclic voltammograms recorded at the scan rate of 100 mv/s, and charge/discharge performances carried out at 0.1 ma, respectively. Compared to the sample that was not subjected to any activation treatment, the sample activated for a time as short as 1 hour exhibits a significant increase in current in the cyclic voltammograms, as it is clearly shown in Figure 49 (a), indicating that the treatment in the flow of carbon dioxide gas at 800 o C could efficiently create some porosities and increase surface area for the carbon converted from the polymeric precursor. It can also be seen that increasing the activation time to 4 hours further increased the current. This demonstrates that increasing the activation time more surface area was accessible to the electrolyte to contribute to the charge separation at the electrical double layer at the interface between the carbon material and the 1 M H 2 SO 4 electrolyte. The charge/discharge tests leaded to similar conclusions. In Figure 49 (b), charged/discharged at the current, the sample that was activated for 1 hour had significant longer time of charge and discharge, compared with the carbon coated fabric sample prior to the activation treatment. It required even longer time to charge and discharge for the sample that was activated for 4 hrs. These results were in agreement with those of cyclic voltammograms, showing that the activation process worked effectively on the carbon coating formed from carbonized PAN. 120

141 Figure 49: (a) Cyclic voltammogram of the Fiber +PAN composite samples Cycled from -0.5 V to +0.5 V at various activation times. (b) Charge/discharge curves of Fiber +PAN composite samples at various activation times. 121