Applied Science, Faculty of
Engineering, School of (Okanagan)
DSpace
UBCO
Yavarinasab, Adel
Master of Applied Science - MASc
University of British Columbia
In this research, the application of electrochemical impedance spectroscopy (EIS) for electrochemical detection of different components in aqueous media (water, KCl solution, and standard electrolyte solutions) is scrutinized. One of the main advantages of electrochemical sensors compared to other electrical- or optical-based sensing methods is the real-time determination for in situ monitoring of various compounds in a medium. In this regard, 3 chemiresistors with different functional layers (i.e., graphene/poly (methyl methacrylate), polypyrrole, and polyaniline) have been developed in this research. These sensing layers have been exposed to several analytes of interest (e.g., volatile organic compounds, hydrogen sulfide, ammonia, metal ions, etc.). The experiments and measurements were conducted in a broad range of concentrations (part per billion (ppb) to part per thousand (ppt)). In all experiments, the variation in impedance provides several vital characteristics enabling the detection of the analyte of interest with much more selectively as compared to other conventional resistance-based sensors. For this purpose, the faradaic and non-faradaic responses to each analyte at different concentrations are correlated with an equivalent circuit. One of the novelties of this research is the incorporation of the individual equivalent circuit elements as features in 2D and 3D clustered plots to represent the selectivity of the sensors. Another novelty of this work relates to the use of potentiodynamic electrochemical impedance spectroscopy (PDEIS) for a selective in situ recognition of biological trace elements. PDEIS provides a combination of the information that conventional cyclic voltammetry (CV) and EIS represent for analyzing the sensing platform and the electrochemical reactions occurring at the surface of the electrode and electrolyte. Similar to the tests conducted with single analytes, mixtures of different analytes (hydrogen sulfide and ammonia at ppm- and ppb-levels) were also studied in terms of the effect of their reaction on the sensing platform. The results from the principal component analysis (PCA) for the mixtures of the analytes again confirm the high potential of the sensors and electrochemical analysis techniques (EIS and PDEIS) in selectively detecting the analytes of interest in mixture solutions.
i DEVELOPMENT OF IMPEDANCE-TRANSDUCED CHEMIRESISTORS FOR HIGHLY SELECTIVE ELECTROCHEMICAL DETECTION IN AQUOUES MEDIA By Adel Yavarinasab B.Sc., Iran University of Science and Technology, Iran, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Mechanical Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) August 2020 © Adel Yavarinasab, 2020 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled: DEVELOPMENT OF IMPEDANCE-TRANSDUCED CHEMIRESISTORS FOR HIGHLY SELECTIVE AND SENSITIVE ELECTROCHEMICAL DETECTION IN AQUOUES MEDIA Submitted by Adel Yavarinasab in partial fulfillment of the requirements of the degree of Master of Applied Science . Dr. Mina Hoorfar, School of Engineering Supervisor Dr. Homayoun Najjaran, School of Engineering Supervisory Committee Member Dr. Chen Feng, School of Engineering Supervisory Committee Member Dr. Shahria Alam, School of Engineering University Examiner iii Abstract In this research, the application of electrochemical impedance spectroscopy (EIS) for electrochemical detection of different components in aqueous media (water, KCl solution, and standard electrolyte solutions) is scrutinized. One of the main advantages of electrochemical sensors compared to other electrical- or optical-based sensing methods is the real-time determination for in situ monitoring of various compounds in a medium. In this regard, 3 chemiresistors with different functional layers (i.e., graphene/poly (methyl methacrylate), polypyrrole, and polyaniline) have been developed in this research. These sensing layers have been exposed to several analytes of interest (e.g., volatile organic compounds, hydrogen sulfide, ammonia, metal ions, etc.). The experiments and measurements were conducted in a broad range of concentrations (part per billion (ppb) to part per thousand (ppt)). In all experiments, the variation in impedance provides several vital characteristics enabling the detection of the analyte of interest with much more selectively as compared to other conventional resistance-based sensors. For this purpose, the faradaic and non-faradaic responses to each analyte at different concentrations are correlated with an equivalent circuit. One of the novelties of this research is the incorporation of the individual equivalent circuit elements as features in 2D and 3D clustered plots to represent the selectivity of the sensors. Another novelty of this work relates to the use of potentiodynamic electrochemical impedance spectroscopy (PDEIS) for a selective in situ recognition of biological trace elements. PDEIS provides a combination of the information that conventional cyclic voltammetry (CV) and EIS represent for analyzing the sensing platform and the electrochemical reactions occurring at the surface of the electrode and electrolyte. Similar to the tests conducted with single analytes, mixtures of iv different analytes (hydrogen sulfide and ammonia at ppm- and ppb-levels) were also studied in terms of the effect of their reaction on the sensing platform. The results from the principal component analysis (PCA) for the mixtures of the analytes again confirm the high potential of the sensors and electrochemical analysis techniques (EIS and PDEIS) in selectively detecting the analytes of interest in mixture solutions. v Preface The research presented in this thesis is the original work performed by the author. This thesis was supervised by Dr. Mina Hoorfar at the Advanced Thermo-Fluidic Laboratory (ATFL) in the School of Engineering, University of British Columbia. Parts of this thesis have been published in different journals and presented in conferences. The details of the publications and the author’s contributions in them are explained below: a. Refereed journal publications [1] A. Yavarinasab, S. Janfaza, N. Tasnim, H. Tahmooressi, A. Dalili, M. Hoorfar, Graphene/poly (methyl methacrylate) electrochemical impedance-transduced chemiresistor for detection of volatile organic compounds in aqueous medium, Analytica Chimica Acta, Volume 1109, 2020, Pages 27-36 [2] A. Yavarinasab, H. Tahmooressi, S. Janfaza, N. Tasnim, M. Hoorfar, Potentiodynamic electrochemical impedance spectroscopy of polyaniline and polypyrrole modified pencil graphite electrodes for selective detection of biochemical trace elements (To be submitted in Talanta) [3] A. Yavarinasab, S. Janfaza H. Tahmooressi, M. Ghazi, N. Tasnim, M. Hoorfar, A polypyrrole-based sub-ppm impedimetric sensor for detection of dissolved hydrogen sulfide and ammonia mixture (To be submitted in Sensors and Actuators B: Chemical) [4] A. Yavarinasab, H. Tahmooressi, N. Tasnim, M. Hoorfar, Innovative nanostructured metal oxide gas sensors in the detection of lung cancer on breath (To be submitted in Coordination Chemistry Reviews) b. Conference proceedings and presentations [1] A Yavarinasab, S Janfaza, MM Montazeri, N. Tasnim, AD. Farahani, P. Kadota, P. Markin, A. Dalili, E. Taatizadeh, H. Tahmooressi, M. Hoorfar, A graphene-based chemical sensor for hydrogen sulfide measurement in water, 2019 IEEE Sensors, 2019 vi Table of Contents Abstract .................................................................................................................................................................... iii Preface ....................................................................................................................................................................... v Table of Contents .................................................................................................................................................. vi List of Tables ....................................................................................................................................................... viii List of Figures ......................................................................................................................................................... ix List of Symbols and Abbreviations ................................................................................................................ xii Acknowledgments ............................................................................................................................................. xiii Dedication ............................................................................................................................................................. xiv Chapter 1: Background ............................................................................................................................... 1 1.1 Introduction ........................................................................................................................................................... 1 1.2 Analytes of interest .............................................................................................................................................. 2 1.2.1 Volatile organic compounds ................................................................................................................... 2 1.2.2 hydrogen sulfide ......................................................................................................................................... 3 1.2.3 Heavy metals ................................................................................................................................................ 4 1.3 Detection Methods ............................................................................................................................................... 6 1.3.1 Optical methods .......................................................................................................................................... 6 1.3.2 Spectral methods ........................................................................................................................................ 7 1.3.3 Electrochemical methods ........................................................................................................................ 7 1.4 Sensing Layer ......................................................................................................................................................... 8 1.4.1 Carbonaceous materials .......................................................................................................................... 9 1.4.2 Conductive polymers .............................................................................................................................. 10 1.4.3 MOS sensors ................................................................................................................................................ 11 1.5 Challenges and motivations ........................................................................................................................... 12 1.6 Objectives .............................................................................................................................................................. 13 1.7 Organization of thesis ....................................................................................................................................... 14 Chapter 2: Theory ....................................................................................................................................... 15 Chapter 3: Development of an electrochemical chemiresistor for detection of volatile organic compounds in aqueous medium .................................................................................................... 20 3.1 Experimental Method ....................................................................................................................................... 20 3.1.1 Chemicals and substrate ........................................................................................................................ 20 3.1.2 Sensor fabrication .................................................................................................................................... 20 3.1.3 Nanostructured film ................................................................................................................................ 21 vii 3.1.4 Experimental setup .................................................................................................................................. 21 3.1.5 Electrical measurement ......................................................................................................................... 23 3.2 Results and discussions ................................................................................................................................... 23 3.2.1 Characterization of thin film ................................................................................................................ 23 3.2.2 Electrochemical impedance spectroscopy (EIS) measurements .......................................... 25 3.2.3 Equivalent circuit and feature extraction ....................................................................................... 30 Chapter 4: PDEIS behavior of polyaniline and polypyrrole modified pencil electrodes in presence of heavy metals.................................................................................................................................. 35 4.1 Experimental Method ....................................................................................................................................... 35 4.1.1 Chemicals and substrate ........................................................................................................................ 35 4.1.2 Sensor Fabrication ................................................................................................................................... 35 4.1.3 Experimental Setup and electrical measurements ..................................................................... 36 4.2 Results and discussions ................................................................................................................................... 38 4.2.1 Electrochemical characterization of PAni/ and PPy/ modified PGE ................................... 38 4.2.2 EIS measurements and selectivity ..................................................................................................... 40 4.2.3 EIS characteristics of reduction potential ...................................................................................... 44 4.2.4 Potentiodynamic profiles ...................................................................................................................... 45 Chapter 5: Development of the Ppy-based chemiresistive sensing platform for detection of volatile organic compounds in water and standard electrolyte solution .................................. 50 5.1 Experimental Method ....................................................................................................................................... 50 5.1.1 Chemicals and substrates ...................................................................................................................... 50 5.1.2 Instruments and analysis ...................................................................................................................... 52 5.2 Results and discussion ..................................................................................................................................... 53 5.2.1 Characterization of thin film ................................................................................................................ 53 5.2.2 impedance spectroscopy of hydrogen sulfide .............................................................................. 55 5.2.3 Equivalent circuit...................................................................................................................................... 56 5.2.4 impedance spectroscopy of ammonia .............................................................................................. 59 5.2.5 Prediction Model for mixture of hydrogen sulfide and ammonia ........................................ 61 Chapter 6: Conclusions and future work ............................................................................................ 64 6.1 Summary ................................................................................................................................................................ 64 6.2 Contribution to the filed .................................................................................................................................. 66 6.3 Future work .......................................................................................................................................................... 66 References .............................................................................................................................................................. 68 viii List of Tables Table 3-1 The values of the three-element equivalent circuit for different concentrations of the analytes in a 0.5-M KCl solution ...................................................................................................................................... 34 Table 5-1 Indicators for evaluating the accuracy of the regression model ................................................... 63 ix List of Figures Figure 2.1a) Randles equivalent circuit b) Typical Nyquist diagram for a faradaic probe c) The corresponding Bode plot .................................................................................................................................................... 19 Figure 3.1 The schematic of the experimental procedure: (A) interdigitated electrode and sensing layer deposition, (B) binding PMMA and GN dispersed in THF, (C) dipping the sensor in the solution, and (D) chemical reaction between the analyte and the sensing layer which gives rise to the response. (Reproduced from [90] with permission from Elsevier) ...................................................................................... 22 Figure 3.2 The SEM images of the PMMA-Graphene film at different magnifications of a) 2.5k and b) 10k. (Reproduced from [90] with permission from Elsevier) ............................................................................ 24 Figure 3.3 The effect of the thin film on the impedance behavior of the sensor. The results are presented in the form of a Bode plot (Reproduced from [90] with permission from Elsevier) ........... 25 Figure 3.4 The Nyquist plots of EIS for: ethanol, IPA, acetonitrile, and acetone with the concentration of 0.025 %v/v (equivalent to 19.6 ppt) in 0.5 M KCl. The frequency (𝑓) range is within 100 KHz to 1 Hz (Reproduced from [90] with permission from Elsevier) ............................................................................... 26 Figure 3.5 - Bode plots for acetone (red), ethanol (purple), IPA (green), and acetonitrile (blue) in 0.5 M KCl, with the concentration of 0.0025, 0.0125, 0.0375, and 0.0875 %v/v (equivalent to 1.96, 9.85, 29.5, and 69 ppt); frequency from 100 KHz to 1 Hz (Reproduced from [90] with permission from Elsevier) .................................................................................................................................................................................... 27 Figure 3.6 - Nyquist plots for acetone (red), ethanol (purple), IPA (green), and acetonitrile (blue) in 0.5 M KCl, with the concentration of 0.0025, 0.0125, 0.0375, and 0.0875 %v/v (equivalent to 1.96, 9.85, 29.5, and 69 ppt); frequency from 100 KHz to 1 Hz (Reproduced from [90] with permission from Elsevier) .................................................................................................................................................................................... 28 x Figure 3.7 a) The relative change in the impedance of the thin film exposed to 0.025%v/v (equivalent to 19.7 ppt) of ethanol in 0.5M KCl for 6 repetitions. b) The error bars show the standard deviations of the measurements. (Reproduced from [90] with permission from Elsevier) ........................................ 29 Figure 3.8 The calibration curve for ethanol (𝑅2=0.93), IPA (𝑅2=0.95), acetone (𝑅2=0.98), and acetonitrile (𝑅2=0.98) (Reproduced from [90] with permission from Elsevier) ....................................... 30 Figure 3.9 The Bode plot from the experimental data and the fitted 3-element equivalent circuit for 0.025 %v/v equal to 19.7 ppt ethanol in 0.5 M KCl (Reproduced from [90] with permission from Elsevier) .................................................................................................................................................................................... 31 Figure 3.10 The values of the elements of the equivalent circuit for ethanol, IPA, acetonitrile, and acetone in KCl in a) 3D, and b) 2D plots (Reproduced from [90] with permission from Elsevier) ..... 33 Figure 4.1 Schematic representation of the test setup a) CV of polypyrrole b and c) CV of aniline d) with the three-electrode cell f) deposition of the CP on the surface of the PGE .......................................... 40 Figure 4.2 a) Nyquist spectra of electro-synthesized PPy in the electrolyte at 0.6 V and the values of b) charge transfer resistance, and c) double layer capacitance for the corresponding equivalent circuit .......................................................................................................................................................................................... 42 Figure 4.3 - The Nyquist spectra of electro-synthesized PAni in the electrolyte at a) 0.8 V, b) 0.9 V, and c) 1.0 V. The values of d) resistance of solution, e) charge transfer resistance and f) double layer capacitance for the corresponding equivalent circuit ............................................................................................ 44 Figure 4.4 Nyquist spectra of electro-synthesized i) PPy and ii) PAni for the analytes of (a) Cr (III), (b) Cu (II), and (c) Fe (III) at their corresponding reduction potential. The values of (iii) charge transfer resistance, and d(iv)) double layer capacitance...................................................................................... 45 xi Figure 4.5 PDEIS spectra of electrosynthesized PPy within the potentials of -0.2 V to 1.0 V for a) Cr (III), b) Cu (II), and c)Fe (III) and the values of (1) impedance and (2) double layer capacitance as a function of potential ............................................................................................................................................................. 47 Figure 4.6 PDEIS spectra of electrosynthesized PAni within the potentials of -0.2 V to 1.0 V for a) Cr (III), b) Cu (II), and c)Fe (III) and the values of (1) impedance and (2) double layer capacitance as a function of potential ............................................................................................................................................................. 49 Figure 5.1 Schematics of the impedance-transduced chemiresistor. (A) Deposition of PPy on the surface of the interdigitated electrode. (B) Dipping the chemiresistor in the electrolyte. (C) Exposure of the PPy film to the targets ............................................................................................................................................. 54 Figure 5.2 (A) CV of the electropolymerization of PPy. (B) The effect of the PPy film on the impedance behaviour of the chemiresistor: the inset figure shows the Nyquist spectra of the corresponding Bode plot. .............................................................................................................................................................................................. 54 Figure 5.3 A) Impedance spectra of the chemiresistor exposed to different concentrations of H2S, and (B) the impedance as a function of H2S concentration, presenting a calibration curve ........................... 56 Figure 5.4 (A) The Bode, (B) phase angle, and (C) Nyquist plot of the PPy thin film to 5 ppm H2S and (inset) the corresponding equivalent circuit ............................................................................................................. 58 Figure 5.5 (A) Impedance spectra of the chemiresistor for NH3 and (B) The calibration curve of the sensor to NH3 (C) Radar diagram of normalized values of the equivalent circuit for H2S and NH3 ..... 61 Figure 5.6 A-D) Impedance spectra of the chemiresistor for the mixture of H2S and NH3 at different concentration ratios [NH3: H2S ppm] E) Some predicted responses of the sensor F) Comparison of the predicted response of the sensor and experiment result for a specific mixture of 5 ppm of each H2S and NH3 ...................................................................................................................................................................................... 63 xii List of Symbols and Abbreviations C concentration ω angular frequency Cdl double-layer capacitance Abbreviation Cg geometric capacitance of the cell 2-D two-dimensional CS surface concentration 3-D two-dimensional f frequency CP conducting polymer I current CPE constant-phase element i imaginary unit CV cyclic voltammetry I0 magnitude of oscillating current DI deionized Kp equilibrium constant EIS electrochemical impedance spectroscopy P CPE parameter FEG field emission gun R gas constant GN graphene R2 coefficient of determination HPLC high-pressure liquid chromatography Rct charge-transfer resistance IL ionic liquid Re resistance of the external circuit IPA isopropyl alcohol Rf/Rcp film resistance MOS metal oxide semiconductor Rs solution resistance PAni polyaniline t time PCA principal component analysis T CPE parameter / Temperature PDEIS Potentiodynamic EIS V voltage / potential PGE pencil graphite electrodes V0 magnitude of oscillating voltage PMMA poly(methyl methacrylate) Z impedance ppb part per billion Z’ real part of impedance ppm part per million Z’’ imaginary part of impedance ppt part per thousand ZW Warburg impedance PPy polypyrrole Greek symbols RSD relative standard deviation α surface coverage of metal adatoms SD standard deviation ΔH enthalpy variation SEM scanning electron microscopy ΔS entropy variation SSE sum of squared errors θ phase degree THF tetrahydrofuran φi phase of the complex current VOC volatile organic compound φv phase of the complex voltage xiii Acknowledgments Firstly, I would like to express the deepest gratitude to my supervisor Dr. Mina Hoorfar, who kindly offers me the opportunity to undertake the Master project in her group. Undoubtedly, none of the achievements occurred without her constant guidance and thoughtful encouragement throughout the research. I am also extremely grateful to Sajjad Janfaza and Mostafa Abedini, who devoted a great deal of their time and helped me a lot throughout the project. My appreciation also extends to my dearest friends, Hamed Tahmooressi and Romina Amirsardari who lend me a giant shoulder in difficult times. xiv Dedication For my beloved family for all their support and sacrifices to make all these achievements possible… I love you1 1 Chapter 1: Background1 1.1 Introduction In a laboratory environment, it is a crying need to detect the components of different compounds for multifarious applications such as environment (e.g. pollutants), health care (e.g. biomarkers), etc. Sensors are devices used to detect a specific chemical and generate a signal while being exposed. The chemical constituent which is of interest in the analytical procedure (sensing) is sometimes called target or analyte (of interest). There have been a sublime number of investigations throughout the 20th and 21st centuries regarding the detection of specific analytes in the gas phase (e.g. breath). However, the differentiation of the target in the liquid phase is as important as gas media. Biological fluids (e.g. blood, urine, etc.), food industry (e.g. milk, beverage, etc,), and environmental fluids (e.g. water) are some areas which require the detection of different components in their samples for their corresponding purposes. In this thesis, first, I have introduced 3 major analytes, which all the studies have been conducted in them. Then, different techniques for detection in the liquid phase is briefly introduced, followed by a deep study on electrochemical sensors, and more specifically, chemiresistors. Finally, the challenges, objectives, and organization of the thesis are represented. 1 Parts of this chapter have been published as a full paper in Analytica Chimica Acta, and submitted in Sensors and Actuators B: Chemical, Talanta, and Coordination Chemistry Reviews 2 1.2 Analytes of interest 1.2.1 Volatile organic compounds Volatile organic compounds (VOCs) are organic chemicals released from various sources, ranging from environmental [1,2] to metabolic [3], with high pressure and volatility which causes them to evaporate at room temperature. Most VOCs (e.g., acrylonitrile, benzene, chloroform, etc.) are classified as toxic or hazardous pollutants in gas and/or liquid media. The existence of VOCs in the environment can be potentially carcinogenic and a risk factor for health issues like neurological and autoimmune diseases [4]. VOCs can also be used as a diagnostic tool for early detection of chronic diseases such cancer (pulmonary [5], ductal [6], colon [7], and prostate [8]), as cancerous cells produce VOCs due to the membrane peroxidation and metabolic changes of cells [9]. Most of the studies in the area of VOC sensing are conducted in the gas/vapor phase because VOCs are mostly recognized by their high volatility and low water solubility[10]. However, polar VOCs (e.g. methanol, ethanol, and propanol) are soluble in water at various degrees [11] (and some, like benzene and toluene, can potentially be considered as public health threat [12]). Dissolved VOCs can also be observed in human body fluids such as in blood [13], urine [14], and saliva [15] (it has been reported that more than 150 and 360 different types of VOCs are detected in blood and saliva, respectively, with acetonitrile and alcohols being major components [16]). In this regard, detection of VOCs at different aqueous media is a significant unmet need. However, to date, there have been only a few quantitative analyses conducted on the sensing of VOCs in electrolyte solutions compared to gas media. Raguse et. al [17] were the pioneers in the development of a sensor capable of detection of analytes in a liquid phase (they detected 3 dichloromethane and ethanol dissolved in a KCl aqueous solution). However, the reported analytes were significantly different in terms of structure, size, etc. A few studies have also been conducted regarding the detection of larger analytes like hexane [18], toluene [19], octane [20], and benzene [21] in liquid solutions. 1.2.2 hydrogen sulfide As early as 18th century, hydrogen sulfide (H2S ) has been discovered as one of the most versatile molecules with potential irritation to ocular and pulmonary systems [22]. H2S is a colourless, highly flammable dense gas, with a pungent smell. It has the most reduced oxidation state of sulfur (-2) with the possible reaction of 𝐻2𝑆 ↔ 𝐻𝑆− + 𝐻+ ↔ 𝑆2− + 𝐻+. It has a long-standing detrimental reputation, as it is the inhibitor of cytochrome c oxidase within mitochondria, which are responsible for Adenosine triphosphate (ATP) generation [23]. During this process, the consumption of oxygen and consequently cellular respiration are halted, leading to the deterioration of cardiac and nervous systems which have high demands for O2. H2S is also involved in numerous toxicological effects on DNA [24], protein kinase [25], cellular division [26], cytoskeletal organization [27], etc. Aside from its cytotoxic effects at high concentrations, H2S is associated with several biological benefits. It is one of the three gasotransmitters (sharing with NO and CO) synthesized in the brain which plays a pathophysiological role as the endogenous signalling messenger in the body [28]. The endogenous H2S in humans is due to the side reaction of certain enzymes with dietary cysteine in nervous and cardiovascular system as well as the liver [29]. Cytoprotective effect against DNA [30], limitations of atherogenesis [31], protein modification [32], radical scavenging [33], vasodilation (muscle relaxation) [34], to name a few, are some of the 4 positive biological effects of H2S in the body. H2S is also extremely toxic to the environment. Generated by chemical industries (like tanneries [35], petroleum refineries [36], and paper mills [37]) or by-product of biological activities (volcanic gases [38] or bacterial decomposition [39]), H2S catalyzed by metal or metal oxides is one of the foremost reason for severe photochemical smog and acid rain [40]. It is corrosive for sewage treatment facilities released during sludge pyrolysis [41] and highly toxic for marine life [42]. In a recent comprehensive review, H2S has been named as one of the most potent molecules in life’s origin [43]. The critical role of H2S in ecology and immunology has prompted the researchers to accurately detect it for further understanding of this pervasive molecule and its possible pharmacological and physiological roles. 1.2.3 Heavy metals The presence of certain metal ions is an unmet need to drive biological processes in human body: any imbalances in that regard can cause serious disorders and malfunctions for living tissues. Among the metal cations, Cu (II), Cr (III), and Fe (III) receive significant attentions due to their role in different metabolisms. Ferric iron, the oxidized state (Fe (III)), is the second most abundant transition metal ion in human and one of the critical sources at the active site for catalytic synthesis of substances [44–46]. Iron ions have different metabolic functions and biological activities such as heme synthesis (formation of haemoglobin)[47], electron and oxygen transport [48], DNA repair and synthesis (iron–sulfur (Fe–S) clusters) [49], free-radical detoxification [50], etc. The recommended intakes of Fe (III) for normal adults is in the range of and 8–18 mg day−1 [51]. Due to its redox-cycle, regulation of this amount is highly required as iron deficiency (hypoferremia) or over exposure 5 (hyperferremia) results in erythroid disorders (e.g. anemia [52], hemochromatosis [53],) metastasis and cancer [54], in addition to many more dysfunctions of physiological systems. Copper ion is the third most abundant essential elements for living organism, which plays as an enzyme catalytic cofactor for superoxide dismutase[55], cytochrome c oxidase [56], and tyrosinase [57]. Disturbance of copper homeostasis leads to a wide variety of disorders. Copper deficiency can attribute to incomplete development and neurological issues, like Alzheimer’s [58] and Menkes diseases [59], as it highly affects amyloid plaques in brain tissue. On the other hand, hyperaccumulation of copper ions can seriously damage hepatic and neurological tissues [60]. Aceruloplasminemia, amyotrophic lateral sclerosis, Huntington disease, and Parkinson disease are some other disorders, highly associated with copper homeostasis [61]. Chromium is another trace element in body, which is not widely investigated compared to iron and copper. However, its role in fat and carbohydrate breakdown [62], cholesterol [63], and bone growth [64] is very well-known. Apart from the metabolic role of heavy metal ions, one other aspect is that they are usually produced by anthropogenic activities and categorized as pollutants in the environment [65]. What makes it worse is non-biodegradability of metal ions, which makes them to accumulate in living organisms and cause harmful disorders [66]. The important role of metal ions in body and environment necessitates the development of highly sensitive and selective techniques for trace level detection of the ions in different biological and environmental samples. 6 1.3 Detection Methods Different detection methods have been evolved to determine the concentration of the components in different samples. In a very general category, detection techniques can be divided into 3 major groups, namely, optical, spectral, and electrochemical sensors. Assuredly, each method has its advantages and limitations. 1.3.1 Optical methods The principle of optical sensors is the change of optical properties of the target due to the emission of electromagnetic waves [67]. In surfaced-based techniques, e.g. localized surface plasmon resonance [68] and surface/tip-enhanced Raman scattering [69], the collection of molecular vibrations gives rise to the variation of wavelength or frequency of incident light, leading to point-of-care detection of the component in the sample. In colorimetric arrays, upon exposure to volatile species, redox reactions as well as Brønsted and Lewis acidity/basicity [70] change the color of the probe in a nonreversible way, indicating a disposable device [71]. For example, for H2S detection, methylene-blue assays are used to react the target with N, N-dimethyl-p-phenylenediamine sulfate to absorb the light [72]. Long incubation time (>30min), very low sensitivity (<1μM), and lack of specificity are the major hindrance of this method to detect and quantify H2S [73]. In fluorescent probes, the fluorescent sulfide-dibimane is usually achieved with the reaction of H2S with monobromobimane molecules, and high-pressure liquid chromatography (HPLC) is finally exerted [74]. Lack of the ability of real-time quantification, costly equipment, and formation of tissue autofluorescence make them impractical to monitor H2S fluctuations [75]. Optical spectroscopic approaches have also been extensively developed for trace detection of heavy 7 metals; e.g. surface-enhanced Raman spectroscopy [76], and colorimetry [77]. Besides, optical techniques require relatively costly and bulky equipment, which are not appropriate for daily usage with several times. Also, challenging procedure of the polarization of the near-field light, low reproducibility, lack of sensitivity, and long incubation time are some hindrances for their application in real-time diagnosis [78]. 1.3.2 Spectral methods Inductively coupled plasma [79] coupled with various preparations (i.e. mass spectroscopy [80], optical emission spectrometry [81], atomic emission spectrometry [82]), atomic absorption spectroscopy [83], neutron activation analysis, flameless atomic absorption spectrophotometry [84], X-ray fluorescence spectrometry [85] and laser induced breakdown spectroscopy [86] are some of the highly-mature spectral techniques for ppm- and ppb-level detection of trace elements in complicated matrices. However, long incubation time, bulky and costly equipment, multiple sample preparation, and requiring chromatographic methods for target speciation are some bottlenecks for real-time monitoring [87]. There are also some mass-based sensors like surface acoustic waves [88] and quartz crystal microbalance [89], which are based on the oscillation and shifting of the frequency, respectively. Due to the lack of sensitivity, specificity, and excessive interference, these methods are not commonly investigated. 1.3.3 Electrochemical methods The mechanism of the electrochemical sensor is based on the reaction of the functional layer when exposed to the target [90]. During the chemical reaction, the electrical properties of the sensing layer change when transporting electric charges through the electrodes, leading 8 to detect the analyte of interest [91]. Depending on the method and the applied voltage, DC or AC, the change occurs in potential [92] (potentiometry), current [93] (amperometry), resistance [94], and impedance [95] (chemiresistor), and conductance [96] (conductometry). The chemiresistor response is based on a change in the electrical resistance/impedance due to the resonant quantum tunneling of the sensing material while exposed to the analyte of interest [97]. They are comprised of two parts — a conductive thin-film functional layer and a pair of electrodes that sandwich the functional layer. The characteristics of the chemiresistor are highly associated with the properties of the functional layer. This layer acts as a bridge between two electrodes and is responsible for transporting electric charges through the electrodes [91]. 1.4 Sensing Layer The important role of the sensing layer is undeniable in electrochemical sensors as the reaction between the sensing layer and the analyte of interest is the concept of chemiresistors. A spectrum of conducting materials plays as the sensing material to determine the targets, which can be mainly divided into carbonaceous materials, conducting polymers (CPs), metal oxide semiconductors (MOSs), and their corresponding composites. Among them, nanocomposites (i.e., a combination of a conductive nanomaterial and polymer matrix) have demonstrated superior properties due to their structural and electrical characteristics. In this section, a short literature of each sensing material is explored. 9 1.4.1 Carbonaceous materials Nanostructured carbon materials such as graphene oxide [98], reduced graphene oxide [99], single-wall carbon nanotube [100], multi-walled carbon nanotubes [101] and fullerene [102], are highly conductive, and hence facilitate detection of different analytes in aqueous solutions. Graphene (GN) consists of a two-dimensional (2-D) monolayer of carbon atoms arranged hexagonally and bonded in the form of a plane of sp2-bonded atoms [103]. To date, there has been little agreement on which allotrope of carbon is better for sensing [104]; however, GN with its higher surface area (calculated as 2630 m2 g-1), lack of metallic catalyst impurities, as well as high affinity to different chemical species, has the highest potential to be used in sensing industry to detect VOCs with high sensitivity [105]. The high specific surface area of GN provides a large contact area between GN and the supporting polymer matrix [106]. In fact, GN can outperform similar materials such as CNT. CNT tends to agglomerate during fabrication, resulting in the limited dispersion of nanofillers, and provide weaker reinforcement to the polymer matrix [107]. The combination of GN and polymers can be used for the development of lightweight and electrically conductive materials that are capable of transporting electrons between two electrodes. Carbonaceous materials are of much interest to be mixed with the polymers and play as a conductive nanofiller in the polymer matrix. Due to their high conductivity, eco-friendliness, and electrochemical stability, they are significantly used in electrode materials for electrical double-layer supercapacitors [108]. In this regard, in the recent past, many carbonaceous materials including graphite [109] and pyrolytic graphite [110], carbon nanotube [111], glassy carbon [112], carbon fiber electrode [113], graphene [114], boron-doped diamond 10 [115] etc. are so many targeted for sensing multifarious analytes in gas and aqueous media. Among which, the most stable form of carbon, pencil graphite electrodes (PGE) is of particular interest due to its low cost, omnipresence, commercialization, stability, and analytical reproducibility in comparison to those of its expensive family [116]. Renewability of the PGE is another significant aspect, leading to being considered as the working electrode rather than the ones requiring surface polishing procedures [117]. The configuration of the carbons in graphite is all sp2 hybridized which is responsible to its high conductivity, and more importantly, facilitates the adsorption of the analyte to the electrode, while for example in diamond, since the carbon atoms are all sp3 hybridized, it has low conductivity [118]. In addition, in contrast to commonly used glassy carbon electrode which is disposable and expensive, PGE is able to provide reproducible voltammetric peaks and fast rate of electron-transfer for usual Fe(CN)63−/4− and Ru(NH3)63+/2+ redox systems [119]. 1.4.2 Conductive polymers The past twenty years have seen increasingly rapid advances in the field of conductive polymers in many research areas. They have the mixed properties of metals, e.g. electrical charge transfer, and regular polymers like the ease of synthesis, and high strength. The structure of CPs includes a conjugated backbone with alternating single and double comprise π-bonds in which unpaired electrons can move freely [120]. This characteristic results in CPs’ vast application in fouling prevention of the membrane surfaces in water and wastewater industry [121], in the aerospace industry for aircraft structures manufacturing, especially during the lightning strike [122], in energy storage systems like lithium-ion batteries and supercapacitors [123], in fuel cell bipolar plates [124,125], and more than all, 11 in “smart” biomedical applications [126–128]. Among more than 25 CPs, polypyrrole (PPy) and polyaniline (PAni) are the most investigated polymers, based on the huge amount of publication regarding their synthesis, properties, and applications [129], which lead to a Nobel Prize in Chemistry in 2000 for Alan MacDiarmid [130]. Due to their extended π-conjugated backbone structure, the electrical conductivity of PPy and PAni reaches 102 and 103 S.cm−1, respectively, and because of their hetero-aromatic structures, both are favorite candidates for aforementioned industries [131,132]. Utilization of conductive and semi-conductive polymers can be also a good candidate for electrochemical H2S sensing in liquid. Although polyaniline has been traditionally used for H2S detection [133], recently some other CPs like poly(3,4-ethylene dioxythiophene) [134], polyvinyl alcohol [135], poly(methyl methacrylate) (PMMA) [136], polypyrrole [137], and chitosan [138] are being synthesized to in situ determination of H2S. Among which, due to its structure, polypyrrole was proven to have an irregular response to H2S and was not investigated for H2S detection as other polymers [139]. 1.4.3 MOS sensors The sensing layer includes crystalline grains that are loosely connected by necks. These crystal structures form larger aggregates connected to another aggregate by grain boundaries. On the surface of the grains, oxygen is adsorbed and removes electrons from the near-surface region, making a region where no charge carrier exists (depletion or space-charge layer). Once the sensor is heated, free electrons go back and forth through the grain boundaries, and a potential barrier occurs at the surface of the metal oxide. Once the analyte is introduced to the sensing layer, variation in the surrounding atmosphere of the MOS 12 sensor, and consequently the reactions between ionosorbed surface oxygen (𝑂2, 𝑂−, 𝑂2−, O2−) and the exhaled breath analyte, changes the conductivity of the sensing layer with a reaction (𝑂2(𝑔) + 𝑛𝑒− ↔ 𝑂𝑥(𝑎𝑑)𝑛− + ℎ𝑜𝑙𝑒𝑛+) and the reaction on the surface of the sensing layer is transmitted to a readout electrical signal. For example, upon the exposure of H2S to MOS sensors, the target reacts with the chemisorbed oxygen on the surface of the electrode, releasing electrons back to the sensing layer. This decrement of the width of depletion and accumulation layers change the resistance of the sensor and facilitate H2S sensing, i.e. 𝐻2𝑆 +3𝑂− → 𝑆𝑂2 + 3𝑒− or 𝐻2𝑆 + 3𝑂2− → 𝑆𝑂2 + 6𝑒− [140]. CuO [141], SnO2 [142], ZnO [143], Fe2O3 [144], WO3 [145], In2O3 [146], and binary [147] and ternary oxides [148] are ubiquitous oxides to readily react with H2S. 1.5 Challenges and motivations One hurdle in electrochemical sensors is their poor stability while exposed to the sample in the liquid phase as the current can wash away the sensing layer. Generally, materials with higher crystallinity show a more robust response than those of amorphous or polycrystalline characteristics. One approach is loading a non-conductive polymer to stabilize the sensing layer and provide robust results. This technique is widely discussed in Chapter 3. One other disadvantageous of electrochemical sensors, particularly in the gas phase, is the requirement for high temperatures to evaporate the aqueous media. This issue can be overcome by direct sensing in the liquid phase. Also, although electrochemical sensors have been investigated to selectively and sensitively detect the components in the media for a long time, their capability to simultaneously sense the analytes in the mixture is yet to be explored. 13 1.6 Objectives The core purpose of this thesis is a detailed study on the functionality of electrochemical sensors with the following features: 1) step-by-step fabrication of 3 different sensors (GN/PMMA on gold electrodes, polypyrrole and polyaniline on graphite pencil electrodes, and polypyrrole on gold electrodes) 2) sample preparation (standard electrolyte) 3) measuring the impedance of the target as well as other similar components at different concentrations 4) analyzing EIS data 5) investigating on the functionality and performance of the impedance-transduced chemiresistor for in situ detection of the target One objective of this thesis is to introduce the equivalent circuit for further analysis of the chemical and physical reactions at the interface between the sensing layer and target. The equivalent circuit has also been used as a promising feature for selectivity, as each analyte has unique electrochemical characteristics. Another aspect of this thesis is using PDEIS as a complementary tool for traditional EIS and cyclic voltammetry measurements. PDEIS technique is widely used for overoxidation in electrochemistry, but it shows as a promising tool to be studied for analyzing the selectivity of electrochemical sensors as each functional layer show different PDEIS behavior while exposed to the analyte of interest. Finally, the capability of the electrochemical sensors to simultaneously detect the analytes (NH3 and H2S) in a mixture is studies using principal component analysis. 14 1.7 Organization of thesis In this thesis, the theory of electrochemistry is first summarized (Chapter 2), along with the introduction of PDEIS and the equivalent circuit. Next, an impedance-transduced sensor is developed based on nanostructured graphene and PMMA sensing film for the detection of individual VOCs in aqueous media (Chapter 3). In Chapter 4, the potential of PDEIS is analyzed for a selective in situ recognition of biological trace elements in the human body, i.e. Cr (III), Cu (II), and Fe (III). In both sections, the impedance behaviors of the sensing layers are recorded through electrochemical impedance spectroscopy (EIS) and scrutinized by means of an appropriate equivalent circuit. In Chapter 5, a polypyrrole-based impedimetric sensor is represented to simultaneously detect the cocktail of hydrogen sulfide and ammonia in aqueous media. Finally, the achievements of the thesis, as well as potential future works, are summarized in Chapter 6. 15 2 Chapter 2: Theory2 The standard technique in EIS is exciting the system by applying a sinusoidal perturbation (either voltage or current) and the response, which is current or voltage respectively, is measured. The sinusoidal excitations are conventionally represented in the polar form as: 𝑉(𝑡) = 𝑉0𝑒−𝑖𝜔𝑡−𝜑𝑣 (1) 𝐼(𝑡) = 𝐼0𝑒−𝑖𝜔𝑡−𝜑𝑖 (2) In which ω is the angular frequency and V0 and I0 are the magnitudes of the oscillating signals [149]. Using Euler's formula and following Ohm’s law, impedance (Z) is calculated as: cos(𝜔𝑡 + 𝜑) =12(𝑒𝑖(𝑤𝑡+𝜑 + 𝑒−𝑖(𝑤𝑡+𝜑) (3) 𝑍 =𝑉(𝑡)𝐼(𝑡)=𝑉0𝐼0𝑒𝑖(𝜑𝑣−𝜑𝑖) (4) 𝜃=𝜑𝑣−𝜑𝑖→ 𝑍 =𝑉0𝐼0𝑒𝑖𝜃 = 𝑍0𝑒𝑖𝜃 (5) Here, the phase of the impedance can be considered as the phase shift which lags the voltage by the applied current. Due to the imaginary unit, i, for convenience, it is regular to show any complex number, including impedance, as a pair of numbers in the complex plane as: 2 Parts of this chapter have been published as a full paper in Analytica Chimica Acta, and submitted in Sensors and Actuators B : Chemical and Talanta 16 𝑍 = 𝑍′ + 𝑖𝑍" (6) where Z’ and Z” are the real and imaginary parts, known as resistance and reactance, respectively, and can be calculated as: 𝑍′ = 𝑅𝑒 +𝑅𝑓1 + 4𝐶𝑔𝐶𝑑𝑙+ 4(𝐶𝑔𝐶𝑑𝑙)2 + (𝜔𝑅𝑓𝐶𝑔)2 (7) 𝑍" = 𝑅𝑓𝜔𝑅𝑓𝐶𝑔 +2𝐶𝑔𝐶𝑑𝑙+ 4(𝐶𝑔𝐶𝑑𝑙)2𝜔𝑅𝑓𝐶𝑔1 + 4𝐶𝑔𝐶𝑑𝑙+ 4(𝐶𝑔𝐶𝑑𝑙)2 + (𝜔𝑅𝑓𝐶𝑔)2 (8) Thus, the magnitude of the impedance is defined as: |Z| = √𝑍′2 + 𝑍′′2 (9) It should be noted that in electrochemical control studies, systems are considered linear, i.e. impedance are derived from constant voltage or current inputs or from Laplace-transformed dynamic equations; therefore, admittance is defined as the inverse of impedance. In other words, the current response to a sinusoidal voltage is a sinusoid at the same frequency and shifted in phase. In order to interpret the data collecting from EIS, an equivalent circuit is commonly utilized to predict the physical, chemical, and biological phenomena occurring in the system. For faradaic probe, in the presence of a redox pair, the most well-known equivalent circuit is called Randles equivalent circuit, presented in Figure 2.1 a. It contains the resistance of the solution (Rs) related to the bulk properties of electrolyte, Warburg impedance (ZW) for the diffusion of redox, the double-layer capacitance (Cdl), and the charge-17 transfer resistance (Rct), related to the surface properties of the interface between the electrode and the solution. Nyquist and bode plots are two usual graphical representatives of EIS. In the Bode plot, the function of impedance and phase angle vs frequency, the magnitude of impedance |Z| goes to Rs and Rct at very high and low frequencies, respectively. At medium frequencies, however, impedance is calculated with the following equation: |𝑍|2 = 𝑅𝑠2 +2𝑅𝑆𝑅𝑐𝑡𝜔2𝑅𝑐𝑡2 𝐶𝑑𝑙2 + 1+𝑅𝑐𝑡2𝜔2𝑅𝑐𝑡2 𝐶𝑑𝑙2 + 1 (10) In this case, as 𝑅𝑠 + 𝑅𝑐𝑡 > 𝑍 > 𝑅𝑠 with the assumption of 𝑅𝐶𝑇2 ≫ 𝑅𝑠2, the above equation can be simplified as: |𝑍|2 =𝑅𝑐𝑡2𝜔2𝑅𝑐𝑡2 𝐶𝑑𝑙2 + 1 (11) In typical electrochemical measurements, where 𝑅𝑐𝑡2 ≫ |𝑍|2, the denominator of Equation (11) is rationalized as 𝜔2𝑅𝑐𝑡2 𝐶𝑑𝑙2 + 1 ≈ 𝜔2𝑅𝑐𝑡2 𝐶𝑑𝑙2 , and the impedance as middle-range frequencies is: |𝑍| =1𝜔𝐶𝑑𝑙 (12) The high concentration of the analyte allows the ions to move through the electrode interface. In the equivalent circuit, this fact can be attributed to the double-layer capacitance in parallel to the film resistance (𝑅𝑓). The use of the double-layer capacitance in the equivalent circuit of aqueous media is a common practice, e.g., [17,150]; however, there is a discrepancy between the real and imaginary part of the impedance at very low frequencies based on Equation (7) and (8) − 𝑍’ = 𝑂(𝜔0) while 𝑍” = 𝑂(𝜔−1). Also, the electrical double 18 layer at the interface of the electrode and the electrolyte never acts as a pure capacitor due to frequency dispersion and the interfacial heterogeneity of the thin film [151], which can result in the weak interpretation of data. Hence, the impedance form of the double-layer capacitor is commonly replaced by a constant phase element (CPE). 𝑍 = 𝑅𝑒 + [(𝑅𝑓 + 𝑍𝐶𝑃𝐸)−1+ (𝑖𝜔𝐶𝑔)−1] (13) In the above equation, 𝑍𝐶𝑃𝐸 is represented in a polar form. Also, the phase angle (𝜃) is independent of the angular velocity (𝜔) and hence referred to as CPE. The corresponding Nyquist plot, the real and imaginary parts of impedance, for a typical Randles circuit is shown in Figure 2.1 b and c. At very high and very low frequencies, Randles circuit acts like a resistor, and the phase angle is close to zero, but at medium frequencies, by the increment of the imaginary part of the impedance, phase angle increases. The half circle of the Nyquist plot has a peak at ωθ=max, showing the maximum phase shift. At this point, the double-layer capacitance can be derived as: 𝜔(𝜃=max) =1𝑅𝑐𝑡𝐶𝑑𝑙 (14) In Figure 2.1 b, σ is the Warburg coefficient, which is affected by the properties of the redox couple, and the area of the electrode. In faradaic impedance, charge transfer is usually considered as the most important factor for the transfer of an electron from one the electrode to the electrolyte [152]. Potentiodynamic EIS (PDEIS) correlates the AC and DC perturbation by the analysis of the typical AC responses (Impedance and double layer capacitance) as a function of potential. 19 The typical investigation is the transition from underpotential to overpotential deposition of the trace elements on the surface of the PGE. The general form of perturbation of the electrode potential in PDEIS is represented as: ∆𝑖 = (𝜕𝐼𝜕𝑉)∆𝑉 + (𝜕𝐼𝜕𝐶𝑠) ∆𝐶𝑠 + (𝜕𝐼𝜕𝛼)∆𝛼 (15) Where CS and α are the surface concentration of the metal cation and surface coverage of metal adatoms, generating by the deposition. While the first term is usually modeled by Rct as it corresponds to the active impedance component, the second term is in direct correlation with diffusion so as Warburg impedance due to the variation of local concentration at different frequencies. Finally, the last term is highly dependent on the reversibility of the electrochemical system. Of note, non-linearity in PDEIS occurs only at high perturbation amplitudes, so those terms are omitted in Equation (15). Figure 2.1a) Randles equivalent circuit b) Typical Nyquist diagram for a faradaic probe c) The corresponding Bode plot 20 3 Chapter 3: Development of an electrochemical chemiresistor for detection of volatile organic compounds in aqueous medium3 3.1 Experimental Method 3.1.1 Chemicals and substrate Glass microscope slides were supplied by VWR VistaVision™, Edmonton, Alberta. GN nanopowder was offered by Graphene Supermarket. PMMA, tetrahydrofuran (THF), ethanol, methanol, acetone, acetonitrile, and potassium chloride (KCl) were purchased from Sigma-Aldrich, Missouri, United States. Isopropyl alcohol (IPA) was prepared from VWR International, Pennsylvania, United States. All other chemicals and reagent were analytical grade and used without any purification or further treatment. The deionized (DI) water was used for all solutions. 3.1.2 Sensor fabrication The sensor was microfabricated on glass microscope slide substrates. First, the glass was first precleaned using an airgun, then polished and washed in an ultrasonic bath (Branson 3510 Ultrasonic Cleaner) containing a blend of dish soap and tap water. The precleaned slides were then cleaned again with acetone, IPA, and water in a cleanroom facility. Next, the slides were dehydrated on a hotplate at 150C for 20 min. A layer of Cr and Au with a thickness of 25 nm and 75 nm, respectively, was then deposited on the substrate using a 3 Parts of this chapter have been published as a full paper in Analytica Chimica Acta, 21 sputtering system (Angstrom, CA). Then, a positive photoresist (S3000 series) was spin-coated and subsequently heated at 115C for 1 min for the soft baking of the deposited metal layers. After a 9-sec exposure period, the redundant Cr/Au was etched out, forming the interdigitated electrodes as a transducer unit, by applying MF-319 (MicroChem, USA) as the photoresist developer, gold-etchant, chromium-etchant and photoresist remover 1165 (MicroChem, USA). Finally, the chip was rinsed with DI water to remove any residuals/contaminants. The area of the electrode is fabricated so small to minimize the formation of capacitance, and consequently high impedance at low frequencies. 3.1.3 Nanostructured film The functional layer of the sensor containing PMMA and GN with different ratios was prepared by sonicating (using Branson 3510 Ultrasonic Cleaner) stock solutions of GN (7.5 mg/ml) and PMMA (3.6 mg/ml), prepared in THF, for 15 min and mixing for 30 min using a vortex mixer (Maxi Mix II, Fisher Scientific). Next, the suspensions were mixed to make nanocomposites with different mass ratios of PMMA/GN (10, 5, 2.5, 0.1, 0.05, 0.025). The resulting suspensions were again placed in an ultrasonic bath for 15 min and mixed for 10 min. Finally, the resulting PMMA/GN suspension was deposited on the glass substrate and allowed to dry on a hotplate at 80C overnight. The surface morphologies of PMMA-GN nanocomposite were investigated with scanning electron microscopy (SEM) equipped with a field emission gun (FEG) for high-resolution imaging. 3.1.4 Experimental setup The sensing platform is schematically shown in Figure 3.1. The experimental sampling and measuring container consisted of a container with a 3D-printed lid to prevent evaporation 22 of the dissolved analyte as VOCs are prone to high temporal and diurnal variation. The solution of 0.5M potassium chloride (KCl) was used to investigate the effect of the electrolytes on the sensing layer, that there is no redox pair due to the lack of electron charge transfer. The impedance spectra of the sensor were recorded after 8 min exposure of the sensor to five different concentrations (0.0025, 0.0125, 0.025, 0.0375, and 0.0875 %v/v equivalent to 1.96, 9.85, 19.7, 29.5, and 69 ppt) of the four VOCs —ethanol, isopropanol, acetone, and acetonitrile. After every single measurement, the sensor was removed from the solution and placed in DI water to recover. Figure 3.1 The schematic of the experimental procedure: (A) interdigitated electrode and sensing layer deposition, (B) binding PMMA and GN dispersed in THF, (C) dipping the sensor in the solution, and (D) chemical reaction between the analyte and the sensing layer which gives rise to the response. (Reproduced from [90] with permission from Elsevier) 23 3.1.5 Electrical measurement The electrochemical impedance spectroscopy (EIS) measurements were performed by applying a sine-wave of 100 mV in a frequency range of 100 KHz to 1 Hz with 50 step/dec. The measurements were performed at room temperature in the solution of 40 ml KCl (0.5M). A VersaSTAT 4 instrument (Princeton Applied Research) interfaced with VersaStudio 2.54.2 software was used for data collection. Data analysis was performed with the ZPlot 2.4 software, and the complex plane impedance spectra were viewed with ZView. The interdigitated electrodes comprised of two-terminal configurations with finger arrays. Each test was repeated at least 3 times and all measurements were made under the same room temperature and laboratory conditions. 3.2 Results and discussions 3.2.1 Characterization of thin film The SEM images (taken at different magnifications of 2.5 and 10k) of the PMMA-GN composite film are shown in Figure 3.2. They revealed a fairly uniform dispersion of GN throughout the PMMA matrix, indicating that GN sheets are well distributed and well-wetted in the matrix. No clustering of the nanosheet fillers was observed. This even distribution is dependent on some parameters such as the type of GN surface modification, the preparation method of polymer/GN nanocomposites, and the existence of polar groups in the PMMA or GN [153]. Highly magnified SEM images indicate that the graphene sheets are surrounded by PMMA (Figure 3.2 (b)). Presumably, this is due to the interaction between GN and polymer matrix. 24 The graphene sheets may contain pendant hydroxyl groups across their surface which reacts with carbonyl groups of PMMA (which is a polar polymer) and forms a hydrogen bond. This phenomenon is beneficial as it leads to close GN–PMMA interactions and a percolated interphase [154]. Also, there lies a polar–polar interaction between the methacrylate (-COOCH3) of PMMA and the remaining carbonyl of GN. Figure 3.2 The SEM images of the PMMA-Graphene film at different magnifications of a) 2.5k and b) 10k. (Reproduced from [90] with permission from Elsevier) Multiple tests were conducted for different mass ratios of the composite (within the range of 10, 5, 2.5, 0.1, 0.05, 0.025). For the ratio of 10:1, which is used in this paper, the results revealed that the graphene fillers develop a network with the most robust electrical change, also known as the percolation threshold [107]. This percolated network can be achieved at a low loading fraction due to high conductivity and high aspect ratio of GN. Thus, for the developed PMMA-GN nanocomposite, GN formed a network within the polymer matrix, and significantly increased the overall electrical conductivity of the sensor. The electrical properties of the GN-PMMA film are shown in Figure 3.3. GN has a zero-overlap semimetal characteristic with the electron configuration of 2s2 2P2 in its valance layer [155]. 25 In GN, 3 of the 4 outer shell electrons are interconnected on the two-dimensional plane, and the last electron will be freely available in the third dimension, resulting in high electrical conductivity [156]. Adding a non-conductive polymer, e.g. PMMA, decreases the conductivity of the film. Due to the reverse relationship between the conductivity and the resistivity, it is expected that the impedance of the film containing PMMA and GN increases compared to that of the graphene film. Figure 3.3 The effect of the thin film on the impedance behavior of the sensor. The results are presented in the form of a Bode plot (Reproduced from [90] with permission from Elsevier) 3.2.2 Electrochemical impedance spectroscopy (EIS) measurements The selectivity of the sensor is represented by the electrochemical behaviors of the sensing layer while being exposed to different analytes. The Nyquist plots of the sensing films in KCl (0.5M) solution at room temperature are shown in Figure 3.4. The measurements were conducted at the frequency range of 1 to 106 Hz for different analytes (all at the 26 concentration of 0.025%v/v equivalent to 19.7 ppt). The Nyquist plots form a straight line (with different slopes and magnitudes) and the K+ and Cl- distribute charges randomly but uniformly throughout the detected area and hence result in linear signals in EIS. At the high-frequency region, the sensor acts as a conductor. Of note, the Nyquist plot of the analytes in KCl, as a non-faradaic probe, is different from those in water which usually forms the classic patterns of depressed semicircles passing through the axis origin with a tail [157]. At higher frequencies, the system can be modeled by a parallel RC circuit representing the resistive and capacitive components of the film. Due to the higher electric conductivity of the KCl solution (as the ionic liquid (IL)) in comparison to water, the depressed half circle is removed from the Nyquist plot, facilitating a more accurate analysis of the analyte/sensing layer behavior. Thus, all experiments were performed in the KCl solution as the supporting electrolyte. Since the conductivity of ILs increase with temperature [158], all the tests and measurements were conducted at room temperature. Figure 3.4 The Nyquist plots of EIS for: ethanol, IPA, acetonitrile, and acetone with the concentration of 0.025 %v/v (equivalent to 19.6 ppt) in 0.5 M KCl. The frequency (𝑓) range is within 100 KHz to 1 Hz (Reproduced from [90] with permission from Elsevier) 27 The impedance of the film exposed to four analytes (ethanol, IPA, acetone, and acetonitrile) in a 0.5-M KCl solution (as the supporting electrolyte) is shown in Figure 3.5. Increasing the concentrations of the analytes decreases the imaginary part of the tail of the Nyquist plot until the polymer reaches its percolation threshold and becomes saturated (and hence does not accept any more analyte to change its impedance). Figure 3.5 - Bode plots for acetone (red), ethanol (purple), IPA (green), and acetonitrile (blue) in 0.5 M KCl, with the concentration of 0.0025, 0.0125, 0.0375, and 0.0875 %v/v (equivalent to 1.96, 9.85, 29.5, and 69 ppt); frequency from 100 KHz to 1 Hz (Reproduced from [90] with permission from Elsevier) 28 Figure 3.6 - Nyquist plots for acetone (red), ethanol (purple), IPA (green), and acetonitrile (blue) in 0.5 M KCl, with the concentration of 0.0025, 0.0125, 0.0375, and 0.0875 %v/v (equivalent to 1.96, 9.85, 29.5, and 69 ppt); frequency from 100 KHz to 1 Hz (Reproduced from [90] with permission from Elsevier) The reproducibility of the sensor response was investigated by exposing the film to the analytes 6 times consecutively under the same experimental conditions (see Figure 3.7 showing the EIS measurements obtained from these tests in the KCl aqueous solution). The standard deviation (SD) and % relative standard deviation (RSD) were 6.36 and 0.1045, with the mean value of 481.86 and 0.6172, respectively, at the frequency of 10000 Hz, showing the ability of the sensor to recover to its initial conditions. The even distribution of GN on a microscopic scale, uniformity of the alignment within PMMA matrix, and the strong interface with PMMA, are key factors reflected in the stability, and electrical and mechanical properties of the PMMA-GM nanocomposite film developed here. 29 Figure 3.7 a) The relative change in the impedance of the thin film exposed to 0.025%v/v (equivalent to 19.7 ppt) of ethanol in 0.5M KCl for 6 repetitions. b) The error bars show the standard deviations of the measurements. (Reproduced from [90] with permission from Elsevier) The calibration curve of the sensor under the optimal conditions (the applied voltage of 100 mV in a frequency range of 100 KHz to 1 Hz with 50 step/dec) is shown in Figure 3.8. The sensor demonstrated a linear response for all the analytes within the concentration range of 0.0025%v/v to 0.0875 %v/v (equivalent to 1.69 to 69 ppt); while the 𝑅2 values are 0.93, 0.95, 0.98, and 0.98 for ethanol, IPA, acetone, and acetonitrile, respectively. 30 Figure 3.8 The calibration curve for ethanol (𝑅2=0.93), IPA (𝑅2=0.95), acetone (𝑅2=0.98), and acetonitrile (𝑅2=0.98) (Reproduced from [90] with permission from Elsevier) 3.2.3 Equivalent circuit and feature extraction Based on the Bode and Nyquist plots of the film, the results are characterized by a simple three-element equivalent circuit, consisting of a film resistance (𝑅𝑓), resistance of the solution (𝑅𝑠) and a CPE (as the pseudo capacitance.) Although different equations were proposed for CPE [159–161], the most common relationship is as follows [151]: 𝑍𝐶𝑃𝐸 =1𝑇(𝑖𝜔)𝑃 (16) where 𝑖 is the unit imaginary number, 𝜔 is the angular frequency (rad. s−1), 𝑇 is the CPE parameter (F cm−2 sα−1) and 𝑃 is the CPE exponent. The values of 𝑃 (CPE-P) and 𝑇 (CPE-T) play an important role in the characteristics of the element. When the CPE-P is equal to 1, (𝑃→ 0), the CPE acts like a capacitor with a phase angle near 90 deg. (while values of CPE close to 0.5 are inherently a diffusion type impedance [162]). When the CPE-P is equal to 0 31 and -1, the CPE acts like a resistor and the inductor, respectively. For the currently developed film, CPE-P never reached below 0 since there was no positive data for the phase angle through the working frequencies. This is because CPE-P is highly dependent on both the fractal geometry of the interface and the shape and roughness of the surface [163]. Using ZView, the values of CPE-P were recorded to be in the range of 0.79 to 0.83, independent of the analyte, leading to the assumption of a constant CPE-P for all targets. This means that the selectivity is based on CPE-T, resistance of solution, and the film. Figure 3.9 The Bode plot from the experimental data and the fitted 3-element equivalent circuit for 0.025 %v/v equal to 19.7 ppt ethanol in 0.5 M KCl (Reproduced from [90] with permission from Elsevier) The values of the three-element equivalent circuit were obtained by fitting it to the Bode plots obtained for each analyte exposed to the PMMA-GN film (see Figure 3.9 for 0.025 %v/v equal to 19.7 ppt ethanol in 0.5 M KCl). For each analyte, the phase angle reached a constant 32 value in the frequency range of 10-1000 Hz, while reaching its maximum (-80 deg.) at 150 Hz. The results indicate that at low frequencies, the film acts like a capacitor where the electrodes are connected via the electrolyte. One explanation for the phenomenon is that the CPE behaves as an open-circuit and its voltage becomes equal to the source voltage [164]. At high frequencies, on the other hand, the magnitude of the impedance reaches a constant minimum value, indicating the minimum impact of the frequency on the impedance of the film as the CPE shorts the resistance of the film. The selectivity of the sensor was examined by the values of the equivalent circuit, obtained from the experimental Nyquist and Bode plot. The values of the elements in the equivalent circuit are shown in Table 3-1 and plotted in a 3D and 2D scattered diagram as demonstrated in Figure 3.10. According to Table 3-1, the values of CPE-P for all analytes are in the range of 0.75 to 0.85 (being independent of the concentration), showing that the capacitive behavior of the film dominates its resistive behavior. Although the values of CPE-P are distinctive for each analyte, the closeness of these figures leads us to neglect their values in the analysis. The values of the resistance of film and solution and CPE-T are depicted in Figure 3.10 a, the (the cross sign represents the average values of the element for each analyte). The cluster of each analyte at different concentrations further demonstrates the high differentiability of the film to the selected targets. It is inferred that among the elements of the equivalent circuit, CPE-T and resistance of the solution present more differentiation between the analytes than the resistance of the film. Therefore, the values of CPE-T and 𝑅𝑠 are selected as the features and plotted in a 2D figure to demonstrate the selectivity of the sensor (Figure 3.10 b). As presented in Table 3-1 and Figure 3.10 b and, ethanol has the highest solution 33 resistance while IPA shows the largest magnitude for the film resistance (𝑅𝑓). The high value of CPE-T for acetone can be explained with the 2D distribution formula of CPE, proposed by Brug et al. [160]: 𝑍𝐶𝑃𝐸 = 𝑇𝑃(1𝑅𝑠+1𝑅𝑓)𝑃−1𝑃 (17) At a fixed CPE-P, the higher resistance of the solution and film results in lower CPE-T. The results presented in Figure 3.10 b show the synergetic effect of GN and PMMA resulting in a highly selective and sensitive sensor in the range tested (0.0025% v/v to 0.0875% v/v). Figure 3.10 The values of the elements of the equivalent circuit for ethanol, IPA, acetonitrile, and acetone in KCl in a) 3D, and b) 2D plots (Reproduced from [90] with permission from Elsevier) 34 Table 3-1 The values of the three-element equivalent circuit for different concentrations of the analytes in a 0.5-M KCl solution Analyte Concentration (%v/v) → (ppt) 𝑹𝒔 (Ω) CPE-T (10-6 ) CPE-P 𝑹𝒇 (Ω) (106) Ethanol 0.0025→1.96 75.61 2.19 0.77 2.28 0.0125→9.85 77.3 2.18 0.78 2.70 0.025→19.7 79.8 1.96 0.77 1.78 0.0375→29.5 83.54 1.73 0.79 1.11 0.0875→69 89.1 1.68 0.79 1.01 IPA 0.0025→1.96 58.22 4.96 0.82 1.14 0.0125→9.85 59.19 4.12 0.82 5.65 0.025→19.7 61.63 4.19 0.81 5.54 0.0375→29.5 62.39 4.42 0.81 1.13 0.0875→69 64.26 4.41 0.81 6.14 Acetonitrile 0.0025→1.96 44.7 3.00 0.82 3.00 0.0125→9.85 44.9 2.27 0.83 3.98 0.025→19.7 45.9 1.91 0.83 3.37 0.0375→29.5 49.7 1.56 0.84 3.99 0.0875→69 51.7 1.80 0.83 4.00 Acetone 0.0025→1.96 38.46 6.28 0.79 0.17 0.0125→9.85 38.88 7.16 078 0.24 0.025→19.7 40.27 6.60 0.78 0.42 0.0375→29.5 42.22 6.32 0.78 0.517 0.0875→69 43.12 6.81 0.78 0.53 35 4 Chapter 4: PDEIS behavior of polyaniline and polypyrrole modified pencil electrodes in presence of heavy metals4 4.1 Experimental Method 4.1.1 Chemicals and substrate Distilled and unmodified aniline (≥99.5%) and pyrrole (98%) (sigma chemicals, USA) were purified until they were eventuated to colorless liquids and kept in the dark at 5° C. Fresh phosphoric acid (sigma chemicals, USA), analytical grade, was used. Oxygen-free nitrogen (OFN) was prepared from Nissan-IOI, Malaysia. All aqueous solutions were newly prepared using ultra-pure water from Milli-Q plus (Millipore Corp., USA). All other chemicals including calcium chloride, potassium chloride, potassium ferricyanide, copper chloride, sodium perchlorate, and chromium nitrate (Merck KGaA, Germany) were analytical grade and used without any purification or further treatment. 4.1.2 Sensor Fabrication A conventional custom-made three-neck electrochemical cell was designed and used, accompanied by two composite 2B pencil graphite (1.8 mm diameter ∅ and 100 mm length, Staedtler Lumograph, Germany) as the working electrode to be covered with pyrrole and aniline monomer, an external platinum (Pt) wire, cleaned with a 1:1 H2SO4/HCl solution, as the counter and pseudo-Ag/AgCl wire as a reference electrode to complete the circuit, to which all potentials are referred. 4 Parts of this chapter have been submitted as a full paper in Talanta, 36 The pseudo Ag/AgCl reference electrode was synthesized by putting a silver wire with a platinum electrode in a saturated KCl solution and applying the DC voltage of 1.6 - 1.8 V for 20-30 minutes. To remove the impurities and defects, the graphite leads were treated with 5% HNO3 overnight, washed with DI water and dehydrated at room temperature before sealing into the PVC tube. After preparing all the standard electrodes, the electrochemical syntheses and electrodeposition of PAni and PPy on 2B pencil graphite (as unmodified electrode) were potentiodynamically performed by cyclic voltammetry on 10 mL aqueous solution, comprising 0.5 M phosphoric acid (H3PO4) and 100 mM of aniline, as well as 0.1 M NaClO4 and 100 mM pf pyrrole, at a scan rate of 100 mv/s over applied and sweeping potential ranges (vs. Ag/AgCl) from -0.2 V to + 1.0 V. Prior to electrodeposition, both solutions were stirred for 20 minutes to be homogenized. The film thickness is controlled by the number of cycles in CV as a thick sensing layer results in lower response due to the generation of an additional resistance into the cell. 4.1.3 Experimental Setup and electrical measurements The preparation of each trace ion was achieved by dissolving the corresponding substance in DI water and stirring for 15 min and the following concentrations were obtained by further dilution. All the electrochemical measurements were conducted by personal-controlled and computer-equipped CompactStat potentiostat (Ivium Technologies, Netherlands) interfaced with IviumSoft software package for data collection and characterization of cyclic voltammetry (CV), EIS, and PDEIS measurements, respectively. The potentiostat plays as the actuator in PDEIS probing. 37 PDEIS was performed within the frequency range of 15 to 1000 Hz by real-time analysis of 20 wavelets at each 2 mV step of a staircase potential ramp with a ramp rate of 2 mV/s (narrower than the probing amplitude) to provide a quasi-continuous scan. In PDEIS, due to the nonstationary characteristics of the system, a low range of frequency is applied, and the potential variation is lower than that of EIS at the lowest frequencies. All the stages were established by superposition of the responses at various phase shifts through the probing stream. EIS assessments of the modified electrode versus the reference electrode were then conducted in another 10 ml solution (consisting of 10 μM of the trace element) by applying a sinusoidal wave of 100 mV in a frequency range of 100 KHz to 0.01 Hz with 50 step/dec under OFN atmosphere at the temperature of 25± 2.5° C. In all experiments, CP-functionalized PGEs were immersed in the stirred solution (300 rpm) containing the metal ion to be accumulated on the electrode surface , and pH values were also taken into account. The electrode was then removed from the sample solution, rinsed with ultrapure water, and put in the supporting electrolyte. To monitor the electron transfer along the electrode and electrolyte, anionic-probe ion pairs, i.e. Fe(CN)6 3−, was used as the redox probe. Also, all experiments were conducted at a constant pH of 3 (as suggested in [165]) . It is worth mentioning that at higher pH values (e.g. > 6.0), hydrolysis of the ions (occurring by the formation of hydroxylated species) may interfere with the accumulation of ions at the surface of the electrode. Although the sensors were both reusable after each experiment, fresh films were used for each analyte of interest for a more accurate investigation of the electropolymerized polymers. 38 4.2 Results and discussions 4.2.1 Electrochemical characterization of PAni/ and PPy/ modified PGE The cyclic voltammetry of PPy and PAni modified PGE along with the schematic of the experimental setup is shown in Figure 4.1. It is widely accepted that in acidic environment, aniline radical cations (which have been produced at the beginning of oxidation) are paired together in the polymerization process [166]. The cation itself is acidic, so it is expected to remain stable in an acidic environment. The structure of the primary dimers of aniline during oxidation can be head to head, tail to tail, and head to tail (depending on the molar ratio of the species to the pH of the environment) [167]. Polyaniline is the result of the sequential bonding of the aniline monomer units to the polymer chain. The presence of nitrogen atoms in phenyl rings causes different redox forms in the physical properties of polyaniline to occur. Typically, there are three distinct forms depending on the degree of nitrogen oxidation. These forms include completely-reduced form, semi-oxidized form, and fully-oxidized form, namely Leucoemeraldine Base (LB), Emeraldine Base (EB), and Pernigraniline Base (PB), respectively. As shown in the cyclic voltammogram of aniline on the graphite pencil tip (see Figure 4.1b), the anodic peak occurs in the first forward scroll due to the monomer radical cation formation. However, the cathode peak is not displayed in returned scroll because of the involvement of radical cations together [168]. This indicates the irreversibility of the electropolymerization process. Figure 4.1c illustrates the three pair peaks in potential ranges of 1 to -0.2 V. First pair peak is for transformation of LE to ES in the range of 0.2 -0.3 V (O3/R3), following by the second pair peak (in the range of 0.6 V (O1/R1)) representing oxidation of ES to PB. Finally, pair peaks which are in potential range of 0.3 to 39 0.6 V (O2/R2) belong to decomposition of hydroquinone to quinone. Of note, overoxidation of PAni can generate the significant part of the film to quinone to control the conductivity [169]. The generation of PPy by pyrrole monomers follows the same concept as oxidation of aniline units. However, for the case of PPy, the nitrogen atoms connect the chains of the monomers, where imine nitrogen atoms is more subject to protonation that that of amine atoms [170]. The Pyrrole’s cyclic voltammetry does not display any obvious configuration peaks (see Figure 4.1-a), so their synthetic peak is used to interpret their electrochemical properties. The peak of the CV in polypyrrole have shifted to the negative potentials due to the monomer oxidation and easier formation of radical cations. Also, the current of synthetic peak also reduces with each cycle because of lower conductivity of modified electrode in comparison to the graphite. 40 Figure 4.1 Schematic representation of the test setup a) CV of polypyrrole b and c) CV of aniline d) with the three-electrode cell f) deposition of the CP on the surface of the PGE 4.2.2 EIS measurements and selectivity As PPy PGE showed high values of impedance at high applied potentials, the value of V = 0.6 V is selected as the bias potential for EIS measurement. Figure 4.2-a shows the EIS Nyquist plots of electro-synthesized polypyrrole in the 10 μM Cr (III), Cu (II), and Fe (III) in aqueous media. The Nyquist plot of faradaic solutions forms the classic pattern of depressed semicircle at high frequencies with a straight line as a tail of the circle at low frequencies. The radius of the circle is proportional to the resistance of the system to the flow of the electrons at the interface and represents the charge transfer resistance and the formation of the double layer capacitance at the modified electrode/solution interface while the straight line is usually attributed to a contribution of diffusion and other parameters [136,171]Thus, 41 the small diameter of the depressed half circle contributes to the low resistance of the film against the flow of the electrons. The Randles equivalent circuit has been considered and its values are presented in Figure 4.2-b for the charge transfer resistance (𝑅𝑐𝑡) and Figure 4.2-c for the double-layer capacitance (𝐶𝑑𝑙). It is obvious that the low value of 𝑅𝑐𝑡 represent high charge transfer and redox transformation for the conducting polymer. Also, when the Warburg impedance decreases, diffusion of protons and permeability of ions on the surface of the polymer-electrolyte increase, resulting in a better charge transfer. Although the values of 𝑅𝑠 are very similar to those of the analytes (as their Nyquist plots start from the origin in the existence of supporting electrolyte), the values of charge transfer resistance are different: 90 Ω, 31 Ω, and 9 Ω for Cr (III), Cu (II), and Fe (III), respectively. It should be noted that conductivity of the elements of Period 4 (in the periodic table) is higher than other metals due to filling of 3d orbitals. Thus, the shielding effect increases diminishing the effect of the core on the valence layer helping the electrons to move freely. Since conductivity of Cr (III) is lower than that of Cu (II), and Fe (III), higher charge transfer resistance happens for Cr (III). The higher charge transfer resistance of Cu (II) compared to Fe (III) can be attributed to the coordination of one Cu (II) ion with four nitrogen atoms of the PPy film which provides a higher number of bonding and greater bonding affinity as compared to the case of Fe (III). Also, in this four-coordinate system where the copper ions stay tetrahedrally coordinated in oxidation states, the electron self-exchange rate (the contribution of the copper redox couple) is extremely low which leads to higher resistance [172] as compared to the case of Fe (III). Finally, different values of 𝑅𝑐𝑡 and 𝐶𝑑𝑙in the equivalent circuit as well as selective behavior of the PPy modified PGE can be contributed to the adsorptive capacity of PPy due 42 to chelation of the nitrogen atoms on the PPy surface with heavy ions at the faradic current [173]. Figure 4.2 a) Nyquist spectra of electro-synthesized PPy in the electrolyte at 0.6 V and the values of b) charge transfer resistance, and c) double layer capacitance for the corresponding equivalent circuit For the sake of comparison, PAni modified PGE is tested to study the effect of the change in the sensing layer on the selectivity of the sensor (Figure 4.3). Unlike PPy, the bias voltage of 0.6 V produced a large incomparable impedance for the electro-synthesized PAni modified PGE. Thus, the Nyquist spectra have been represented at the voltages of 0.8 V, 0.9 V, and 1.0 V to study the effect of metallic ions on the electrochemical behavior of PAni. In general, at room temperature, the conductivity of PPy is higher than that of PAni in metallic regimes [174], especially in the cases that Fe (III) salts are used as the oxidants [170]. Thus, by increasing the bias voltage, the current at the interface increases and leads to decrease in the charge transfer resistance of the solution of analyte without changing its resistance (the range of 𝑅𝑠 is similar for Cr (III), Cu (II), and Fe (III) solutions). The change in the charge transfer resistance (as a result of changing the voltage) can be explained by Eq. (9) [175]: 𝑅𝑐𝑡 = (𝜕𝐼𝜕𝑉)−1 (18) 43 In the above equation, the potential is rapidly changed to keep the perturbation at the surface constant. Thus, the values of the charge transfer resistance, i.e. the radius of the half circle, is significantly different at different voltages as well as different analytes. As a result, the charge transfer can be used as a promising parameter for feature extraction to selectively differentiate different analytes. Unlike charge transfer resistance, which is in direct correlation with bias voltage, a non-linear regression equation is modelled for the double layer capacitive behavior of electrochemical studies for a magnitude K of current change ( such as 𝑉(𝑡) − 𝑉(0) = −𝑅𝑐𝑡𝐾(1 − 𝑒−𝑡/𝑅𝑐𝑡𝐶𝑑𝑙)[176]) Therefore, the values of 𝐶𝑑𝑙 is not directly related to the bias voltage but generally increases by the increment of the voltages from 0.8 V to 1.0 V. Of note, while at low voltages, no degradation and high efficiency is mostly reported, but creates parallel/series issues at high voltages [177]. The values of 𝐶𝑑𝑙 follows the same trend as to PPy reasonably attributed to the similar structure and consequently, higher interface between iron and the electrolyte than those of copper and chromium, as reported previously. 44 Figure 4.3 - The Nyquist spectra of electro-synthesized PAni in the electrolyte at a) 0.8 V, b) 0.9 V, and c) 1.0 V. The values of d) resistance of solution, e) charge transfer resistance and f) double layer capacitance for the corresponding equivalent circuit 4.2.3 EIS characteristics of reduction potential To study the underpotential effect for PDEIS analysis, the reduction and deposition potentials of the metal ions in the electrodes were also investigated. The reduction potentials of the 10 μM Fe (III), Cr (III) and Cu (II) in aqueous medium on the modified electrode containing PPy were obtained as 0.31 V, 0.4 V, and 0.28 V for each trace element, respectively. The impedance spectra of the solutions on their corresponding reduction potentials was scrutinized in Figure 4.4i((a)), (b), and (c)) The charge transfer resistance of Fe (III) contained solution on its reduction potential is lower than that of Cr (III) and Cu (II) due to the necessity of unpaired electrons in Fe orbitals. Same trends were observed for PAni (see Figure 5ii((a), (b) and (c)). However, for PAni, the reduction potentials of Cu (II) and Fe (III) are in the same range as they have they have the same ionization energy. As the results shown in see Figure 4.4iii), the 𝑅𝑐𝑡 value of Cr (III) is the largest in both films (PPy and PAni) due to its larger average particle size, leading to a longer diffusion pathway for electrons, which hinders the electron transfer between the electrolyte and electrode [178]. For Cu (II), the electron configuration is [Ar]4s13d10, which means the core is 45 influenced by 10 electrons and the shielding effect on the electron of the last layer decreases, so the electron moves away from the core and reduces the charge transfer resistance. Figure 4.4 Nyquist spectra of electro-synthesized i) PPy and ii) PAni for the analytes of (a) Cr (III), (b) Cu (II), and (c) Fe (III) at their corresponding reduction potential. The values of (iii) charge transfer resistance, and d(iv)) double layer capacitance 4.2.4 Potentiodynamic profiles In electrochemical measurements, a bias signal is initially assigned affecting all the parameters. Therefore, the resulting EIS spectra are snapshots of a stationary system at fixed and constant potential states. However, optimization of the bias potential prior to all the measurements are required to obtain a highly selective and sensitive sensing layer with 46 further efficiency. In this regard, PDEIS is performed to study the change in the system for a range of potentials in the time domain. Figures 4.5 and 4.6 shows the PDEIS spectra of Cr (III), Cu(II) and Fe (III) on PPy- and PAni- modified PGE, respectively. In these figures, the cyclic voltammograms are related to different reversal potentials. As the impedance signals at adjacent potentials are smoothly connected, no abrupt steps are seen in the waveform. The AC components (impedance and capacitance) have been decomposed and shown potential dependences. In both PPy and PAni modified PGE, the magnitude of the impedance and other electrochemical parameters is the function of the applied potential of the conductive polymer. PPy modified PGE is much less conductive at high potentials, e.g. > 0.8 V. The minimum value of impedances for Cr (III), which mainly correspond to the charge transfer, takes place at 𝑉 = 0.1 V (Figure 4.5 a(1)). In contrast, electrodeposition of adatoms of Cr (III) on the non-metallic PPy modified PGE electrode significantly changes the electrochemical interface, i.e, the. double layer capacitance (Figure 4.5 a(2)). For Cu (II), the film showed a very low resistance behavior among different metals in a broad range of 𝑉 = -0.2 V to 0.7 V with the lowest values in the voltage range of V=0.1-0.4 V (see Figure 4.5 b(1)). In comparison to Cr (III), Cu (II) has a larger span of low impedance due to its good conductivity (its outermost 4s energy zone is only half filled, transferring electric current by more electrons). At all potentials, Cu (II) PPy PGE showed a relatively lower double layer capacitance than that of Cr (III) (Figure 4.5 b(2)). Same as Cr (III) and Cu (II) contained electrode, PPy modified PGE reveals an almost-constant impedance for Fe (III) at low potentials (Figure 4.5 c(1)). After a pseudo-sinusoidal impedance variation, the electrical 47 impedance sharply increases at 𝑉 = 0.8 V until it reaches its maximum value at 𝑉 = 1.0. This shows the capability of the PPy modified PGE to differentiate between the elements since each metal has shown its unique electrochemical behavior in the media. Also, in comparison to Cr (III) and Cu (II), PPy modified PGE exposed to Fe (III) shows a more constant values of capacitance at low voltages (𝑉 = -0.2 V to 0.5 V) and increases drastically at 𝑉 = 0.7 V (Figure 4.5 c(2)). In potassium ferrocyanide (K4[Fe(CN)6]), the salt reacts and reveals Fe(III) with the configuration of [Ar]3d6,4s2 with one lone electron. Simply, the unpaired electron can be attracted to the poles of the magnet and produces the paramagnetic characteristic of the iron. This may be the reason that Fe (III) salts are the typical oxidants for production of highly conductive PPy [170]. The increase in the double layer capacitance at the beginning of bulk ion growth in all samples can also be attributed to the decrease in dielectric permittivity in the nucleation stage [179,180]. Figure 4.5 PDEIS spectra of electrosynthesized PPy within the potentials of -0.2 V to 1.0 V for a) Cr (III), b) Cu (II), and c)Fe (III) and the values of (1) impedance and (2) double layer capacitance as a function of potential 48 The potentiodynamic electrochemical behaviors of the PAni modified PGE while exposed to the trace elements are shown in Figure 4.6. It has been reported that PAni is highly resistive at negative and sufficiently positive potential [181]. The solution of Cr (III) shows the least resistivity (impedance) while the potential is within the range of 𝑉 = 0.1 V to 0.4 V (see Figure 4.6 a(1)). Then, the real and imaginary parts of the impedance rise dramatically while reaching to the highest values at 𝑉=0.7 V. There is no linear relationship between the magnitude of the impedance and capacitance, meaning that the lowest value of the capacitance does not necessarily takes place at the same potential where the highest magnitude of the real and imaginary part of the impedance occurs (see Figure 4.6 a(2)). As shown in Figure 4.6 b(1), the PAni film also showed a smaller range of low impedance when it is exposed to the Cu (II) solution (as compared to Cr (III)). For both PPy and PAni films exposed to Cu (II), the same range of potentials (𝑉 = 0.1 V to 0.4 V) with the lowest resistivity was obtained. Higher stored electric energy is at the interface of Cu(II) electrode and electrolyte is also observed between 𝑉 = 0.3 V to 0.6 V (Figure 4.6 b(2)). The PAni film exposed to Fe (III) showed a very high impedance value at negative potentials which slowly decades until it reached its lowest value at 𝑉 = 0.2 V (Figure 4.6 c(1)). The sharp peak observed at the double layer capacitance profile of Fe (III) (for the PAni modified PGE) is attributed to the generation and subsequent oxidation of Fe nuclei (Figure 4.6 c(2)). In general, for all studied tests, PAni modified PGE showed more dependency on the potential in comparison to PPy, with the lowest values of impedance at positive voltages near 0, i.e. 𝑉 = 0.1 V to 0.4 V. 49 Figure 4.6 PDEIS spectra of electrosynthesized PAni within the potentials of -0.2 V to 1.0 V for a) Cr (III), b) Cu (II), and c)Fe (III) and the values of (1) impedance and (2) double layer capacitance as a function of potential 50 5 Chapter 5: Development of the Ppy-based chemiresistive sensing platform for detection of volatile organic compounds in water and standard electrolyte solution5 5.1 Experimental Method 5.1.1 Chemicals and substrates All reagents were in analytical grade without further purification unless it is mentioned. Distilling under vacuum, the polymer was grown potentiodynamically in an aqueous solution containing 0.1 M pyrrole monomer (Merck KGaA) and 0.1 M lithium perchlorate (LiClO4- Sigma-Aldrich) as the anionic doping agent for the chemical bath. 68.2 μL pyrrole was initially dissolved in 10 ml distilled water and then 100.6mg salt was gradually added to the stirring solution as the oxidant. A conventional three-electrode electrochemical cell was utilized with a gold chip surface served as the working to be covered with PPy, an external Ag/AgCl wire as the reference, and an external platinum wire as the counter electrode. Of note, some on-chip potentiostats have been recently developed which is not used in this paper, due to ease of access [182]. The interdigitated gold electrode had two terminals on a glass substrate with a 5μm gap and 250 digits (125 on each side) and a digit length of 6760μm. The cross-section area of the electrode was chosen to be small to impede the formation of capacitance and high impedance at low frequencies. 5 Parts of this chapter have been submitted as a full paper in Sensors and actuator B – Chemical, 51 One very common issues of electrochemical method, particularly for H2S and hydrosulfide (HS-), is the elemental sulfur, results from the oxidation by-product of H2S at low potentials (<+0.2V), i.e. 𝐻2𝑆 → 𝑆0 + 2𝐻+ + 2𝑒− and 𝐻𝑆− → 𝑆0 + 2𝐻+ + 2𝑒− [183]. The insoluble elemental sulfur adsorbed onto the surface of the electrode, passivates it by blockage of the electroactive sites, which causes poor sensitivity and unstable results. Also, the formation of polysulfides after each oxidation of H2S, which is the result of applied potential, thickens the insulating layer, and affects the sensitivity as well. One option is applying higher potentials (>+1.0V) to form sulfur oxides but may cause disturbance and interference on other electroactive sites and is not applicable [184]. To overcome the fouling effect of sulfur, alkaline solutions with a redox mediator can transform electrons from H2S (and HS- at pH=7.0) to the working electrode and impedes direct contact between them. The redox probe contains 5mM 𝐾3𝐹𝑒(𝐶𝑁)6, 5mM 𝐾4𝐹𝑒(𝐶𝑁)6, and 0.1 M KCl (Sigma Aldrich – Missouri – United States), with the following mechanism: 2[𝐹𝑒(𝐶𝑁)6]4− ↔ 2[𝐹𝑒(𝐶𝑁)6]3− + 2𝑒, and 2[𝐹𝑒(𝐶𝑁)6]3− + 𝐻𝑆− → 2[𝐹𝑒(𝐶𝑁)6]4− + 𝐻+ + 𝑆. For electropolymerization, CV was performed by sweeping the electrode potential from 0.0 to +0.8 V at a scan rate of 0.05 V/s using a potentiostat electrochemical instrument (VersaSTAT 4 - Princeton Applied Research) (Figure 5.1). In an equilibrium reaction, NH4SH forms as a result of a reaction between NH3 and H2S (𝐻2𝑆 + 𝑁𝐻3 ↔ 𝑁𝐻4𝑆𝐻) with the equilibrium constant, Kp, of [185]: 𝑙𝑜𝑔10𝐾𝑝 =∆𝑆2.303𝑅−∆𝐻2.303𝑅𝑇 (19) 52 In which ∆𝑆 and ∆𝐻 are the change in entropy and enthalpy of the reaction per degree Kelvin, respectively. R and T are gas constant and temperature. A simplified equation for the equilibrium constant of the reaction is [186]: 𝑙𝑜𝑔10𝐾𝑝 = 14.83 −4715𝑇 (20) Based on the above equation, the reaction of (𝐻2𝑆 + 𝑁𝐻3 ↔ 𝑁𝐻4𝑆𝐻) has the equilibrium constant in the range of 0.3<Kp<0.4. 5.1.2 Instruments and analysis The schematic of the sensing platform is shown in Figure 5.2. The electrochemical characterization of the electrodes covered with PPy was investigated by means of impedance spectroscopy. Each concentration of the sample was prepared by diluting a certain amount of H2S (0.4% dissolved in water – LabChem, Pennsylvania, United States) and NH3 (25% Merck KGaA, Darmstadt, Germany) solution in the electrolyte and waited for a required time so that the analytes thoroughly diffuse through the electrolyte. The sensor was then stated in contact with the solution and a sinusoidal wave of 100 mV in a sweeping frequency range of 100 KHz to 1 Hz with 50 step/dec was recorded for 45 seconds. To minimize the film disturbance and consequently, signal-to-noise ratio, the voltage was selected as low as possible. Also, as frequencies lower than 1.0 Hz extended the measurement time without any significant analytical data, the minimum value of frequency was set to 1.0 Hz. The impedance spectra were recorded three minutes after dipping in the solution, so the analyte has enough time to evenly distribute through the media. All experiments were performed at room temperature and the pH of the electrolyte was controlled and kept constant at 6.9. Each test 53 was replicated three times under the same condition, e.g. temperature and pH as they might affect the electrochemical behavior of the film [187]. 5.2 Results and discussion 5.2.1 Characterization of thin film In the electrochemical synthesis of PPy, the morphology of the film is highly affected by monomer concentration, electrode material, counter ions, roughness, and electrochemical parameters of cyclic voltammetry [188]. PPy is a highly redox active and electron affinitive material. During electropolymerization, anions (ClO4-) are incorporated into the polycationic oligomers to keep it electroneutral. Cations (Li+) in the electrolyte medium also permeate through the polymer matrix. In this process, pyrrole, as a p-type organic, is oxidized and released radical cations to the solution, and then the oligomers slowly deposited on the surface of the gold. The cyclic voltammetry of polypyrrole scanned between 0.0 V and 0.8 V is shown in Figure 5.1 C. As the thin film grows, the peak of the oxidation and reduction of the PPy, as well as the charging currents, increase. The oxidation peak, results from the formation of pyrrole radical cations, was observed in a broad spectrum at the peak of 0.21 V and the reverse catholic peak was seen at 0.15 V. Notably, the pyrrole oxidation potential is highly dependent on the scan rate of the polymerization. At the scan rate of 5 mV/s, higher polymerization occurs resulted from more electron transfer in comparison to higher scan rates, e.g. 10 mV/s, 25 mV/s, and 50 mV/s [189]. Figure 5.1 D shows the electrical properties of the electrode before and after the deposition. Clearly, the conductivity of the old electrodes is higher than the semi-conductive PPy thin film. After CV and formation of 54 PPy on the surface of the electrode, the resistance and consequently the impedance of the chemiresistive sensor increases, providing a more robust response. Figure 5.1 Schematics of the impedance-transduced chemiresistor. (A) Deposition of PPy on the surface of the interdigitated electrode. (B) Dipping the chemiresistor in the electrolyte. (C) Exposure of the PPy film to the targets Figure 5.2 (A) CV of the electropolymerization of PPy. (B) The effect of the PPy film on the impedance behaviour of the chemiresistor: the inset figure shows the Nyquist spectra of the corresponding Bode plot. 55 5.2.2 impedance spectroscopy of hydrogen sulfide The real and imaginary components of the impedance of the sensor exposed to H2S for the range of frequencies from 100 KHz to 1 Hz is shown in Figure 5.3A. The Nyquist plots form a depressed half circle with a strike line at low frequencies (similar to all the faradaic probes). Based on a simple analogy, the radius of the Nyquist can be equivalent to the resistance in the DC mode. Considering H2S as an electron-donor chemical, it was expected that the film follows the same trend as other reducing molecules. However, due to deliberation of protons, the dynamic behaviour of the cations increases the ionic conduction of the oxidized film. Therefore, as H2S is adsorbed, proton transfer from H2S to PPy intensifies the doping level of the PPy backbone [137]. In other words, during the exposure, PPy is doped by H+ (dissociated from H2S). Proton doping increases the vacancy concentration in PPy, resulting in the augmentation of the conductivity and shrinkage in the resistance of the film. Thus, H2S reacts the same as other electron-withdrawing molecules, and the radius of the Nyquist plot shrinks as the concentration of H2S increases. The calibration curve of PPy film upon exposure to different concentrations of H2S is presented in Figure 5.3B. The sensors showed a linear response (𝑍𝐻2𝑆 =−9.787𝐶𝐻2𝑆[𝑝𝑝𝑚] + 294.2, Where 𝑍𝐻2𝑆 is the response and 𝐶𝐻2𝑆 shows the concentration of dissolved H2S) with the coefficient of determination of 𝑅2 = 0.995 for a broad concentration range of 500 ppb to 7.5 ppm. The error bars represent the standard deviation from the mean values. The error is less than 1% at each point. The large value of the coefficient of determination and low value of standard deviation indicate the good accuracy, reproducibility, and reliability of this sensing method. 56 Figure 5.3 A) Impedance spectra of the chemiresistor exposed to different concentrations of H2S, and (B) the impedance as a function of H2S concentration, presenting a calibration curve 5.2.3 Equivalent circuit The impedance spectra of the sensing layer are fitted to an equivalent circuit containing RC components and the Warburg impedance as the diffuse circuital element [90]. However, since the maximum value of the 𝑍’’ is smaller than half of the maximum value of 𝑍’, a constant phase element (CPE) is preferred rather than the ideal capacitance in the equivalent circuit (see the inset in Figure 5.4A). In the Bode plot (Figure 5.4A), there are two phase angles at high- and low-medium frequency regions, which are modelled by two capacitances, i.e., double layer capacitance (Cdl) and CPE (if there is any charge transfer). Notably, an ideal pure capacitance never occurs at the electrode/electrolyte interface because of the frequency dispersion, polarization effects, and the interfacial heterogeneity of the PPy [151]. In the equivalent circuit, 𝑅1 and 𝑅2 are Schottky contact resistances occurring at the interface of the electrode/PPy, and the ohmic (bulk) resistance between the electrodes, respectively. Cdl is the double layer capacitance, formed by the ion solvation. At low frequencies, electron 57 transfer is limited by the mass transport of the electroactive species, and hence a diffusion layer is formed within the matrix, which is usually considered by Warburg impedance (𝑍𝑤) [190]. This fitted Warburg impedance contains three parameters, W-R as the diffusion resistance, W-T representing the diffusion layer, W-P showing Warburg exponent [191]. According to Figure 5.4A, increasing the working frequency decreases the impedance of the sensor, which shows the weakening effect of the frequency on impedance at high frequencies. The phase angle of the sensing layer upon exposure to 5 ppm H2S is shown in Figure 5.4B. As there is no positive phase data, no inductive phenomenon is considered in the equivalent circuit. The negative phase after the frequency of 3000Hz is attributed to the signal delay. It is notable that at the frequencies higher than 10KHz, high discrepancy occurs because of the formation of additional stray capacitance and contact resistance [164]. The fitted data is also validated by the Nyquist plot (Figure 5.4C) as it shows the classic pattern of depressed half circle and followed by a strike line. 58 Figure 5.4 (A) The Bode, (B) phase angle, and (C) Nyquist plot of the PPy thin film to 5 ppm H2S and (inset) the corresponding equivalent circuit 59 5.2.4 impedance spectroscopy of ammonia To study the selectivity of the sensor to H2S, the impedance-frequency characteristics of the functional layer upon exposure to different concentrations of NH3 are further studies and shown in Figure 5.5 A. As the concentration of the NH3 increases, the radius of the half-circle expands. That is, the impedance of the chemiresistor under certain working frequency increases with the augmentation of NH3. Generally, PPy is a p-type (hole transporting) polymer and interaction with a target changes its conductivity. Deprotonation of PPy occurs by the bonding between the nitrogen atoms of NH3 and the free orbital of the dopant proton (H+) in the protonated form of PPy (PPyH+). Reduction by deprotonation, the rate of the diffusion of the molecules into the thin film is heightened. This decreases the hole density in PPy and arises the resistance of the chemiresistor. In other words, NH3 is an electron-donor (reducing) molecule, and by electron donation, it compensates for the positive charges in the polymeric chain. Interacting with NH3 adds electrons to the valance band of PPy, affecting the conductivity and resistance of the thin film due to the donation of the electrons of nitrogen to the oxidized PPy. General possible interactions between the ammonia and PPy are as follows: 𝑃𝑃𝑦+𝑋− + 𝑁𝐻3 ↔ 𝑃𝑃𝑦0…𝑁𝐻3+, 𝑋− (21) 𝑃𝑃𝑦+𝑋− + 𝑁𝐻3 ↔ 𝑃𝑃𝑦+(−𝐻)0 + 𝑁𝐻4+𝑋− (22) In which X- represents the dopant. While the former can be a mechanism to reduce the doping level of the film, the latter is a proton transfer between NH3 and PPy. The general reaction can be stated as follows: 60 𝑃𝑃𝑦𝐻+ + 𝑁𝐻3 ↔ 𝑃𝑃𝑦 + 𝑁𝐻4+ (23) As the impedance spectra of NH3 are similar to that of H2S, the equivalent circuit can be modelled using the one presented in Figure 5.5A. The magnitude of the impedance is proportional to the concentration of NH3, denoting an almost linear relationship. Figure 6B shows the calibration curve of the PPy film as it is exposed to NH3 at the frequency of 1000 Hz. The calibration curve shows a linear curve for the concentration range of 500 ppb to 5 ppm (tested at room temperature). As expected, the impedance dynamic response (impedance) increases with the increment of the NH3 concentration at the fixed frequency (1000 Hz) under the optimal conditions. The fitted linear regression equation to the calibration curve (𝑍𝑁𝐻3 = 6.339𝐶𝑁𝐻3[𝑝𝑝𝑚] + 243.1) provide the determination coefficient of 𝑅2 = 0.942. The linearity presented here is over much broader range of concentration than those presented for other polymer-based ammonia sensing methods while the limit of detection is lower than similar studies [192–195]. To show the potential selectively of the sensor, the values of the equivalent circuit for H2S and NH3 are normalized (i.e., 𝑋𝑖 − 𝑋𝑎𝑛𝑎𝑙𝑦𝑡𝑒/𝑋𝑖, in which 𝑋𝑖 is the value of the parameter of the equivalent circuit, and 𝑋𝑎𝑛𝑎𝑙𝑦𝑡𝑒 is the corresponding parameter at a certain target concentration and the results are shown in Figure 6C. Clearly, the 𝑅1 and 𝑅2 resistances as well as Warburg impedance (𝑍𝑤) are significantly different between H2S and NH3, showing the selectivity of the chemiresistor. 61 Figure 5.5 (A) Impedance spectra of the chemiresistor for NH3 and (B) The calibration curve of the sensor to NH3 (C) Radar diagram of the normalized values of the equivalent circuit for H2S and NH3 5.2.5 Prediction Model for mixture of hydrogen sulfide and ammonia As many biological samples contain both NH3 and H2S, it is vital to be able to detect them in the mixture. Figure 5.6A-D show the impedance spectra of the sensor expose to mixture solutions. To predict the response of the sensor to different mixtures, 11 samples (concentration of 5, 10, and 20 ppm NH3, and 2, 5, 10, and 20 ppm of H2S) were used to train a prediction model, and 12th sample was utilized to assess the accuracy of the model. The model consists of three general steps; feature extraction, nonlinear regression, and visualization. In the first step, the response of the sensor to each of the 11 samples is 62 analysed, and the most important features of these responses are extracted using principal component analysis (PCA) [196]. This approach extracts orthogonal principle components to minimize the unessential information. Then in the second step, the relationship between the extracted features and the concentration of H2S and NH3 in the samples is achieved using a nonlinear regression model which depicts the correlation between the response and prediction variables by minimizing the mean squared differences between the prediction of the model and test results. In the end, the features extracted in the first step are calculated for different mixture samples using equations achieved in the second step, and responses of the sensor for these samples are plotted based on these calculated features. Figure 5.6E shows some of the predicted responses. As it was expected, by increasing the concentration of NH3 in the mixture the abscissa and ordinate of the response peak increases, while the increment in the concentration of H2S has a reverse effect on the response. The variation from the baseline of the individual H2S (Figure 5.3) and NH3 (Figure 5.5) can be attributed to the formation of NH4SH. To validate the model, two methods are used; first, the nonlinear regression step is evaluated using the values of 𝑅2, adjusted 𝑅2, sum of squared errors (SSE), and root mean squared error (RMSE). The values for three different features are provided in Table 5-1. It is notable that the variation ranges for features are in the order of 100, so the values of SSE and RMSE suggest a well-fitted regression model. In the second method, the predicted response of the sensor for a mixture of 5ppm NH3 and 5ppm H2S is compared against the experimental results of the same mixture, shown in Figure 5.6F: there is a great agreement between 63 predicted results and experimental results, showing the efficiency of the prediction model that can be used to determine the concentration of each of analyte in the mixture Table 5-1 Indicators for evaluating the accuracy of the regression model R-squared Adj. R-Squared SSE RMSE Feature one 0.9959 0.9876 0.7721 0.8787 Feature two 0.9801 0.9404 3.707 1.925 Feature three 0.9235 0.7705 14.28 3.779 Figure 5.6 A-D) Impedance spectra of the chemiresistor for the mixture of H2S and NH3 at different concentration ratios [NH3: H2S ppm] E) Some predicted responses of the sensor F) Comparison of the predicted response of the sensor and experiment result for a specific mixture of 5 ppm of each H2S and NH3 64 6 Chapter 6: Conclusions and future work 6.1 Summary The main objective of this thesis was to develop new analytical techniques for the selective determination of different components in the liquid phase. In this regard, equivalent circuit, PDEIS, and PCA were developed to differentiate between the analytes of interest in the aqueous media (e.g. water, KCl solution, and standard electrolyte). A summary of the application of such techniques is presented hereunder: • In the first study, An electrochemical sensor based on the PMMA-GN nanocomposite film was developed and investigated upon separate exposure to four VOCs (ethanol, acetonitrile, acetone, and isopropanol) with a wide range of concentrations between 0.0025%v/v to 0.0875 %v/v for direct and point-of-care applications. In this study, a conventional off-chip potentiostat was utilized for the electrochemical study. EIS spectra provided an electrical fingerprint of each VOC and exhibited a differential response in an aqueous environment with the supporting electrolyte. Utilizing a three-element equivalent circuit, consisting of the charge transfer resistance, the resistance of the film, and constant phase element, it has been shown that the electrical properties of the PMMA-GN are highly affected by the presence of VOCs in the aqueous medium. The values of the fitted equivalent circuit were unique for each analyte and hence enables the identification of the analyte and its concentration. These results suggest that the PPMA-GN nanocomposite sensor forms a stable and selective sensing palate with the potential to be used for biomarker sensing related 65 to environmental health applications. As a future step, VOC cocktails will also be tested to demonstrate the potential and applicability of the sensor. • In another study, two inexpensive, disposable, and renewable electrochemical chemiresistors fabricated on the home-made pencil is investigated to study the potential of PDEIS for the selectivity toward trace metals. EIS has also been used to characterize and study the conductivity and charge transfer resistance of the thin film of PPy and PAni in the aqueous medium containing Cr (III), Cu (II) and Fe (III). The repulsion between the cationic metal ions and polymer was balanced by the chelating dopant, which generates the escalated background currents due to the polymer redox and charging reactions. In both electrodes, at various applied potentials, Fe (III) revealed the highest charge transfer and double layer capacitance due to its orbital configuration and paramagnetic property, both of which selected as the feature extraction for further selectivity. The results also demonstrate the ability of PDEIS to differentiate between the metal ions with very low interference. • In the last study, a facile, simple polypyrrole-based impedimetric sensor is represented to simultaneously detect the cocktail of hydrogen sulfide and ammonia in aqueous media. The direct electrochemical method in water removes the necessity of external coating, integrated cleaning pulse as well as regular high-temperature gas sensing approaches. The chemiresistor showed a high performance with the limit of detection of 500 ppb and a wide linear range from 0.5 to 7.5 ppm. The values of the equivalent circuit demonstrated the selectivity of the functional layer. Keeping H2S 66 and NH3 separate with no reaction, a trained PCA model was developed which was able to accurately predict the ppm amount of H2S and NH3 in the mixture. 6.2 Contribution to the filed • One of the major purposes of this thesis is introducing equivalent circuit in electrochemical sensors for better chemical analysis of the analyte and the sensing layer. Developing equivalent circuits for EIS results can provide additional features to the system of sensing, and consequently, can result in more sensitive and selective detection. • To the best of author’s knowledge, PDEIS has never been used for selective determination in electrochemical sensors. The concept of the proposed technique can be applied in further sensing platforms as a complementary tool for cyclic voltammetry and impedance spectroscopy. 6.3 Future work • A very important aspect of detection, particularly in the gas phase, is diffusion, in which the detection occurs based on the different diffusivity of the chemical. While it is a very well-known fact in gas sensors, diffusion-based studies in the liquid phase has not been conducted due to the low speed of diffusion in aqueous media. However, the fabrication of a microchannel with a short length can be an option to overcome the issue. 67 • Although electrochemical sensors are recognized as to be compact, the bulky size of potentiostat has always been a limitation for in situ detection. For example, while one of the purposes of H2S sensor is its capability in sewage and dirty media, it cannot be in pipelines because of the size of the potentiostat. Of note, some attempts are being made to miniaturize the device and develop “self-contained” sensors without external equipment, as has been comprehensively demonstrated in [182]. One suggestion is developing an on-chip potentiostat for electrochemical study. • In most biological and industrial samples, there exist a cocktail of compounds, and some of them react with each other as well as reacting with the sensing layer. In most of the experiments, gas chromatography is conducted before sensing. Although the interaction between H2S and NH3 was investigated in this study, the capability of electrochemical sensors for simultaneous detection requires further investigation. • In this study, the limit of detection in the range of 500 ppb was achieved. While this value is considered as a low limit of detection, more accurate sensors have been developed in the recent past in the range of 10 ppb (e.g. [197]). 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Thesis/Dissertation
eng
Mechanical Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Development of impedance-transduced chemiresistors for highly selective electrochemical detection in aqueous media
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