Xianping Chen
Molecular Modeling
in Design of Polyaniline for Polymer-based
Molecular modeling in design of polyaniline for polymer-based
carbon dioxide sensor
Xianping Chen 2 April, 2013
1. Moleculair modeleren is een magisch wonder voor het ontwerpen en evalueren van chemisch sensor materiaal, en is bedoeld voor creatieve en geïnformeerde mensen.
2. Gereedschap is gefixeerd, maar iemands brein is denkende.
3. Vooral de nieuwe nanostructuren van geleidende polymeren brengen verse lucht naar chemische sensoren met een groter oppervlakte en een betere verspreidbaarheid.
4. Inzicht in de temperatuurafhankelijkheid van de oplosbaarheidsparameter kunnen adequate informatie geven over het gevoeligheid probleem veroorzaakt door temperatuur veranderingen.
5. De verandering van lading drager dichtheid veroorzaakt de verandering in de geleiding van gas-gevoelige geleidende polymeren.
6. De sensor prestaties van geleidende polymeren zijn makkelijk te verbeteren door middel van het aanpassen van de chemische structuur en de chemische samenstelling.
7. Er zijn drie dingen welke een PhD studie makkelijker maken: een goede baas, een goed team en goed nadenken.
8. PhD = Geduld + Hardwerken + Dynamiek.
9. Politici maken eenvoudige problemen complex; de wetenschapper maakt complexe dingen eenvoudiger.
10. Als we weenden om het missen van de zonsondergang, zouden we alle stralende sterren missen.
Deze stellingen worden opponeerbaar en verdedigbaar geacht en zijn als zodanig goedgekeurd door de promotor, Prof. dr. Guoqi Zhang
accompanying the thesis
Molecular modeling in design of polyaniline for polymer-based
carbon dioxide sensor
Xianping Chen 2 April, 2013
1. Molecular modeling is a magic wonder in design and evaluation of chemical sensing materials, only for creative and knowledgeable people.
2. Tool is fixed, but ones’ brain is thinking.
3. The new nanostructures of conducting polymers particularly, provide fresh air to chemical sensors with their higher surface area and better dispersability.
4. Understanding the temperature dependency of the solubility parameter can provide adequate information about the sensitivity issue induced by temperature variations.
5. The change of charge carrier density causes the changes in the conductivity of the gas-sensitive conducting polymers.
6. The sensing performances of conducting polymers are easy to be improved by modifying the chemical structure and the chemical composition.
7. Three things that make PhD study easier: good boss, good team and good thinking.
8. PhD = Patience + Hardworking + Dynamism.
9. The politician makes the easy problem complex; the scientist makes the complex thing easier.
10. If we wept for missing the sunset, we would miss all the shining stars.
These propositions are considered opposable and defendable and as such have been approved by the supervisor, Prof. dr. Guoqi Zhang
for polymer-based carbon dioxide sensor
Proefschrift
ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,
op gezag van de Rector Magnificus Prof. ir. K.C.A.M. Luyben, voorzitter van het College voor Promoties,
in het openbaar te verdedigen op dinsdag 2 april 2013 om 15:00 uur
door
Xianping CHEN
Master of Science in Molecular Bioengineering, Dresden University of Technology, Dresden, Germany
Samenstelling promotiecommisie:
Rector Magnificus voorzitter
Prof. dr. ir. G.Q. Zhang Technische Universiteit Delft, promotor Prof. dr. F. van Keulen Technische Universiteit Delft
Prof. dr. P.J. French Technische Universiteit Delft
Prof. dr. C.P. Wong Georgia Institute of Technology, USA Prof. dr. B. Michel Fraunhofer, Germany
Prof. dr. C. Baile University of Greenwich, UK Dr. C.K.Y. Wong
Prof. dr. C.I.M. Beenakker
State Key Laboratory of Solid State Lighting, China Technische Universiteit Delft, reservelid
ISBN 978-94-91104-13-8
Copyright © 2013 by Xianping Chen
All rights reserved.
No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without prior permission of the author:
To my wife, Li Shen To my parents To my brothers and sisters To whom is curious
AA
ASummary
Conducting polymers are attractive chemical sensing materials due to their outstanding characteristics including low cost, room-temperature operations, easy device fabrication, high sensitivity and short response time. The new nanowires architecture, with high surface-to-volume ratio, makes possible the conducting polymers an ultra fast detection of chemical at low concentrations. Polymer-coated nanowires are thus the potential cost effective solution for the new generation gas sensors.
As a sensing material, the molecular design of the conducting polymer is utterly important. The conductive polymers can be tailored to fulfill the sensing requirement by its modifying functional groups in accordance to the applications. Molecular modeling which predicts the material properties of conductive polymers helps in the design of the sensor material. In this thesis, I present a molecular modeling approach to design and evaluate conducting polymer as chemical sensing material for polymer nanowire or polymer-coated nanowire carbon dioxide (CO2) sensors in greenhouse
application.
In order to provide an overview of the rapid progress in the application of chemical sensing materials with nanowire architecture, literature study on nanowire gas sensors has been presented in the Chapter 2. A comparison between the two basic approaches
(top-down and bottom-up) in the nanowire synthesis is given. The sensing principles and configurations of nanowire gas sensors with their relevant assembly technologies are summarized. Based on the review work, a polyaniline-coated nanowire field-effect transistor (NanoFET) is proposed for CO2 sensing system in greenhouse. This sensor
set combines the advantages of nanowire architecture, FET sensor configuration and conducting polymers.
A crucial part of any molecular simulation study is the choice of forcefields. In Chapter 3, we evaluate the validity of COMPASS and PCFF forcefields in predicting the physical and thermophysical properties of amorphous polymer emeraldine based polyaniline (EB–PANI). A combination of molecular mechanics (MM) and molecular dynamics (MD) analysis is employed to determine the polymer’s properties, including density (ρ) and solubility parameter (δ). The temperature dependence of specific volume (υ), non-bond energy (Enon-bond) and solubility parameters are used to estimate
the glass transition temperature (Tg). Comparing the simulation results with
experimental data, the accuracy of forcefields (COMPASS and PCFF) is elucidated. The COMPASS forcefield has been demonstrated as a better forcefield which provides a closer agreement with experiment data than the PCFF. Thus, the molecular modeling design of PANI for CO2 sensing is conducted by using the COMPASS forcefield.
For effective sensing, the dissolution of an analyte, as quantified as the solubility parameter δ, in the sensing materials is crucial. Understanding of the temperature dependence of solubility parameter can provide adequate information for the sensitivity issue induced as the temperature changes. In Chapter 4, I have developed a compact model to describe the solubility parameter change due to the temperature impacts. It is showing that in the working temperature range of greenhouse, the temperature impact on the solubility parameter is limited and can be neglected. To verify the accuracy of our calculation, two kind of analysis has been are performed: (i) the δ value at 298 K for EB–PANI is predicted and compared with the literature reported data; (ii) the Tg of
the polymer is determined from the δ–T curve and compared with the experimental value. The temperature dependence of solubility parameter of the EB-PANI has been determined by molecular modeling approach.
The sensing mechanism of the PANI for CO2 materials is based on protonic acid
doping. Molecular modeling of the sensing mechanism can offer useful information for the sensitivity and the selectivity of PANI. In Chapter 5, a compact model has been developed to describe the protonic acid doping of PANI with reasonable accuracy. The atomistic model is developed by using a statistical thermodynamic analysis method. The molecular modeling method is comprised of three key steps: (i) developing the atomistic models; (ii) defining the doing criteria; and (iii) simulating the protonic acid doping. By using the molecular model, the relationships including pKa/pH and doping
percentage/pH are established. The computed results compare favorably with the reported experimental data.
The change of charge carrier density causes the changes in the conductivity of the gas-sensitive conducting polymers. Thus, the relationship between macroscopic conductivity and charge carrier density is very useful in the design and evaluation of PANI as chemical sensing materials. In Chapter 6, by using the molecular model derived from Chapter 5, the relationships include the charge carrier density/pH and the conductivity/charge carrier density of EB-PANI are established properly. It is to find that the conductivity has an exponential function relationship with the charge carrier density [σ = (A*n)a] in PANI. Using the computing relationship of conductivity/charge carrier density, the sensitivity of EB-PANI and its derivative K-SPANI for the detection of HCl is evaluated. The finding shows that by introducing function groups (–SO3K),
the sensitivity of K-SPANI is greatly improved by two times. Thus the conducting polymer K-SPANI is a good candidate for acidic gas sensing, such as HCl, H2S, or CO2
in high humidity conditions.
With the fundamental knowledge established in Chapters 3-6, the molecular design of PANI for greenhouse CO2 gas sensing can be achieved. Chapter 7 investigates the
effect of functional group on the working range of polyaniline sensors for CO2 in
agriculture industry. The humidity, temprature and the concentration of CO2 in the
tightly clad greenhouses have been considered in the molecular model. The work compares the response of the pure EB, the polymer mixture of EB-PANI and undoped sodium sulfonated polyaniline (NaSPANI) with sulfur to nitrogen ratio (S/N) of 0.6, 0.5
and 0.4 to CO2. Under the working condition in a greenhouse, the working range of
NaSPANI has been estimated as ~ [102- 104] ppm which demonstrates it is a good candidate for CO2 detection in agricultural industry. In considering the synthetic
difficulty, I propose the conducting polymer NaSPANI (S/N = 0.5) is a good candidate for agricultural CO2 sensing.
In summary, a molecular modeling method which helps in the design and evaluation of conductive polymers for carbon dioxide sensing in greenhouses has been established. This thesis work contributes at use of computational approaches in designing and optimizing chemical sensing materials for various applications.
A
Samenvatting
Geleidende polymeren zijn een aantrekkelijk chemisch detectie materiaal als gevolg van de uitstekende eigenschappen zoals: lage kostprijs, kamertemperatuur werking, eenvoudige toepassing in apparaat fabricage, hoge gevoeligheid en korte responsie tijd. De nieuwe nanodraad architectuur, met een hoge oppervlakte tot volume ratio, maakt ultra snelle detectie van lage concentratie chemicaliën mogelijk. Nanodraden met een geleidende polymeren coating zijn daarom een potentiele kost effectieve oplossing voor een nieuwe generatie gassensoren.
Het moleculaire ontwerp van het geleidende polymeer is zeer belangrijk voor sensor toepassingen. Het geleidende polymeer kan worden afgesteld doormiddel van aanpassingen aan de functionele groepen om aan de eisen van de sensor toepassing te voldoen. Het moleculaire modelleren kan materiaal eigenschappen voorspellen van geleidende polymeren en kan bijdragen in het ontwerp van het sensor materiaal. In dit proefschrift wordt een moleculaire modelleringsbenadering gepresenteerd en een geleidend polymeer wordt geëvalueerd als een chemisch sensor materiaal voor polymeren nanodraden of polymeer gecoate nanodraad carbon dioxide (CO2) sensoren
Een literatuur overzicht van de snelle ontwikkelingen op het gebied van materialen voor chemische sensoren met een nanodraad architectuur wordt gegeven in hoofdstuk 2. Een vergelijking tussen twee standaard benaderingen (top-down en bottom-up) in de nanodraad synthese wordt gegeven. Het sensor principe en de configuratie van nanodraad gassensoren met de relevante assemblage technieken worden samengevat. Op basis van het literatuur onderzoek, wordt een polyaniline-gecoate nanodraad veld-effect transistor (NanoFET) voorgesteld voor CO2 sensor systemen voor broeikas
toepassingen. De sensor assemblage combineert de voordelen van nanodraad architectuur, FET sensor configuratie en geleidende polymeren.
Een belangrijk onderdeel van elk moleculaire simulatie onderzoek is de keuze van krachtvelden. In hoofdstuk 3, evalueren wij de geldigheid van COMPASS en PCFF krachtvelden in het voorspellen van fysische en thermo-fysische eigenschappen van amorfe polymeer emeraldine gebaseerde polyaniline (EB-PANI). Een combinatie van moleculaire mechanica (MM) en moleculaire dynamica (MD) analyse wordt gebruikt voor het bepalen van de eigenschappen van het polymeer met betrekking tot de dichtheid (ρ) en de oplosbaarheid (δ). De temperatuur eigenschappen van specifieke volume (υ), niet-gebonden energie (Enon-bond) en oplosbaarheid parameters worden
gebruikt voor het benaderen van de glas transitie temperatuur (Tg). Na de vergelijking
tussen de simulatie resultaten en de experimentele data, wordt de nauwkeurigheid van de krachvelden (COMSOL en PCFF) opgehelderd. Het COMPASS krachveld toont een betere overeenkomst met de experimentele data dan het PCFF krachveld en wordt daarom gebruikt in het moleculaire modellering ontwerp van PANI voor CO2 gas
sensoren.
Voor het nauwkeurig detecteren, is de ontbinding van een analyt, gekwantificeerd als de oplossingsparameter δ, in het sensor materiaal cruciaal. Het begrijpen van de temperatuur afhankelijkheid van de oplossingsparameter kan informatie geven over de gevoeligheidsproblemen veroorzaakt door temperatuur variaties. In hoofdstuk 4, heb ik een compact model ontwikkeld voor het beschrijven van de oplossingsparameter variatie als gevolg van de temperatuur veranderingen. Het laat zien dat in het temperatuur werkgebied van broeikassen, de temperatuur invloed van de
oplossingsparameter is gelimiteerd en kan worden verwaarloosd. Om de nauwkeurigheid de oplossing te verifiëren, werden twee analyses uitgevoerd: (i) de δ waarde van EB-PANI rond 298 K werd voorspeld en vergeleken met de literatuur waarden; (ii) de Tg van het polymeer werd bepaald van de δ –T curve en vergeleken met
de experimentele waarden. De temperatuur afhankelijkheid van de oplossingsparameter van de EB-PANI werd bepaald door de moleculaire modelleringsbenadering.
Het sensor mechanisme van de PANI voor CO2 materialen is gebaseerd op
protonische zuur doping. Moleculaire modellering van de sensor mechanismen kan nuttige informatie leveren voor de gevoeligheid en selectiviteit van PANI. In hoofdstuk 5 wordt een compact model gegeven voor het beschrijven van het protonische zuur-doping proces van PANI met redelijke nauwkeurigheid. Het atomistische model is ontwikkeld met behulp van de statistische thermodynamische analyse methode. De moleculaire modelleringsmethode bestaat uit drie stappen: (i) ontwikkelen van de atomaire modellen; (ii) definiëren van de criteria; en (iii) simulatie van het protonische zuur dopen. Met behulp van het moleculaire model, worden de relaties pKa/pH en het
doping percentage/pH bepaald. De berekende resultaten komen goed overeen met gepubliceerde experimentele waarden.
De verandering van lading drager dichtheid veroorzaakt veranderingen in de geleiding van de gas-gevoelige geleidende polymeren. De relatie tussen de macroscopische geleiding en lading drager dichtheid is erg nuttig voor het ontwerp en de evaluatie van PANI als een chemisch sensor materiaal. In hoofdstuk 6 wordt met behulp van het moleculaire model van hoofdstuk 5 de relatie tussen de lading drager dichtheid/pH en de geleiding/lading drager dichtheid van EB-PANI bepaald. Er wordt waargenomen dat de geleiding een exponentiele functie relatie heeft met de lading drager dichtheid [σ = (A*n)a] in PANI. Met behulp van de berekende relatie van geleiding/lading drager dichtheid, wordt de gevoeligheid van EB-PANI en zijn afgeleide K-SPANI voor de detectie van HCL geëvalueerd. De resultaten laten zien dat de introductie van functionele groepen (–SO3K), de gevoeligheid van K-SPANI
zure gas detectie zoals HCl, H2S of CO2 in omgevingen met een hoge
vochtigheidsgraad.
Met de fundamentele kennis van hoofdstuk 3-6 kan het moleculaire ontwerp van PANI voor broeikas CO2 gas detectie worden bewerkstelligd. In hoofdstuk 7 wordt het
effect van de functionele groep op het werkgebied van polyaniline sensoren voor CO2
in de landbouw industrie onderzocht. Met de vochtigheid, de temperatuur en de concentratie van CO2 in de broeikassen werd rekening gehouden in het moleculaire
model. Het werk vergelijkt de responsie van de pure EB, het polymeer mengsel van EB-PANI en ongedoopte natrium gesulfoneerde polyaniline (NaSPANI) met zwavel tot stikstof ratio (S/N) van 0.6, 0.5 en 0.4 tot CO2. Het werkgebied van NaSPANI in
broeikassen wordt geschat op ~ [102- 104] ppm, dit toont aan dat het een goede kandidaat is voor CO2 detectie in de landbouw industrie. Rekening houdende met de
synthetische moeilijkheden, stel ik voor dat het geleidende polymeer NaSPANI (S/N = 0.5) een goede kandidaat is voor landbouw CO2 gas detectie.
Samenvattend, een moleculaire modelleringsmethode, welke helpt met het ontwerp en de evaluatie van geleidende polymeren voor koolstofdioxide detectie in broeikassen is ontwikkeld. Dit proefschrift draagt bij aan het gebruik van computationele benaderingen in het ontwerp en de optimalisatie van chemische detectie materialen voor verschillende toepassingen.
A
Contents
Summary...I
Samenvatting ...V
Chapter 1 Introduction... 1
1.1 Background ...11.1.1 Conducting polymer gas sensors...3
1.1.2 Sensing principle...4
1.1.3 Molecular modeling ...5
1.2 Research objectives...6
1.3 Outline of thesis ...10
Chapter 2
Nanowire-based gas sensors ... 13
2.1 Introduction...13
2.2 Nanowire synthesis and nanofabrication ...14
2.2.1 Top-down versus bottom-up...15
2.2.2 Top-down nanofabrication approach based on iterative thermal size reduction ...18
2.3.1 Metallic nanowires...20
2.3.1.1 Adsorbate effect on conductance quantization in metallic nanowires ..20
2.3.1.2 Metal nanowire gas sensors...21
2.3.2 Semiconducting nanowires...23
2.3.2.1 Adsorbate effect on conductance in semiconducting nanowires...23
2.3.2.2 Metal-oxide nanowire gas sensors ...25
2.3.3 Silicon nanowire gas sensors ...25
2.3.4. Conducting polymer nanowire gas sensors ...27
2.4 Configurations and sensing principles of different sensors ...28
2.4.1 Nanowire based resistors ...28
2.4.2 Nanowire field-effect sensors ...30
2.4.3 Optical nanowire sensors...32
2.4.4 Gas ionization sensors based on nanowires...35
2.4.5 Quartz crystal microbalance sensors using nanowires ...36
2.4.6 Surface acoustic wave sensors using nanowires...38
2.4.7 Self-powered nanowire nanosensors ...39
2.5 Towards “more than moore”...40
2.6 Polyaniline-coated nanowire CO2 sensor...42
2.7 Discussion and conclusion ...43
2.8 Prospective...45
Chapter 3 Forcefield validation... 47
3.1 Introduction...47
3.2 Molecular models and simulation ...50
3.3.1 Building amorphous polymer model ...50
3.3.2 Simulation...51
3. 3 Results and Discussion...53
3.3.1 Model validation...53
3.3.2 Prediction of glass transition temperature ...55
3.3.3 Temperature dependency on non-bond energy...57
Chapter 4 Temperature effect on solubility parameters... 60
4.1 Introduction...60
4.2 Computational methodology...64
4.3 Molecular modeling details...65
4.4.1 Building the amorphous polymer system ...66
4.4.2 Geometry optimization and equilibration of polymer system ...68
4.4.2 Glass-rubber transition of polymer ...69
4.4 Results and discussion ...69
4.4.1 Validation of model in predicting solubility parameter...69
4.4.2 Temperature dependence of specific volume and cohesive energy...70
4.4.3 Temperature effects on the cohesive energy components related to solubility parameters...72
4.4.4 Temperature dependence of solubility parameters ...73
4.5 Conclusions...75
Chapter 5 Model of sensing mechanism of polyaniline ... 76
5.1 Introduction...76
5.2 Development of molecular models ...79
5.3 Molecular models and simulation ...82
5.3.1 Molecular models ...82
5.3.2 Simulation protocol for protonic acid doping...83
5.4 Results and discussion ...85
5.5.1 Model validation...85
5.5.2 pH dependence of pKa...87
5.5.3 pH dependence of doping percentage...88
5.5.4 Evaluation and selection of chemical sensing materials...89
5.5 Conclusions...90
Chapter 6 Molecular model for the charge carrier density dependence
of conductivity of polyaniline... 92
6.2. Models and computational methodology ...95
6.2.1. Conducting polymer gas sensors ...95
6.2.2. Molecular model construction ...96
6.2.3. Computing the charge carrier density dependence of conductivity...97
6.2.4. Evaluating the sensitivity of polyaniline ...99
6.3. Results and discussion ...101
6.3.1. Model validation...101
6.3.2. Relationship of charge carrier density/pH ...101
6.3.3. Relationship of conductivity/charge carrier density ...102
6.3.4. Evaluation of the sensitivity of EB-PANI and K-SPANI to HCl ...104
6.4. Conclusions...105
Chapter 7 Impact of functional group of polyaniline on CO
2sensing106
7.1 Introduction...1067.2 Models and simulations ...109
7.2.1 Sensing principle ...109
7.2.2 Molecular model construction ...110
7.2.3 Fixed pressure simulation ...112
7.2.4 Fixed loading simulation ...112
7.3 Results and discussion ...113
7.3.1 Structural relaxation and model validation...113
7.3.2. Loading number calculation ...114
7.3.3. Numerical analysis of polymer-analyte interaction ...115
7.3.4 Model benchmarking with relative solubility...116
7.3.5 Dependence of conductivity of polymer on CO2 concentration ...116
7.4 Conclusions...119
Chapter 8 Conclusions and perspectives ... 120
8.1 Conclusions...120
Bibliography ... 125
Publications ... 149
Acknowledgments ... 151
C
HAPTER
1
Introduction
1.1 Background
The detection of chemical species is central to many areas of healthcare, lifestyle, environmental sciences and homeland security, ranging from uncovering and diagnosing disease to the discovery and screening of new drugs and to giving off early warning against environmental agents [1]. Hence, the development of reliable and inexpensive devices that enable direct, high sensitive/selective, and rapid analysis of these species could impact mankind to have a more healthy life. Central to detection is the signal transduction and wireless logistics associated with selective recognition of the chemical species of interest.
Nanostructures, such as nanowires [2-7] and nanotubes [2, 3] offer new and unique sensing opportunities. Nanowires have been defined as wires with at least one spatial dimension in the range of 1-100 nm [2]. As a result, these new types of architectures - the nanowires - exhibit a variety of interesting and fascinating properties, and have been functioning as building blocks for nanoscale electronics, nano-optics, and especially for nanosensing technology [4, 5]. The dimensions of these nanostructures are comparable to the sizes of the biological and chemical species being sensed, and thus intuitively
represent excellent primary transducers for recognition phenomena at the surface of the nanostructures. This makes nanowire sensors are recognised to be a next generation building block for ultra-fast chemical sensing systems, such as e-nose and e-tongue. A gas sensor that relies on a single nanowire for its extremely high sensitivity has been created by a team of scientists led by Zhonglin Wang using nanowires of zinc oxide (ZnO) positioned across a pair of platinum electrodes (Fig. 1-1) [6]. Application of the nanowire gas sensor system depends crucially on the reproducibility and costs per device. Polymer-coated nanowire sensors could be a good candidate and satisfied for the requirement of application.
The open world market for non-military sensors grew from EUR 81.6 billion in 2006 to EUR 119.4 billion in 2011 and can be expected to grow to EUR 184.1 billion until 2016, according to the new 2012 world report just published by Intechno consulting at Basel, Switzerland. Note that an average annual growth rate 7.9% between 2006 and 2011, and 9.0% between 2011 and 2016. The average annual growth rate for the entire period covered is 8.5% [7]. Another new category in this report is that at 2016, the share of sensors measuring chemical and biological properties in the world market for sensors was 10.9% [7]. This is a very exciting new for all the researchers engaged in this study field.
1.1.1 Conducting polymer gas sensors
Since the electrical conductivity of conducting polymers, such as polypyrrole (PPY), polyaniline (PANI), polyacetylene (PA) and their derivatives, is affected by exposure to various gases [1, 8], there are more and more attentions have been attracted to the investigation of these materials as gas sensors [9-11]. Conducting polymers are attractive materials for gas sensor applications because a wide range of such polymers are already known [9, 12-14] and the chemical and physical properties of conducting polymers can be facilely adjusted by introducing different substituents, or copolymerizing with different monomers. In addition, the materials are sensitive to a wide range of gases and vapours at room temperature [9, 10] and can be deposited onto microelectronic structures under controlled conditions by electrochemical polymerisation across the gap between two microband electrodes [11, 12]. Conducting polymers also have attractive features such as mechanical flexibility, ease of processing, modifiable electrical conductivity and a lower power and require simpler electronic setups [13]. Among conducting polymers, PANI has received widespread attention due to its simple and reversible doping/dedoping chemistry, stable electrical conduction mechanism, and high environmental stability [4]. It has been widely used to detect a variety of toxic gases such as acidic gases (HCl, CO, CO2, H2S and NO2) [1, 6, 9] or
basic gases (NH3) [14, 15].
Carbon dioxide (CO2) is an essential component for photosynthesis. The ambient
CO2 concentrations will directly affect the growing period, crop quality and yield. The
ability to monitor the CO2 levels in air in the closed environment is important to
greenhouses (Fig. 1-2). The tightly clad greenhouses need reliable and inexpensive sensor devices that enable direct, high sensitive/selective and rapid analysis of the target species at room temperature and high humidity conditions. At present, the metal oxide based sensors, which are the most commonly used commercially sensors, cannot achieve such requirements [11]. To fulfill this, we are developing the CO2 sensor using
the conducting polymers, specifically emeraldine base polyaniline (EB–PANI) and its derivatives such as non-doped sodium sulfated EB–PANI (NaSPAN) [1, 6, 9, 11, 20, 21].
Fig. 1-2: Young tomatoes in an industrial-sized greenhouse in The Netherlands.
1.1.2 Sensing principle
The sensing mechanism of PANI for CO2 proposed by Ogura and coworkers [16]
consists of two key steps [4]: (i) CO2 reacts with H2O to form carbonic acid (H2CO3)
which dissociates into H+ and HCO3 –
, and (ii) protonic acid doping of the insulated PANI and form the conductive counterpart. Fig. 1-3 gives an example, a nanowire field-effect transistor (NanoFET) CO2 sensor using a single PANI coated nanowire as
active sensing element. After exposing the vapor of analyte, the PANI can interact with the analyte molecules, which cause its resistance change. The NanoFET will transfer the resistance change to other detectable physical signal–current. The increase in CO2
concentration results in the changes of the doping degree which finally results in reducing the resistance of the PANI-coated nanowire and thereby the concentration of CO2 can be measured. Understanding the sensing properties of polyaniline depends on
the reversible binding of the target molecule with the sensing film and the minimal interaction between sensing material and the chemical species chemical species which may be present in the sensed environment, including both targeted analyte and background species such as oxygen, carbon dioxide, water, etc. Therefore, a
molecular-level understanding of the sensing mechanism can provide adequate information for the sensitivity and selectivity issues induced by analyte, moisture and temperature changes.
Fig. 1-3: Schematic of sensing principle of PANI coated NanoFET sensor response to
carbon dioxide (CO2).
1.1.3 Molecular modeling
Molecular modeling encompasses all theoretical methods and computational techniques used to model or mimic the behaviour of molecules. The techniques are used in the fields of computational chemistry, drug design, computational biology and materials science for studying molecular systems ranging from small chemical systems to large biological molecules and material assemblies. Materials for gas sensors have been widely investigated using molecular modeling approaches in the last two decades [4]. Methods developed in molecular modeling approaches, such as molecular mechanics (MM), molecular dynamics (MD), quantum mechanical (QM), and atomistic techniques, have been used to evaluate and select candidate materials as well as to provide inputs to design, synthesis and evaluation of new chemical sensing materials [4]. Understanding the sensing properties of chemical sensing materials depends on understanding the
interactions between sensing material and the target molecules which is present in the sensed environment. An approach for selection of chemical sensing materials based on computational approaches will help not only in providing a fundamental understanding of the polymer-analyte interaction at molecular level, but also in setting protocols for optimising the sensor array with less extensive experimental testing [4]. Fig. 1-4 1-2 gives an example to investigate the physical interaction between polymers and CO2
molecules by MD simulation.
Fig. 1-4: Investigation of the interaction between polymer and CO2 molecules by MD.
1.2 Research objectives
The objective of the thesis is to achieve a molecular modeling methodology for the design and evaluation of PANI in developing highly sensitive and selective polymer-coated nanowire CO2 sensors for greenhouses. Materials for chemical and biological
sensing have been investigated using computational and computational-experimental approaches. This thesis presents our examples of computational approaches that have been developed and used successfully in designing and selecting conducting polymers for chemical sensing devices. The computational procedure used in this research includes the following main steps shown in Fig. 1-5.
Fig. 1-5: The main steps in the computational procedure used in this research.
According to the computational procedure (Fig. 1-5), there are six major tasks and each task can be regarded as an approach to answer one research question:
⇒ Task 1: Literature study to answer “Why use nanowires as gas sensors?”.
The high surface-to-volume ratio of the nanowire makes it possible to obtain ultra fast detection of chemical species at low concentrations. It leads to more and more attentions in the nanowire gas sensors fabricated from metals, metal-oxides, silicon (Si) and conducting polymers, and lots of related articles were published. Application of the nanowiresensor system depends crucially on the reproducibility and costs per device. Although nanowire sensors have been proved to be promising the advantage in the utilization, and especially commercialization, of these sensors have been relatively slow. Difficulties arise associated with the complex and expensive manufacturing techniques, such as
e-beam lithography, epitaxial growth of the nanowires etc. Also reliability, packaging and signal processing of these devices are cumbersome. Therefore we will pay special attention to deeply understanding of the nanotechnology and nanowire-based gas sensors. Finally, a polyaniline-coated nanowire gas sensor set will be proposed for CO2 sensing in office buildings and greenhouses.
⇒ Task 2: Forcefield validation to answer “Which forcefield is better to our study?”.
An accurate selection of forcefields is a key importance in enabling good predictions of the molecular interactions and the material properties. The forcefield describes approximately the potential energy hypersurface on which the atomic nuclei move. The class I forcefield “polymer-consistent forcefield (PCFF)” and the class II forcefield “condensed-phase optimised molecular potentials for atomistic simulation studies (COPASS)” will be compared. The calculated results were validated by the prediction of the physical (density, ρ and solubility parameters, δ) and thermal (glass transition temperature, Tg) properties
of polyaniline (Fig. 1-6).
⇒ Task 3: Modeling study of temperature effect on solubility parameter to answer “How to use forcefield based modeling to predict the temperature effect on solubility parameter of polymers?”.
In sensor applications solubility parameter, δ can provide insights to predict the swelling changes of polymers in the presence of volatile chemical compounds. Furthermore, it is useful to optimize processing conditions, as well as select the suitable solvent or the optimum solvents combinations in coatings industry. The temperature dependence behavior of δ for the polymer will be modeled by running molecular dynamics (MD) simulation with the commercial forcefield class II “COMPASS” in a widely temperature range. The effects of temperature on the cohesive energy (Ucoh) and cohesive energy density (ECED) will also be
investigated by MD simulation with the commercial forcefield class II “COMPASS”.
⇒ Task 4: Molecular model for the sensing mechanism to answer “How to describe the sensing mechanism by using forcefield based molecular model?”.
A molecular-level understanding of the sensing mechanism (see section 1.1.2 and Fig. 1-3) can provide adequate information for the sensitivity issue of conducting polymer gas sensors. The molecular-scaled sensing mechanism of the conducting polymer gas sensor and the target gas molecule will be modelled by the molecular modeling approach. A molecular model will be developed to describe the sensing mechanism of polyaniline. The commercial forcefield class II “COMPASS” will be used for the construction of polymer and protonic acid molecules. The radial distribution functions of doped emeraldine salt and the relationships including pKa/pH and doping percentage/pH, will be computed and compared with the experimental data to validate the accuracy of the molecular model.
⇒ Task 5: Molecular model for the charge carrier density dependence of conductivity to answer “How to use using the molecular model developed from task 4 to establish the relationship between the macroscopic conductivity and the charge carrier density in gas-sensitive conducting polymers”.
For gas sensor application, the understanding of the mechanisms of charge conduction, by means of molecular modeling, will help not only in improving the sensing performance of conducting polymers but also in designing new conducting materials [1, 9, 23-25]. The molecular model developed from the task 5 will be used to study the mechanism of charge conduction in gas-sensitive conducting polymers. The relationships include the charge carrier density/pH and the conductivity/the charge carrier density of EB-PANI will be established. The roles that the charge carrier density play in affecting the conductivity and in the mechanism of charge conduction in disordered and amorphous conducting polymers will also be discussed. Furthermore, the use of the relationships of the conductivity/the charge carrier density for determining the sensitivity in design and selection of gas-sensitive conducting polymers will be addressed.
⇒ Task 6: Molecular modeling design of polyaniline to answer “What’s the optimized molecular structure of polyaniline for CO2 sensing?” .
It is well-known that EB-PANI is a pH dependent conducting polymer [4]. The linear pH dependence for detectable conductivity in EB-PANI is at a range of pH 2.0 to 4.0 [4]. Nevertheless, a conducting polymer which operates at near neutral pH range (pH 7.0 to 6.5) is needed for agriculture applications [6, 26, 27]. Thus, in order to improve the sensing properties of PANI for CO2 sensing, the
molecular structure of the polymer will be optimized using molecular modeling approach based on the previously study work of tasks 1–5.
1.3 Outline of thesis
This thesis has been organized into 8 chapters and each of chapter can be read independently. Most of the results addressed in the thesis are essentially new and have not been studied before. From chapter 2 to chapter 7, each of them is to solve a specific task. For giving a good overview of this thesis, I briefly outline of Chapter 2-8 in more detail:
Chapter 2 (to solve Task 1) views the recent process of the development of nanotechnology and nanowire-based gas sensors. The two basic approaches, the top-down and bottom-up, for synthesizing nanowires are compared. The conduction mechanisms, sensing performances, configurations, and sensing principles of different nanowire gas sensors and arrays are summarized and discussed. At the end of this chapter, and a polyaniline-coated nanowire sensor set, which combines the both advantages of nanowire architecture, FET sensor configuration and conducting polymers, will be proposed for CO2 sensing in office building and greenhouses
Chapter 3 (to solve Task 2) deals with the validation of forcefields in predicting the polymer properties of polyaniline. The choice of forcefields is very important in any molecular simulation study. In this chapter, validation of the forcefields COMPASS and PCFF is conducting by the prediction of the physical and thermal properties of polymers. The simulation results on density (ρ), solubility parameter (δ), and glass transition temperature (Tg) of polyaniline respectively predicted by COMPASS and
PCFF will compared with the experimental data, and the accuracy of the forcefields (COMPASS and PCFF) has been validated.
Chapter 4 (to solve Task 3) studies the temperature dependence of solubility parameters of amorphous polyaniline. A molecular modeling strategy is proposed to describe the temperature (T) dependence of solubility parameter (δ) for the amorphous polymer polyaniline which exhibit glass-rubber transition behavior.
Chapter 5 (to solve Task 4) describes the molecular model which is capable of representing the protonic acid doping of emeraldine base polyaniline. The doping process is modeled by a combined molecular mechanics and molecular dynamics simulation techniques. The radial distribution functions of doped emeraldine salt and the relationships including pKa/pH and doping percentage/pH, are computed and
compared with the experimental data.
Chapter 6 (to solve Task 5) probes into the relationship between macroscopic conductivity and charge carrier density in polyaniline (PANI) as chemical sensing materials. It was demonstrated that the conductivity in polyaniline depends on the
charge carrier density. The charge carrier density dependence behaviour of the conductivity was described as an exponential function σ = (An)a. The predicted relationship was verified by the previous study on the charge carrier density dependence of the mobility from the other research group. Using the computing relationship of conductivity/charge carrier density, the sensitivity of emeraldine base polyaniline (EB-PANI) and its derivative, potassium sulfonated polyaniline (K-SPANI) for the detection of HCl was evaluated. It was clearly seen that the sensitivity of K-SPANI was greatly improved about 2 orders of magnitude compared to EB-PANI. This simulation result was verified by the literature reported experimental results. The computational methodology used in this research can be used for determining the sensing properties in design and evaluation of chemical sensing materials.
Chapter 7 (to solve Task 6) develop a molecular modeling methodology to investigate the effect of functional group on the working range of polyaniline sensors for CO2 in agriculture industry. Doping plays the key role in the sensing mechanism of
conducting polymer sensors. The adsorption of CO2 and water, which governs the
production of protons and polymer solubility in water, is important for doping and thus a key property for gas sensing. The molecular model, which is capable of studying the interaction among the functionalized polyaniline, CO2 gas and water solvent, is
employed to study the adsorption. The loading number of adsorbates in the polymer systems at the fixed temperature and pressure is calculated. It indicates that NaSPANI can be used for agricultural CO2 detection.
Chapter 8 closes the thesis with conclusion and perspectives which can be seen as the summary of the research results, as well as some suggestions for the further study.
C
HAP TER
2
Nanowire-based gas sensors
2.1 Introduction
Nanowires have been defined as wires with at least one spatial dimension in the range of 1-100 nm [17-22]. These new types of architectures exhibit a variety of interesting and fascinating properties, and have been functioning as building blocks for nanosensing technology [23-28]. Although the basic gas sensing mechanism (adsorption and desorption of gas molecules) remains the same, compared to the conventional sensors based on flat films, the nanowire gas sensors and sensors arrays exhibit many inspiring characteristics: (i) Ultra sensitivity and fast response time. Due to their small size with high surface-to-volume ratio, a few gas molecules are sufficient to change the electrical properties of the sensing elements. This allows the detection of a very low concentration of gas within several seconds. Polymer single-nanowire optical sensors are used for humidity sensing with a response time of 30 ms and for NO2 and NH3 detection down to subparts-per-million level [29]. The response and
recovery time of ethanol sensor using indium-doped tin oxide nanowires is less than 2 seconds [30]. (ii) Higher selectivity and stability. With the development of nanowire gas sensors, the large arrays of macroscopic individual gas sensors will be replaced
with an “electronic nose (e-nose) embodied in a single device that integrates the sensing and signal processing functions in one chip [30-32, 34, 35, 42, 43]. E-nose is an array of nanowire gas sensors (e.g. nanowire based resistors and field-effect sensors) which respond when exposed to vapors [31]. Thus, the selectivity and stability of the gas sensor devices can be improved [34, 35, 42]. (iii) Light weight, low power consumption and wireless communication capability [32]. Nanowire sensors having minimize size, light weight and consume less power , are important for long range coverage [33]. With nanowires, advanced gas sensor and wireless communication capabilities can be realized, e.g. via distributed ad-hoc sensor networks, enabling long range guidance of all kinds of gas detection. (iv) Low-temperature operations [34, 35]. Very small amounts of gas can change the electrical characteristics of nanowires; this enables the sensors to work at lower-operating temperature. Single ZnO nanowires coated with Pt clusters by sputtering are shown to selectively detect hydrogen at room temperature. The single nanowires operate at extremely low power levels of 15-30 µW [35].
With all the above advantages, researchers show intensive interest in the development of nanowire gas sensors and the arrays, with many related articles published. This chapter provides an overview of the rapid progress on gas sensors using nanowires comprising metal oxide, conducting polymer, and semiconductors based on various sensing techniques. The comparison between the two basic approaches, top-down and bottom-up synthesis, of nanowires is given. Some interesting approaches in recent nanowires fabrication are discussed. The sensing principles and configurations of nanowire gas sensors with their relevant assembly technologies are summarized. Meanwhile, as a new exciting sensor types, the self-powered nanowire devices for gas detection are introduced and highlighted. Furthermore, the prospects of the scientific and technological challenges on gas sensors based on nanowires will be addressed.
2.2 Nanowire synthesis and nanofabrication
There are now many distinct methods in synthesizing nanowires. They are commonly classified into two categories [36-39], the bottom-up and top-down approaches.
Similarly, for the nanofabrication, the two approaches are still applied. Here, we review the advantages and disadvantages of those approaches. A new nanofabrication technique [40], based on iterative size reduction, to produce ordered, indefinitely long nanowire and nanotube arrays, is selected.
2.2.1 Top-down versus bottom-up
Top-down approach starts with patterns made on a large scale while reducing the lateral dimensions to the nanoscale. The most common top-down approach to fabrication involves optical and x-ray lithography, e-beam and ion-beam lithography, printing and imprinting, scanning probe lithography, etc. A key advantage of the top-down approach–as developed in the fabrication of integrated circuits–is that the parts are both patterned and built in place, so that no assembly step is needed [41]. The second advantage is that it is easier to obtain well-ordered structures, with a high homogeneity in nanowire diameters and lengths [42]. The challenge for all the top-down techniques is that, while they work well at the microscale (at millionths of a metre), it becomes increasingly difficult to implement in nanoscale dimensions [39]. Furthermore, they involve planar techniques, which mean that the structures are created by the addition and subtraction of patterned layers (deposition and etching). Arbitrary three-dimensional objects are thus difficult to construct. Although lithographic techniques are commercially viable and widely utilized in manufacturing, these top-down approaches suffer from high equipment costs, particularly when fabricating high-resolution structures [43].
On the contrary, the bottom-up approach begins with individual atoms and molecules and builds up the desired nanostructures, in some cases through smart use of self-assembly [38, 39, 42]. Inspiration of the bottom-up approaches comes from biological systems [44], where nature has harnessed chemical forces to create essentially all the structures needed by life. Most of the synthesis techniques are based on bottom-up approach. There are more than ten distinct bottom-up methods includes vapor-liquid-solid (VLS) growth, chemical vapour deposition (CVD), sol-gel processing, plasma or flame spraying synthesis, laser pyrolysis, atomic or molecular
condensation, layer-by-layer self assembly, molecular self assembly, coating and growth, direct assembly, etc. The significant advantage of bottom-up approaches is that they can be used to generate structures with dimensions ranging from angstroms to hundreds of nanometers [49-51, 54, 57]. Another advantage is that nanowires can be assembled on nearly any type of surface, including those that are typically not compatible with standard CMOS processing, such as flexible plastic substrates [45-47]. The third advantage is that sequential patterning and assembly steps enable fabrication of distinct nanowire devices on a substrate [48]. However, construction of hierarchic structures only from bottom–up self-assembling processes could be very tough [43, 49]. With the current state of self-assembly science, a successful outcome cannot yet be obtained by sole reliance on the bottom–up concept. Positioning of assembled patterns on specific locations is particularly difficult in fabricating the required structures in practical applications [43, 49]. So, which approach is better?
Fig. 2-1: Future of top-down and bottom-up approaches: (a) Photo of schematics microelectronics, (b) Image of nanoelectronics and (c) Artist’s impression of an integrated light sensor circuit based on nanowire arrays [50].
The answer as of now is that we need both approaches for many of the applications related to nanowires from a scientific point of view [39, 42]. Top-down approaches are good for producing structures with long-range order and in making macroscopic connections (Fig. 2-1a), while bottom-up approaches are best suited for assembly and establishing short-range order at nanoscale dimensions (Fig. 2-1b). What is the future? The integration of top-down and bottom-up techniques is expected to eventually provide the best combination of tools for nanofabrication as shown in Fig. 2-1. More and more research works has illustrated that the combination of top-down and bottom-up methods can enable rapid development of advanced applications [49, 55, 64-67]. Examples of such a combination have been reported to produce cost-effective nanostructures [51]. Meanwhile, scientists [50] have created the world’s first all-integrated sensor circuit based on nanowire arrays and combining light sensors with electronics made from different crystalline materials (Fig. 2-1c) by using the combination of CVD, VLS, printing and photolithography techniques. Their method can be used to reproduce numerous devices with high uniformity [50, 52]. Furthermore, a line-patterned breath figure film is achieved using a photo-crosslinkable small molecule through a novel dual-patterning process that combines a breath-figure technique (bottom-up) and photolithography (top-down) as shown in Fig. 2-2 [43].
Fig. 2-2: Dual-patterned honeycomb lines from a combination of bottom-up and top-down lithography [43].
2.2.2 Top-down nanofabrication approach based on iterative thermal
size reduction
Fig. 2-3: A new top-down nanofabrication scheme, based on iterative size reduction, to produces indefinitely long nanostructures [40]: (a) A macroscopic multimaterial rod is reduced to ordered arrays of nanowires by the multistep iterative thermal size reduction process and (b) Ultralong semiconducting core/piezoelectric shell nanowire.
Recently, Bayindir Research Group at Bilkent University first successfully produced well-ordered, globally oriented, indefinitely long nanowire and nanotube arrays with different materials using a new top-down approach [40]. The new technique involves a multistep iterative thermal size reduction process inspired from composite-fibre drawing from polymer reels as illustrated in Fig. 2-3a [40]. By using the new top-down nanofabrication scheme, a macroscopic multimaterial rod can be reduced to ordered arrays of nanowires in a protective polymer matrix in successive steps. Each step starts with structures obtained from a previous step, resulting in geometrical size reduction and increment in wire number and length. The total number of nanowires and their ultimate size distribution is determined by the number of packed fibres after each step, the total number of iterative steps and the reduction factor as shown in Fig. 2-3a. In this way, they have produced millions of kilometre-long semiconducting, piezoelectric and polymer nanowires (Fig. 2-3b) with sub-10nm diameter and an aspect ratio of 1011 [40]. The results are kilometer-long nanowires–a novel approach for nanowire fabrication.
In addition, some other new methods are also used to synthesize nanowires and fabrication such as directed electrochemical nanowire assembly [69-71] and assembly free growth-in-place e approach [53].
2.3 Conduction mechanism and sensing performances
It is well established that the electrical conductivity of conducting materials, such as metals [5, 54-57], metal-oxides [77-79], silicon (Si) [7, 38, 42, 80, 81] and conducting polymers [1, 6, 20, 40, 82], with nanowire structure is affected by exposure to various organic and inorganic gases [17, 25]. This has led to the investigation, by a lot of research groups, of the new type of nanostructures as building blocks for gas sensors. According to the conduction mechanisms, the gas-sensitive nanowires are divided into two categories: metallic nanowires and semiconducting nanowires.
2.3.1 Metallic nanowires
2.3.1.1 Adsorbate effect on conductance quantization in metallic nanowires
It has been found for many years that the electrical conductivity of metals decreases upon adsorption of atoms and molecules because of the scattering of the conducting electrons by the adsorbates [5, 56-58]. When the electron mean free path is much smaller than the dimension of the metals, the adsorbate effect is largely limited to nonballistic electron transport. By using the concept of surface resistivity, Persson established a simple relationship to explain the change in the resistivity of thin metallic films upon adsorption of atoms and molecules [84-87]. The adsorbate-induced conductance change (∆G) and the density of states of the adsorbed molecules ρa(εF) at
the Fermi energy of the conductor, is described as [59, 60]
(((( ))))
a F G G d ρ ε ρ ε ρ ε ρ ε ΓΓΓΓ ∆∆∆∆ ∝ −∝ −∝ −∝ − (2.1) where G is the conductance of metal nanowire, d is the thickness of the metal film, andΓ the width of the density of states ρa(εF). Since different molecules have different ρa(εF),
the conductance change should be specific for each adsorbate, which has been confirmed for classical conductors [61]. From Eq. (2.1) it can be found that the sensitivity (∆G/G) of sensors is inversely proportional to the thickness of the metal film. So, in terms of sensor applications, thinner films mean higher sensitivity. In the case of metal nanowires, the dependence of the sensitivity of sensors on nanowire thickness can be simplified by a geometric surface-to-volume ratio [61]
2 4 ( ) 2 G S DL D G V D L ππππ ππππ ∆∆∆∆ ∝ =∝∝∝ === ==== (2.2) where D and L are the diameter and length of metal nanowire, respectively, π is the ratio of the circumference of a circle to its diameter. Thus, the sensitivity of nanowire based gas sensors increases as the diameter of the nanowire decreases, agreeing well with the conclusion obtained from thin metallic films [59].
However, when the wire width is decreased to the atomic scale (a few tens of nanometers), the conductance of the nanowires has been observed to vary in a stepwise fashion in which the steps occur at the integer values of conductance quantum, G0 =
2e2/h [87-89]. Then the conductance of metal nanowires can be strongly affected by the electronic coupling of adsorbates, which will have a significant change in resistance. In 1998, Sha and Tao have studied the conductance quantization in metallic nanowires upon adsorption of molecules with different adsorption strengths [62]. They revealed that the conductance still changed in a step-wise fashion even in the presence of strong adsorption, and the average sharpness, length, and number of the conductance steps remained unchanged. However, the step positions deviate significantly from the integer values of the conductance quantum, G0. The shift in the conductance may be attributed
to the scattering of the conduction electrons by the adsorbates, evidence shows that the adsorbates also affect conductance by changing the atomic configurations of the nanowires [62]. The sensitive dependence of the quantized conductance on molecular adsorption has been used for the direct detection of biological and chemical species [8, 18, 73-76].
2.3.1.2 Metal nanowire gas sensors
Ever since Tao and co-workers demonstrated that the conductivity of gold (Au) nanowires changes upon exposure to gas molecules capable of chemisorbing to Au surfaces, gas sensors based on precious metal nanowires, such as silver (Ag) [8, 73], Au [5], palladium (Pd) [56, 57], have been studied and developed. Penner and co-workers first reported hydrogen (H2) sensor based on Pd mesowire arrays [57]. The nanowire H2
sensor consists of up to 100 Pd “mesowire” arrays which were prepared by electrodeposition onto graphite surfaces and were transferred onto a cyanoacrylate film (see top left corner of Fig. 2-4) [57, 63]. Exposure to H2 with over a concentration range
from 2 to 10%, a rapid (less than 75 milliseconds) reversible increase in the current of the array was observed (see bottom of Fig. 2-4) [57, 63]. The sensing mechanism was based on the closing of nanoscopic gaps or (break junctions) in wires caused by the dilation of palladium grains undergoing H2 absorption, as shown in the top right corner
of Fig. 2-4 [57]. These nanoscopic gaps were opened again when the H2 swollen Pd
grains in each mesowire returned to their equilibrium dimensions in the absence of hydrogen [57].
Fig. 2-4: The Pd nanowire H2 sensors and its sensing mechanism [57].
Penner and co-workers also demonstrated that upon exposure to ammonia (NH3)
vapor, the ensembles of Ag mesowires prepared by electrochemical step edge decoration showed a resistance increase, ∆R/Ro, that was large (up to 10,000%), fast (<5
s), and reversible [54]. Atomic force microscopy analysis of individual Ag wires suggests that the increased resistance induced by NH3 exposure was concentrated at a
minority (<10%) of the interparticle boundaries present along the axes of these wires [54]. Similar behaviors have been observed for mesowires of Au [64]. The advantages of using metal nanowires as the gas sensors are: i) Room-temperature operations. The
closing of nanoscopic gaps caused by gas absorption is at room temperature; ii) Reversibility. The mesowires can be returned to their equilibrium dimensions in the absence of gases; and iii) Very short response time (milliseconds). However, they have several disadvantages, such as: Instability. The mesowires are easy affected by the environment; and High cost. The expensive materials make them would not be extensively used.
2.3.2 Semiconducting nanowires
2.3.2.1 Adsorbate effect on conductance in semiconducting nanowires
At a given temperature, the conductance of the semiconducting nanowires is defined as
2 4 ne D G L µπ µπ µπ µπ ==== (2.3) where n is the initial carrier concentration, e the electronic charge, µ the mobility of the electrons, D and L are the diameter and length of the nanowire channel, respectively. During gas sensing, the change in conductance (∆G) of the semiconducting nanowires will result from change in carrier concentration ∆ns according to [60, 65]
2 s 4 n e D G L µπ µπ µπ µπ ∆∆∆∆ ∆ = ∆ = ∆ = ∆ = (2.4) Hence, the sensitivity of sensors can be defined as
s 0 n G G n ∆∆∆∆ ∆∆∆∆ ==== (2.5) The dependence of the sensitivity on the change in carrier concentration ∆ns is linear
[66], which indicates a more measurable change in carrier concentration could improve the sensing performance. Concerning selectivity and sensitivity, improvements could be obtained either by modifying the surface with catalyst particles or by modifying the intrinsic properties of semiconducting nanowires by plasma treatment [60, 67].
The sensing mechanism in metal oxide and silicon gas sensors is related to ionosorption of species over their surfaces. The most important ionosorbed species when operating in ambient air are oxygen (O2) and water (H2O). With oxygen as the
adsorbate in the temperature range between 100 and 500 ◦C, the SnO2 nanowire surface
vacancies are partially repopulated, which results in ionized (ionoadsorbed) surface oxygen of the general form Oββββ−−−−ααααS, such as molecular (O2
−
) and atomic form (O−) [68].
Up to about 200 ◦C, the lower activation energy form O2 −
is dominating; at higher temperature the O− form is in the dominant position. Upon adsorbing a reducing gas such as CO, the following surface reaction takes place with the ionoadsorbed oxygen:
gas - gas S 2 CO Oββββαααα CO e β β α ββ ββ αα β⋅⋅⋅⋅ ++++ → ⋅→ ⋅→ ⋅→ ⋅β + ⋅+ ⋅+ ⋅+ ⋅α −−−− (2.6)
which results in the change of the electrical conductance of SnO2 [65, 68], and therefore
in the conductivity of the nanowire, ∆G ~ ∆nCO, increases monotonically with CO
concentration. Direct adsorption is also proposed for the oxidizing gases, such as NO2,
whose effect is to decrease sensor conductance:
gas -
-2 2
NO ++++e NO (2.7) The physical properties (e.g. conductivity) of conducting polymers strongly depend on their doping levels. Fortunately, the doping levels of conducting polymers can be easily changed by chemical reactions with many analytes at room temperature, and this provides a simple technique to detect the analytes. Most of the conducting polymers are doped/undoped by redox reactions; therefore, their doping level can be altered by transferring electrons from or to the analytes. Electron transferring can cause the changes in resistance. For example, when a p-type conducting polymer, such as polypyrrole (PPy) reacts with NH3, its conductance is decreased rapidly by a reduction
reaction [69]:
redution
+ - - - +
-3 oxidation 3
after washing with dry nitrogen (N2) or air, the resistance of the sensing layer can be
totally or partly recovered by oxidation reaction as shown in Eq. (2.8).
2.3.2.2 Metal-oxide nanowire gas sensors
Metal-oxides possess a broad range of electronic, chemical, optical and physical properties that are often stable to vary with the composition of the surrounding gas atmosphere [65]. Because of this advantage, metal oxides like SnO2, TiO2, WO3, ZnO,
Fe2O3 and In2O3 for gas detection have been investigated for more than five decades [36,
65], and metal oxides gas sensors have been commercially available for more than 30 years. However, traditional sensors based on pristine or doped metal-oxides configured as single crystals, thin and thick films, ceramics, and powders through a variety of detection and transduction principles, typically have to operate at an elevated temperature, which results in large power consumption [70-72]. In 1991 Yamazoe demonstrated that the sensitivity and energy consumption of metal-oxide gas sensors can be significantly improved by reducing the crystallite size [73]. When the diameter of nanowires is close to or less than double thickness of the space-charge layer [36, 74], the gas sensing performances such as sensitivity, response speed, will be increased remarkably. These discoveries likely explains the exploration of the metal-oxide nanowires as a platform for chemical sensing is a recently hot event [65]. In comparison with their traditional thin- and thick film counterpart, one-dimensional metal-oxide nanowires have two advantages [67]: i) reduction of their operating temperature and power consumption, and ii) the possibility of single nanowire field-effect transistors (FET) and resistor configuration that allows that could be easily integrated with microelectronics technologies for nanosensing technology[65].
2.3.3 Silicon nanowire gas sensors
Silicon nanowire gas sensors, which have attract much attention in recent years [32, 42, 101, 102], are recognised to be a next generation building block for ultra-fast chemical sensing systems [75]. In comparison with bulk silicon field transistors, the sensors
