Characterization of graphene- based sensors for forensic ...1415924/FULLTEXT01.pdf · Observation...

Characterization of graphene-based sensors for forensic applications

Master’s degree project 2019/01 – 2019/06

ÜLLE-LINDA TALTS

KTH ROYAL INSTITUTE OF TECHNOLOGY

E L E C T R I C A L E N G I N E E R I N G A N D C O M P U T E R S C I E N C E

DEGREE PROJECT IN NANOTECHNOLOGY, SECOND LEVEL

STOCKHOLM, SWEDEN 2019

Characterization of graphene-based sensors for forensic applications

Evaluating suitability of CVD graphene-based

resistive sensor for detection of amphetamine

Ülle-Linda Talts

2019-08-02

Master’s Thesis

Examiner

Mattias Hammar

Academic adviser

Jiantong Li

Industrial adviser

Qin Wang

DEGREE PROJECT IN NANOTECHNOLOGY, SECOND LEVEL

STOCKHOLM, SWEDEN 2019

KTH Royal Institute of Technology

School of Electrical Engineering and Computer Science (EECS)

Department of Electronics and Embedded Systems

SE-100 44 Stockholm, Sweden

Abstract | i

Abstract

Recent improvements in sensor technology and applications can be partly attributed to the

advancements in micro- and nanoscale fabrication processes and discovery of novel materials. The

emergence of reliable and inexpensive methods of production of monolayer materials, such as

graphene, has revealed the advantageous electronic properties which when utilized in sensory

elements can significantly enhance response to the input signal. Hence, graphene-based sensory

devices have been widely investigated as the exotic properties of the carbon nanomaterial allow for

cost-efficient scalable production of highly sensitive transduction elements. Previous studies have

shown successful detection of n-type dopants such as ammonia and low pH solution. As the amine

group in amphetamine molecules is known to behave as an electron donor, in this study, graphene

conductivity changes in response to exposure to amphetamine salt solutions were investigated.

Graphene formed by chemical vapour deposition (CVD) was transferred onto SiO2 substrate with

gold electrodes to form a resistive transducer. Observation of large intensity ratio of graphene

characteristic 2D and G peaks as well as minimal defect peaks from Raman spectroscopy analysis

proved the integrity of the carbon monolayer was maintained. The atomic force microscopy and

resistance measurements results showed the storage of these sensory elements in ambient conditions

results in adsorption of impurities which considerably influence the electronic properties of graphene.

Upon exposure to amphetamine sulfate and amphetamine hydrochloride, conductivity decrease was

detected as expected. Signal enhancement by excitation of 470nm light did not show a significant

increase in response magnitude. However, the low reliability of sensor response limited further

analysis of the chemical sensor signal. Non-selective sensor response to amphetamine can be

detected, but improvements in device design are needed to minimize contamination of the graphene

surface by ambient impurities and variations in the sensor system.

Keywords

Sensor systems, Chemical sensors, Nanosensors, Drug screening, Nanomaterials

Sammanfattning | iii

Sammanfattning

De senaste förbättringarna i sensorteknik och applikationer kan kopplas till framsteg inom

framställningsprocesser berörande mikro- och nanoskala samt upptäckt av nya material. Framväxten

av tillförlitliga och billiga produktionsmetoder av monoskiktmaterial, såsom grafen, har avslöjat de

fördelaktiga elektroniska egenskaperna som när de används i sensoriska element och förbättrar

signalresponsen till inputsignalen. Grafenbaserade sensoriska applicationer har undersökts

allteftersom de exotiska egenskaperna hos kolbaserade nanomaterial möjliggör en kostnadseffektiv

skalbara produktion av högkänsliga transduktionselement. Tidigare studier har framgångsrikt visat

detektion av n-typ substanser såsom ammoniak och låg pH-lösning. Eftersom amingruppen i

amfetaminmolekyler är känd för att verka som en elektrondonator, undersöktes i denna studie

konduktivitetsändringar i grafen under exponering för amfetaminsaltlösningar.

Grafen bildad genom kemisk ångavsättning (CVD) överfördes på Si02-substrat med

guldelektroder för att bilda en resistiv omvandlare. Observation av intensitetförhållandet mellan de

grafenkarakteristiska 2D- och G-topparna samt minimala defekttoppar från

Ramanspektroskopianalysen visade att kolmonolagrets struktur upprätthölls. Resultaten av

atomkraftmikroskopi och resistansmätningar visade att lagringen av de sensoriska element i normala

omgivningsförhållanden resulterar i adsorption av föroreningar som avsevärt påverkar grafens

elektroniska egenskaper. Vid exponering för amfetaminsulfat och amfetaminhydroklorid upptäcktes

en förväntad konduktivitetsminskning. Signalförbättring genom excitation av 470nm-ljus visade inte

en signifikant ökning av svarstyrkan. Den låga tillförlitligheten hos sensorn begränsade emellertid

ytterligare analys av den kemiska sensorsignalen. Sensorns icke-selektiva svar på amfetamin kan

detekteras, men förbättringar i enhetens konstruktion behövs för att minimera kontaminering av

omgivande föroreningar på grafenytan och variationer i sensorsystemet.

Nyckelord

Sensorsystem, Kemiska sensorer, Nanosensorer, Drug screening, Nanomaterial

Acknowledgements | v

Acknowledgements

First, I would like to express my genuine gratitude and appreciation to my thesis supervisor Qin Wang

(RISE Acreo) for continuous support and positive mindset that encouraged me through this period.

Also, my thesis examiner and master program director Mattias Hammar (KTH) has provided great

support not only during the thesis project, but throughout the 2-year master program.

In addition, I would like to thank the experts who kindly helped me whenever I had any technical or

conceptual difficulties. Dr. Ingemar Petermann (RISE Acreo), Olof Öberg (RISE Acreo) and Dr. Per

Björk (RISE Acreo) enabled this research by always being able to share their knowledge, skills and

honest opinion. I am thankful for the support from my thesis supervisor Jiantong Li (KTH) and his

PhD students for enabling access to chemistry laboratories and their equipment. I am very grateful to

Prof. Mats Götelid (KTH) who enabled limitless access to Raman spectroscopy instrument, Arne

Quellmalz (KTH) for providing high quality graphene transfer and Simone Dunn (NFC) for providing

the analytes in focus of this study. I would like to also thank the Sweden’s innovation agency (Vinnova)

for financial support to this project through Graphene Strategic Innovations Program (SIO Grafen).

I would also like to acknowledge Marcus Gärdin as the second reader of this thesis, and I am gratefully

indebted to him for his very valuable comments on this thesis report and friendship.

Finally, I would like to express heartfelt gratitude to my family and friends for providing me with

constant support and encouragement throughout my academic career. Thank you.

Stockholm, June 2019

Ülle-Linda Talts

Table of contents | vii

Table of contents

Abstract ........................................................................................................ i Keywords .......................................................................................................................... i

Sammanfattning ........................................................................................ iii Nyckelord ........................................................................................................................ iii

Acknowledgements .................................................................................... v

Table of contents ...................................................................................... vii List of Figures ............................................................................................ ix

List of Tables ............................................................................................. xi List of acronyms and abbreviations ...................................................... xiii 1 Introduction .......................................................................................... 1

1.1 Background ........................................................................................................ 1 1.2 Problem ............................................................................................................... 1 1.3 Purpose ............................................................................................................... 1 1.4 Research Methodology ...................................................................................... 2 1.5 Delimitations ....................................................................................................... 2 1.6 Outcomes ............................................................................................................ 2 1.7 Structure of the thesis ....................................................................................... 3

2 Literature review .................................................................................. 5 2.1 Sensor technology ............................................................................................. 5

2.1.1 Transducer ............................................................................................ 5 2.1.2 Chemical sensing .................................................................................. 7

2.2 Graphene ............................................................................................................. 7 2.2.1 Electrical properties .............................................................................. 8 2.2.2 Fabrication ............................................................................................ 8 2.2.3 Chemical vapour deposited graphene transfer ..................................... 9 2.2.4 Characterization .................................................................................. 10 2.2.5 Graphene-based chemical sensing .................................................... 12

2.3 Drug screening ................................................................................................. 12 2.3.1 Amphetamine ...................................................................................... 13 2.3.2 Analysis tools for amphetamines in laboratories ................................ 14 2.3.3 Analysis tools for amphetamines on-site ............................................ 14

2.4 Related work ..................................................................................................... 14 2.4.1 Amphetamine affinity to graphene ...................................................... 14 2.4.2 Graphene response to the exposure of n-type donor ......................... 15 2.4.3 Signal enhancement by light excitation .............................................. 15

2.5 Summary ........................................................................................................... 16

3 Materials and Methods ...................................................................... 17 3.1 Research Process ............................................................................................ 17 3.2 Sensor fabrication ............................................................................................ 17 3.3 Material Characterization ................................................................................ 18 3.4 Experimental design for sensor ..................................................................... 18

3.4.1 Test environment ................................................................................ 18 3.4.2 Hardware/Software to be used ........................................................... 19 3.4.3 Experimental environment optimization .............................................. 19

viii | Table of contents

3.5 Assessing the reliability and validity of the data collected ......................... 20 4 Results and Analysis ......................................................................... 21

4.1 Sensor characterization .................................................................................. 21 4.1.1 Raman spectroscopy .......................................................................... 21 4.1.2 Atomic Force Microscopy.................................................................... 22 4.1.3 Resistance measurements ................................................................. 23

4.2 Sensor testing .................................................................................................. 23 4.2.1 Response to analyte ........................................................................... 23 4.2.2 Response to light excitation ................................................................ 25 4.2.3 Response to back gating .................................................................... 26

4.3 Reliability Analysis........................................................................................... 27 4.4 Validity Analysis ............................................................................................... 28 4.5 Summary ........................................................................................................... 29

5 Conclusions and Future work ........................................................... 31 5.1 Conclusions ...................................................................................................... 31 5.2 Future work ....................................................................................................... 31

References ................................................................................................ 33

List of Figures | ix

List of Figures

Figure 2-1: Energy transformation diagram of the self-generating and modulating

sensor. Adapted from [2] ............................................................................. 6 Figure 2-2: Diagram comparing graphene mass production methods based on the

quality of the material achieved. Image sourced from [4] ........................... 9 Figure 2-3: Illustration of the graphene transfer process. Adapted from [16] .............. 10 Figure 2-4: Graphene and graphite Raman spectroscopy example. Image source

[20] ............................................................................................................. 11 Figure 2-5: Theoretical estimation of amphetamine molecule physisorption on

CNT sidewall. Imaged sourced from [38] .................................................. 15 Figure 3-1: Illustration of the sensor chip electrode dimensions. The green areas

represent SiO2 and the teal coloured areas are the contact pads. CVD

graphene was deposited over the whole chip. ........................................... 18 Figure 3-2: Experimental setup for fluidic resistance change measurements. A)

Illustrative schematic of the setup with the devices connected. B)

Illustration of the sensor setup with marked components: 1 – stage, 2-

conductive chip holder, 3- the chip with the graphene-based

transducer element, 4 – PDMS cavity forming the solution chamber, 5

– PMMA lid with epoxy secured inlet and outlet tubing, 7 – PEEK

microfluidic tubing. C) Photograph of the sensor. Image adapted from

[3] ............................................................................................................... 19 Figure 4-1: Raman spectroscopy results: A) Comparison of CVD graphene with

blank wafer and graphene ink on the same substrate. B) Analysis of

characteristic graphene G and 2D peaks with individual offset, peak

locations were determined by Gaussian fit and averaged over 5

sensors, intensity ratio is determined from raw data.................................. 21 Figure 4-2: AFM analysis results A) control Si/SiO2 wafer 10m*10m area. B)

CVD graphene on Si/SiO2 wafer 10m*10m area. C)Average

surface roughness parameters and deviation determined from

selected 5 different areas in image A and B. D) control Si/SiO2 wafer

500nm*500nm area. E) CVD graphene on Si/SiO2 wafer

500nm*500nm area. F)Average surface roughness parameters and

deviation determined from selected 5 different areas in image D and

E. Rq – root mean square average of profile height; Ra – arithmetic

average of profile height deviations. .......................................................... 22 Figure 4-3: Electrical measurements of graphene-based transducer response to

amphetamine salts. A) Signal to 1 mg/ml amphetamine sulfate; B)

Signal to 5 mg/ml amphetamine sulfate; C) Signal to 1 mg/ml

amphetamine hydrochloride; D) Signal to 5 mg/ml amphetamine

hydrochloride. All measurements were done in dark, with applied 50

mV bias and 20l/min flow rate. ................................................................. 24 Figure 4-4: Electrical measurements of graphene-based transducer response to

light excitation. A) Current change in illumination at 365 nm with

intensity of 400 W/cm2 when the dry graphene surface was exposed

to ambient conditions and in N2 flow. B) Current change in illumination

at 470 nm with intensity of 9.6 mW/cm2 when the graphene surface

was incorporated into the fluidic system with diH2O. ................................. 25 Figure 4-5: Electrical measurements of graphene-based transducer response to

analyte in constant illumination at 470 nm with intensity of 9.6

mW/cm2. ..................................................................................................... 26

x | List of Figures

Figure 4-6: Electrical measurements of the tested field-effect transistor. IS-

source-drain current; IG – gate current; VG – gate potential; V_ds –

source-drain bias potential ......................................................................... 26 Figure 4-7: Inconsistency of electrical measurements’ results of graphene-based

chemical sensor response to amphetamine. A) Response to

amphetamine sulphate in constant UV excitation (365 nm, 400

W/cm2.B) Strong response to amphetamine hydrochloride. C) A

weak response to amphetamine sulphate with increased noise. D)

Opposite current response to amphetamine sulphate. .............................. 27 Figure 4-8: A) Control measurement of current response to same solution in 2

separate syringe pumps. B) Control measurements for analyte

response in 0.01PBS buffer solution. ......................................................... 28 Figure 4-9: Electrical measurements of graphene-based transducer response to

amphetamine hydrochloride of different concentration: A) 2.8 mg/ml,

B) 10 mg/ml. ............................................................................................... 28

List of Tables | xi

List of Tables

Table 1-1: Summarizing diagram of the research process with the main aspects

of each part. ................................................................................................. 3 Table 2-1: Functional sensor characteristics [2] ............................................................ 6

List of acronyms and abbreviations | xiii

List of acronyms and abbreviations

AmpHCl Amphetamine hydrochloride

AmpSul Amphetamine sulfate

Au Gold

CNT Carbon nanotubes

CV Cyclic voltammetry

CVD Chemical vapor deposition

diH2O Deionized water

I-V Current-voltage

PBS Phosphate buffered saline

PDMS Polydimethylsiloxane

PMMA Poly(methyl methacrylate)

Si Silicon

SiC Silicon carbide

SiO2 Silicon dioxide

Ti Titanium

UV Ultraviolet

Introduction | 1

1 Introduction

Nanotechnology-based sensors have gathered much attention as they enable highly sensitive as well

as specific detection with cost-effective devices [1]. Among multiple areas that could greatly benefit

from advancements in this field is forensic science [2]. A graphene-based chemical sensor that enables

drug detection has been proposed for onsite analysis of seized drugs. A previous project in

collaboration with the Swedish National Forensic Centre (NFC) at RISE ICT Acreo demonstrated that

such sensors can be realized. Resistive transduction elements based on high-quality graphene on-SiC

have been established to enable detecting presence of drug substances, such as cocaine and

amphetamine [3]. Based on these positive proof-of-concept results, graphene suitability for

amphetamine detection was further investigated.

1.1 Background

Potential of graphene as a transducer for sensing devices has been investigated in a large number of

publications (Google Scholar gives >350,000 results when searching ‘Graphene sensor’). A major

portion of these studies focuses on utilizing advancements in micro- and nanoscale fabrication

processes and the discovery of novel materials [2]. The emergence of reliable and inexpensive

methods of production of monolayer materials, such as graphene, has revealed the advantageous

electronic properties which when utilized in sensory elements can significantly enhance response to

the input signal. Maturing of chemical vapour deposited (CVD) graphene fabrication and transfer

techniques enable cost-efficient scalable production of highly sensitive graphene-based transduction

elements [4].

Previous studies monitoring conductivity changes in graphene have shown successful detection

of n-type dopants such as ammonia [5] and low pH solution [6]. The amine group in amphetamine

molecules is known to behave as an electron donor [7] thus electrical properties of graphene are

influenced upon adsorption of these molecules on the surface [5]. Monitoring the changes in

conductivity in response to exposure to amphetamine salt solutions are expected to provide a signal.

1.2 Problem

The previous research investigating graphene as an amphetamines detection transduction element

was using SiC as a substrate material as well as the precursor for epitaxially grown graphene. This

material is priced at 7.8 $/mm2 in graphene supermarket while CVD produced and transferred

graphene on SiO2/Si substrate is priced at 0.45 $/mm2 from the same supplier [8]. As cleaning of

epitaxial graphene surface grown on SiC has proven to be difficult and not always successful even

when using highly reactive solutions, reusing these devices has not shown to produce reliable results

due to irreversible changes to the surface through oxidation and impurities. This applies more-so for

transferred CVD graphene that is not as strongly bound to the substrate and would be

damaged/removed in too harsh cleaning conditions [9]. Thus, for commercialization of these devices,

a more cost-effective graphene-based sensor, such as transferred CVD graphene-based device, must

be used for detecting the analyte.

1.3 Purpose

The purpose of this thesis is to evaluate the suitability of CVD graphene as a transduction element in

resistance based sensory system for drug detection. The focus of this project is analyzing the

conductance change caused by exposing the transduction element to aqueous amphetamine solution

of known concentration and testing methods for enhancing the signal magnitude. Success in proving

2 | Introduction

the suitability of this cost-effective sensor technology for detecting seized drugs would enable faster

and improved onsite analysis of unknown substances.

1.4 Research Methodology

Quantitative method is used to deductively approach the hypothesis of this study. The experimental

research methods used here include a literature survey, characterization of the device, testing the

performance of the device, followed by the analysis of the results. Internal validity of the experiment

is ensured by performing repeated control experiments and by providing the baseline analyte-free

measurements in combination with analyte response measurements for comparison. Reliability of the

sensor performance is evaluated by comparing the response to the same type and magnitude of

analyte on multiple graphene-based transducers. The external validity of the sensor’s suitability for

onsite drug analysis is not evaluated as the selectivity of the sensor is not investigated.

Experimental artifacts during testing of the sensor are minimized by using automatic periodic

switching between the two compared sensor states. Variability in conditions of different sensors is

unavoidable due to the manual assembly of the experiment station but minimal changes are

introduced to the devices themselves. The conclusion made in this study state the influence of these

artefacts and how to avoid them in future studies.

1.5 Delimitations

Due to the limited timeframe and availability of instrumentation, the following limitations were

made:

• Experiments with SiC based devices were not repeated for comparative analysis due to

absence of clean SiC devices and unavailability to produce more.

• While sensor response to the exposure of amphetamine was investigated, the selectivity of

the transduction mechanism to amphetamine was not investigated. The aim of the study was

to establish if graphene surface is influenced by the analyte and the simplest design with

minimal surface processing was utilized to reduce defects introduce to the graphene

monolayer. Hence changing the transduction element surface through functionalization for

the selective response was not investigated.

• The transduction element surface was strongly influenced by being exposed to ambient

impurities. This can potentially be improved by changing the design of the transduction

element and fluidics system, redesigning the sensor system was out of the scope of this

project but is strongly recommended for any future studies.

• Other fabrication methods of the graphene-based transducers, such as using chemically

exfoliated graphene, were not analysed during this study. The experiments providing the

theoretical basis for testing the hypothesis used epitaxially grown graphene on SiC [3] and

the utilized sensor fabrication during this study enables producing comparable single-layer

graphene sheets.

1.6 Outcomes

Results from the experimental research showed how transferred CVD graphene on SiO2 substrate had

distinguishable signal when exposed to the target analyte making the graphene component an

effective resistance-based transduction element for chemical sensing of amphetamine salts. However,

the sensor design resulted in significant variation in device performance making reliability as well as

quantitative sensor characterization problematic. Initial tests to enhance the signal through light

excitation and back-gate optimization did not improve the sensor response but further investigation

Introduction | 3

3

is recommended. Characterization of the graphene surface revealed substantial amount of impurities

on the graphene surface which are estimated to have a significant effect on the performance and

reliability. Overall, transferred CVD graphene enabled to detect presence of amphetamine but sensor

design needs to be improved to minimize impurities and variations in sensing properties.

1.7 Structure of the thesis

The structure of the thesis is provided in Table 1-1 with main takeaways. Chapter 2 presents relevant

background information about sensors, graphene and analyte in focus of this study. Chapter 3

presents the methods and materials used to fabricate the sensor, characterize the transduction

element and test the conductivity response in response to amphetamine exposure. Chapter 4 includes

the results and analysis of the findings. Chapter 5 concludes the study by summarizing the outcomes

and proposing strategies to continue this research.

Table 1-1: Summarizing diagram of the research process with the main aspects of each part.

Chapter 2: Literature review

• Overview of sensor technology basics

• Introduction to graphene

• Forensic analysis methods and amphetamine properties

Hypothesis

Resistive transduction element made of CVD graphene on SiO2/Si enables detection of

amphetamine exposure in aqueous environment.

Chapter 3: Experimental methods

Device fabrication: Chemical vapor deposited graphene transferred onto thermally grown SiO2 on

Si 4’’ wafer with Au electrodes with device dimensions 6*8 mm.

Sensor test setup: manually mounted PDMS chamber and PMMA lid, integrated with

microfluidic inlet and outlet, placed between Au electrode pads that are connected with electrical

probe station for biasing as well as current readout.

Material characterization:

• Raman spectroscopy

• Atomic force microscopy

• Resistance measurements

Measurements of conductivity changes in response to:

• amphetamine salt solutions

• light excitation

• amphetamine salt solutions + light excitation

• adapting the setup to a back-gated field-effect transistor

Chapter 4: Results and analysis

Response to amphetamine salt was successfully detected but the signal magnitude was not enhanced by light

excitation. Ambient impurities detected on the graphene surface are significantly changing the electronic

properties of the transducer and causing inconsistency in the analyte response readout.

Chapter 5: Conclusion

Non-selective sensing of amphetamine is enabled by the proposed devices but the reliability of the

graphene-based transducer must be improved through redesigning the sensor system.

Literature review | 5

2 Literature review

This chapter provides an overview of and reasoning behind this study. First, the general sensor

concept is described with a focus on transducer elements and chemical sensors. This is followed by a

basic introduction to graphene and the reasoning for applying this nanomaterial in the sensory

devices. Additionally, background information about the properties of the analytes in the focus of this

study, amphetamine-like drugs, are described. Finally, several related articles published previously

that lay the theoretical background for combining graphene-based devices for detection of

amphetamines are summarized.

2.1 Sensor technology

Sensors are devices used to record the presence or changes in the presence of a defined input

signal, either a physical or chemical signal. The term is defined as the whole component, including

the physical packaging and external connections. The range of devices can be subdivided based on

properties sensed or technology used. The latter can, in turn, be categorized based on physical

phenomena utilized as well as material types used [2].

Advances in materials science and engineering have paved the way for the development of new

and more capable sensors. Combined with improvements in micro-and nano fabrication techniques,

performance and cost-efficiency of many applications has improved. The multidisciplinary research

considering the physical phenomena utilized for sensing, material properties and production

engineering is needed to for determining improvement opportunities and assessing technical risks of

novel technology [2].

The final devices would include the basic elements of a sensor such as sensor element/transducer,

sensor packaging, connections, sensor signal processing hardware. Improving the technology with

material advancements can be achieved through changes in 1) sensor transducer mediums, 2) sensor

packaging material and 3) signal processing devices [2]. This thesis focuses on investigating the first

variable by testing novel transducer mediums for a specific input signal.

2.1.1 Transducer

In the scientific community, transducer is often used as a synonym to sensor or sensory element.

American National Standards Institute has defined a transducer as “a device which provides a usable

output in response to a specific measurand” [2]. Another physics focused definition describes the

sensory element as the fundamental transduction element responsible for converting one form of

energy into another [10]. The following section describes transducers based on the latter definition.

With the domination of solid-state electronics in sensor technology evolvement, the output has

been mostly associated with an electrical quantity while other physical or chemical readouts are also

valid. For example, optical and fluidic readout techniques have evolved significantly within the last

decade and are believed to be suitable alternatives specifically in sub-micron scale devices. However,

due to the benefits of computer-based control, recording and signal processing, electronic output has

been most investigated and applied in current applications [2].

Transducer working principle can be separated based on self-generating and modulating

mechanism, as depicted in figure 2-1. The first, self-generating, enables the transformation of one

type of energy into another without any additional energy input. An example of this is a piezoelectric

pressure sensor where mechanical energy (input) is converted into an electrical charge (output) by

changes in material structure (physical phenomena utilized by the transducer). The modulating

mechanism requires an input of an auxiliary energy type for output energy. This can be seen in, for

example, a strain gauge, where the mechanical strain (input) is converted into a change in electrical

6 | Literature review

current (modulation energy form) driven through the transducer element enabling an output signal

in the form of change in resistance. Commonly used signal energies in modulating sensors include

photoconductive, magnetoresistive, thermoresistive, piezoresistive and electrically conductive [2].

The latter is the focus of this study, where the input energy is measured as a change in conductance

of the transducer.

Figure 2-1: Energy transformation diagram of the self-generating and modulating sensor. Adapted from [2]

The suitability of a sensor can be determined by its characteristics and how these fit with the

requirements of the specific application. There is no defined method for classifying and finding the

sensor with optimal properties. Sensors can be characterized based on numerous considerations and

the suitable one is chosen based on individual cases. Firstly, the sensors can be defined based on their

input energy form. Secondly, sensor properties can be listed based on the functional properties of the

device itself. Third, for any device designed for future commercial use, practical considerations should

be discussed and viewed as well [2]. The following section will focus on each one of these points and

will introduce the relevant aspects of this study.

The form of the primary input signal compatibility with transduction mechanism defines the

suitability of the sensor. There are 6 major energy forms commonly detected: mechanical, thermal,

electrical, magnetic, radiant and chemical. While it is important for the device to correctly detect the

chosen form of energy, it’s stability when simultaneously exposed to the other forms must be ensured

by verifying the stability of the transducer as well as the other part such as packaging and connections.

The device used for this thesis uses chemical energy as the input signal. For example, changes in

thermal or electrical conditions of the sensor, the environment may have a significant effect on the

performance of the device. While the input energy determines the sensor signal, other energy forms

need to be considered to ensure reliability [2].

In addition to stability in a changing environment, other functional properties need to be

considered. Several important ones have been brought out and separated into static and dynamic

characteristics in table 2-1. In application requiring performance in dynamic region, static properties

must also be considered. Accuracy, important for static and dynamic sensors, is defined as the degree

of correctness with what the sensor can provide the value of the measured input and is generally

described in maximum deviation from expected values. This percentage of distortion allowed within

a device is defined by its application and specific sensor constraints. Range and limit of detection

define the input parameters (analyte quantity) that the device operates reliably in. Selectivity is

sensors ability to measure only the desired parameter. Sensitivity is the amount of signal produced

by the sensor in response to the defined amount of input over the sensor’s working range; this is

important to estimate the device’s ability to detect changes. Sensitivity is often compared to the noise

levels to determine the signal-to-noise ratio at certain input. These are commonly used parameters to

characterize sensors [2].

Table 2-1: Functional sensor characteristics [2]

Static Dynamic

Accuracy Dynamic error response Distortion Instability Hysteresis Hysteresis Limit of detection Drift Linearity Noise Selectivity/specificity Operating range Sensitivity Repeatability Threshold Step response


7

In addition to previously mentioned properties of the input signal conversion to output, practical

considerations of the device ought to be analyzed. An important factor is the price per unit and if the

device is reusable. Price constitutes of raw materials, fabrication process and its scalability as well as

maintenance costs. Another important consideration is the portability of the measurement setup and

the scenario of intended use. In addition, the target user competence must consider when defining

the steps needed to use the sensor. Economic and practical considerations are important for

determining the commercialization capability of novel devices [2].

2.1.2 Chemical sensing

Chemical sensors are defined as devices or instruments that can determine the presence,

concentration or quantity of a given analyte – chemical substance of interest for qualitative or

quantitative analysis. Recent advancements in synthesis of novel materials have enabled significant

possibilities in improving detection in a variety of applications such as environmental control, process

monitoring in industrial production lines, gas composition analysis in for example alcohol detection

in breath, national defense for drug or explosive detection as well as numerous possibilities in medical

innovation. Due to this huge potential, research teams around the world have been working towards

developing chemical sensors and solving some of the issues mentioned in the following paragraphs

[11].

The complexity of this type of sensors is caused by the specific nature of chemical substances

analyzed as it relies on elemental or molecular properties. The selective sensing mechanism of the

target analyte is generally enabled by recognition of a defined molecular structure or associated

reactivity. While the need for selectivity can be eliminated by analyte pre-processing in e.g.

chromatography or electrophoretic sample separation, these steps require an additional tool and

more resources, making selectivity important characteristics to incorporate into prospective sensor

technologies [2].

Sensitivity and limit of detection relate to the quantity or concentration of the analyte species

which for most chemical sensors is required to be 10-9 molar concentrations or less. The dynamic

range in which the sensor should function as expected can vary by a factor of 1023. These

considerations make sensitivity to the target analyte another challenge in addition to the requirement

of specificity [12].

Phase dimensionality and temporal aspects of the target species can be in any physical phase (gas,

liquid, solid) with quantities varying from bulk volumes in liters to micro range scales of picolitres or

in nanoscale of surface layers. Added complexity can be caused by the need to monitor changes

repeatedly or overtime in restricted environments (e.g. water analysis or implantable medical

sensors). The requirement of reliability, characterized by accuracy and precision of the quantitative

analysis, needs to be ensured in all possible environments for a successful device [2, 12].

2.2 Graphene

Graphene is a 2D nanomaterial that earned its producers and characterizers Andre Geim and

Konstantin Novoselov the 2010 Nobel Prize in physics [13]. This single atom thick layer of graphite

has been heavily researched as the exotic properties of graphene could potentially enable a wide range

of innovations in all aspect of technology. This chapter focuses on giving a brief overview of graphene

properties directly relevant for electrical sensing purpose. An introduction to developments in

fabrication techniques, developed after the initial scotch-tape method of single layer exfoliation, is

provided. Specific characterization techniques used for nanoscale material is another aspect

discussed here, as it is a necessity for monitoring and optimizing the properties of graphene. The final

section is dedicated to discussing the usability of graphene as a transduction element in sensory

applications.


2.2.1 Electrical properties

Graphene consists of carbon atoms that each have 6 protons and 6 neutrons with 6 electrons

orbiting around the nucleus. 2 of these electrons from the inert fully filled inner orbital, 4 of these

constitute the valence shell. The energy levels of the valence shell are influenced by the external

environment and can be changed by forming bonds with other atoms. Graphene consists of only

carbon atoms, thus for the 2-dimensional (2D) sheet 3 covalent sigma bonds are formed by using 3 of

the valence electrons from each atom and the 4th valence electron forms a cloud of delocalized charge

in the horizontal plane through intermittent -bonds. The latter phenomenon is the origin behind the

enhanced electrical conductivity of this carbon-based material [4, 14]

Graphite is the most stable form of carbon material. In graphite, the graphene sheets are stacked

on top of each other horizontally by weak van de Waals forces and the delocalized electrons are not

localized to a single layer. In graphene, the larger the 2D structure, the more stable the sheet becomes.

The electron movement is confined within the planar sheet the molecular structure results in a

semiconductor material with zero bandgap giving rise to ambipolar characteristics that enables rapid

charge transport by either type of charge carriers [14]. The electronic properties are strongly

influenced by the chemical and electrical environment due to large surface-to-volume ratio. Changing

the Fermi energy by introduction of surface adsorbates or by applying gate potential influences the

conductivity rapidly. The former is used in this study by monitoring resistance changes in response

to changes in the chemical environment [5].

2.2.2 Fabrication

For graphene-based devices to compete and succeed in silicon-based technology applications, the

fabrication must be compatible with the standard wafer-scale lithographic method. In addition, it

must be possible to integrate the production with other widely used integrated circuit fabrication

processes. Common fabrication methods are compared based on production costs and the quality of

the material produced in figure 2-2. Two methods enabling scalable high quality of the nanomaterial

are epitaxial graphene growth on silicon carbide (SiC) surface and chemical vapour deposition on

transition metal for further transfer [4].

Silicon carbide is a large bandgap semiconductor that in normal conditions behaves as an

insulator. Thermal desorption at high temperatures (1100 C) and ultra-high vacuum (-10-6torr) can

be used to make the Si atom from the surface desorb, leaving a crystalline layer of carbon atoms

forming graphene. This graphitization reaction is not self-limiting which may lead to inconsistent

depth of silicon removal causing inhomogeneous number of graphene layers. The layer or layers are

coupled to the surface by van der Waals forces having minimal effect on the electronic structure of

graphene due to very high purity or defect formation. The high purity of the graphene produced makes

it difficult to modify or functionalize. In addition, SiC as substrate material is currently too costly for

single-use applications resulting in the need for alternative methods [15].

Another commonly used production method is chemical vapour deposition (CVD) during which

graphene is directly synthesized from hydrocarbons. For example, widely commercially available CVD

graphene is produced from methane on a transition metal surface, most commonly a copper foil. This

enables the production of large-area graphene with defined number of layers which can be

subsequently transferred on the desired substrate. This makes this technique useful for commercial

applications in industrial scale [15]. Due to these benefits, this fabrication method was chosen for

producing graphene-based sensors in this study and is described in further detail in the following

section.


9

Figure 2-2: Diagram comparing graphene mass production methods based on the quality of the material

achieved. Image sourced from [4]

2.2.3 Chemical vapour deposited graphene transfer

CVD is a bottom-up production method of high-quality graphene single layers. Majority of

applications require the material to be transferred to an insulating surface. The nanomaterial must

be transferred onto the target substrate via a suitable and optimized process. As the transfer process

is critical for determining the final properties, a defined step-by-step process must be followed with

care. Research teams have been investigating further transfer optimization and improvement

techniques to make the transfer process damage the graphene less and enable more reliable

production [15].

The general fabrication protocol of wet transfer of CVD graphene-based device can be

summarized in the following points:

1) Synthesizing graphene on a transition metal surface through CVD, receiving the CVD

deposited graphene from the commercial supplier.

2) Spin coating of polymethyl methacrylate (PMMA) layer on graphene as a carrier material

(figure 2-3 A).

3) Removing the copper foil by etching in iron (III) chloride hexahydrate (FeCl3) solution

with PMMA graphene facing the solution-air interface (figure 2-3 B).

4) The PMMA graphene film is floated on DI water and the final substrate is elevated from

the solution while ensuring the film stays on the substrate (figure 2-3 C).

5) The substrate graphene PMMA stack is baked at 45 C for 10 minutes to dry it and enhance

the interaction between the substrate and graphene layer.

6) The substrate with the film is placed in acetone for 24 hours to remove the PMMA

7) Acetone residues are removed by submerging the substrate in isopropanol for 5 minutes.

8) The substrate is dried under nitrogen flow and baked at low temperature for 10 min [16].


Figure 2-3: Illustration of the graphene transfer process. Adapted from [16]

The transfer process is crucial for determining graphene properties and its suitability for the

intended purpose. In the ideal case, the substrate and graphene interface remains completely clean,

smooth and the graphene layer is not affected by the processing steps. While damaging and changing

the nanomaterial is a possibility, the impurities and structures on the surface and at the interface have

shown to have the most dominant impact on the properties. Etchants used for removing the copper

are likely to leave metal oxide residues which influence the stability and conductivity of graphene.

Same applies to the sacrificial transfer material, PMMA, that has shown to leave residues on the

surface that are difficult to remove without damaging the graphene itself [17]. The properties that

enable high sensitivity in graphene transducers, make any changes introduced during processing very

impactful.

Any impurities and defects introduced during these steps can have a significant effect on the

electrical properties of graphene. While carrier mobility in the range of 103 to 104 cm2/Vs has been

reported at specific conditions, mobility in the ambient environment (conditions for most commercial

application) is in the range of 200 to 2500 cm2/Vs due to extrinsic scattering from charged impurities

that have a dominating effect. In addition, hysteresis is observed in resistance-voltage sweeping

measurements. The most likely cause behind changing the intrinsic graphene properties is trapped

H2O and O2 molecules at the graphene-substrate interface. Also, the material used to support the

graphene during the transfer process leaves residues on the surface that are difficult to remove

afterwards [18]. Graphene cannot withstand some of the standard semiconductor processing steps

to remove the polymer residues leaving the only suitable method of annealing in a clean or reducing

environment of vacuum, H2/N2 or H2/Ar2 [17]. Studies have shown that the combination of acetone

treatment with vacuum annealing can reduce the impurity level and remove the dopant molecule

effects [19]. Post-processing treatment and care when handling the material are required to control

the electrical properties.

2.2.4 Characterization

As described in the previous section, the graphene is highly susceptible and greatly influenced by

its environment as well as the processing history. Thus, ensuring the quality and monitoring changes

in widely used parameters becomes essential for predicting the graphene-based device performance

and suitability for the intended application. Commonly used techniques, Raman spectroscopy and

atomic force microscopy, are described in the following paragraphs.

Raman spectroscopy

Transitions between molecular energy levels have distinguished patterns that are directly related to

the unique molecular configurations. Measuring these changes enables to characterize the single-

layer graphene layer [20].

A B C


11

As the incident monochromatic light source is directed towards the sample, radiation scattered

contains the original wavelength as well as pairs of new frequencies diverging from the original one.

This shift is used as a characteristic energy shift in the scattered molecule. The upward energy

transitions shifting the detected energy lower, called the Stokes shift, has proven to be a reliable

source of information about the molecular bonds enabling to determine the Raman band m. The

energy absorbed can correspond to vibrational, rotational or electronic transitions. For measurement

reliability and available information, scattering from vibrational states is most commonly used for

reliable measurements (within 0-4000 cm-1 Stokes shift) [21].

In addition to obtaining the Raman band with a frequency shift of m, the polarization of the

energy state can be evaluated from the shape and intensity of the spectrum peak. This can be an

indicator of impurities which either disrupt the symmetry of vibrations or have energy shift similar to

the analyte making it difficult to distinguish between the substrate and impurity [21]. The analyte

factors that affect the intensity of the peak are strongly correlated with large polarizability changes on

vibrational models, frequency of the incident radiation, incident radiation intensity and the number

of scattering molecules per unit volume. Due to this, for example, double and triple bonds between

carbon atoms have higher intensity in Raman spectrum making detection of single-layer graphene

possible even at a very low number of scattering centres [20].

Graphene structure has sp2 hybridized carbon hexagonal interconnected structures with 2 atom

unit cell. The most significant features of Raman spectra are the G-band at 1582 cm-1 – graphite

characteristic, and 2D band at approximately 2650 cm-1. The former G peak is a result from doubly

degenerate resonance observed in graphite samples as well. The latter, 2D feature, is a second-order

zone boundary interaction resulting from double-resonance Raman process that links electron and

phonons in the dispersion relations of graphene. As these zone boundary phonons are not allowed in

graphite samples due to selection rules, they appear at approximately 2650 cm-1 only in graphene

samples. These phonon interactions result in peaks at approximately half frequency, 1325 cm-1, at

defect points visible in for example oxidized graphene and graphite samples [22, 23]. The single 2D

peak with 2D/G intensity ratio above 4 has proven to be a clear indication of a single -layer defect-

free graphene. From figure 2-4 difference between the graphite and graphene Raman spectroscopy

peaks can be seen at excitation wavelength 514 nm published by Ferrari et al Excitation light of 633

nm would result in very similar peaks with slight redshift [20].

In this study 633 nm laser source was used which would penetrate the surface to 3 m when

focused on the surface. As the substrate material is silicon, the appearance of a distinctive peak at

m(Si)=523cm-1 can be used as an indicator of focus correctness [24].

Figure 2-4: Graphene and graphite Raman spectroscopy example. Image source [20]


Atomic Force Microscopy

Atomic force microscope (AFM) is a versatile tool for characterizing surface topography with

resolution in the nanometers range. A cantilever with angstrom size tip is scanned over the surface

line-by-line while the height changes are monitored by the laser reflectance changes from the top

surface of the cantilever. In close proximity to the surface, the cantilever becomes deflected due to

van der Waals forces. The change is deflection is fed into a feedback loop to continuously keep the

forces constant by changing the cantilever height. This enables retrieving information about the

surface height changes at the specific position while ensuring the tip does not get damaged by strong

contact with the substrate. The scanning modes are separate into static contact and dynamic tapping

modes with the latter being preferred for minimizing the damage on the sample as well as the probe.

The cantilever is made to oscillate near its resonance frequency with defined amplitude and

frequency. At certain proximity, the amplitude change is caused by the interaction with the surface

which is used as a signal to adjust the probe height. Due to the scanning nature of this technique,

characterizing large areas is very time-consuming [25]. However, the instrument enables

characterization of local nanoscale structures making it a valuable tool for analyzing any surface with

nanomaterials and structures.

Previous studies have shown how the corrugations from the SiO2 surface are adapted to the

overlaying CVD graphene surface. Any deposits and impurities remaining on the graphene surface

from the lithography process should be visible from increased roughness from blank SiO2 samples

[26]. Comparison between the substrate and graphene surface topology enables retrieving data about

the nanomaterial quality.

2.2.5 Graphene-based chemical sensing

Graphene has been promoted highly for improving sensory devices and a large number of

research teams have focused on investigating graphene potential as a transduction element in

electroconductive measurements [27]. The delocalized -electrons, responsible for the high mobility,

are highly influenced by their immediate environment making any binding events on the surface

detectable by changes in the conductivity of the graphene layer [5]. The inherently high surface-to-

volume ratio of single-or few-layer graphene makes the surface reactions dominate over the bulk

properties resulting in high sensitivity which enables single- molecule detection. In addition, similarly

high conductivity to metals and low defect density enables low intrinsic noise at minimal charge

injection [28].

The influence of adsorption on the graphene surface affects the conductivity by influencing the

Fermi level making graphene a suitable transducer material for chemiresistive sensors for analytes in

gas or liquid state [5, 6, 29]. Graphene-based devices have shown to successfully detect changes in

gas composition in the vicinity of the surface. For example, ammonia, NH2, interacts with graphene

by donating electrons to the transducer and thus contributing towards n-type doping [30]. Other

studies have shown how air humidity affects graphene have shown that adsorption of polar H2O

molecules results in p-type doping of the graphene and the resulting increase in p-type doped CVD

graphene on SiO2 substrate [31]. Similarly, toxic gas NO2 has higher electronegativity resulting in

electron transfer from the graphene sensor element to the gas molecule [29]. Adsorption of polar

molecules can be detected through conductivity changes.

2.3 Drug screening

European report on drug consumption and development has highlighted the issue that drug

availability and consumption is in the rising trend. As the number of cases has been increasing, the

need to make analysis of the evidence more efficient is becoming more prevalent. In addition, with


13

internet enabling to market the illegal substance to a wider community, the ability to compare police

findings’ chemical composition is becoming a key to determine the traffic routes [32].

Amphetamines and metamphetamines are most frequently seized stimulant in the north and

north-east Europe. Based on data from 2000-2014, only northern European countries showed an

increasing trend of amphetamines consumption. Estimation of 11.9 million adults in Europe have

tried amphetamines during their life and 35 000 European clients were admitted to specialized drug

treatment programs tackling consumption of amphetamines making it the 2nd most common

substance abused in these clinics after heroin [32].

Chemical sensing in forensic science has several specific challenges that make substance analysis

more complex. Most prevalent is the absence of quality control in the manufacturing of illegal drugs

causing a large variation in composition. The analysis techniques need to have a wide working range

while still enabling selective detection for defined substances in an unknown matrix [31] .

2.3.1 Amphetamine

Amphetamine is the simplest form of the known amphetamine-type neurostimulants (others

include e.g. metamphetamine, cocaine). Single dosage can vary from tens to hundreds of milligrams

depending on the purity of the substance but seized tablet can contain up to 40mg of the active drug.

The most common synthesis method uses phenylacetone, formic acid, ammonium formate or

formamide thus occurrence of these chemicals in seized samples is possible. Detecting some of these

drug precursor residues and derivatives can indicate the origin of the drugs. Commonly seized

substances in Europe can have a purity ranging from 5% to 28%. The remaining amount is made up

of cutting agents such as caffeine, glucose and sugars [33].

It is commonly seized in crystalline salt form as amphetamine sulfate and less commonly as

amphetamine hydrochloride, basic properties of both are shown in table 2-2. A spectrophotometric

study focusing on amphetamine-like drugs showcased that the nitrogen group in amphetamine makes

the molecule act as a base and donate electrons to the acceptor molecule when forming an ion-pair

complex [7].

Table 2.2: Chemical information about common amphetamine salts. Data obtained from [34]

Amphetamine sulfate Amphetamine hydrochloride

Structure

Molecular formula C18H28N2O4S C9H14ClN

Molecular weight 368.492 g/mol 171.668 g/mol

Topological polar

surface area

135 Å2 26 Å2


2.3.2 Analysis tools for amphetamines in laboratories

Guidelines set by the United Nations report recognize that the methodology and analysis method

is to be determined by the analysis method and depend on regional/local specifics but it has been

agreed upon that minimum of at least 2 uncorrelated parameters must be identified. Optimally 3

different techniques are used as for example colour tests, chromatography and UV or IR spectroscopy.

Using gas chromatography-mass spectrometry (GC-MS) enables to determine 2 parameters with this

single technique which is why it is the most commonly used technique in laboratories [35]. Gas

chromatography measures the elapsed time between elution of the vaporized analyte sample on the

selective column walls to separates compound mixtures into molecules and mass spectroscopy

enabling to determine the molecular weight and ion composition of the individual molecules [36].

2.3.3 Analysis tools for amphetamines on-site

A common field test used to detect amphetamine is Marquis test that consists of 10%

formaldehyde in concentrated sulfuric acid [33]. Carbonium ion is formed by formaldehyde and

sulfuric acid, the ion is further stabilized by reaction with the aromatic component of the analyte. The

reaction proceeds in an acidic environment to form a dimer that is oxidized by the trace metals found

in sulfuric acid and is converted into carbonium ion with a characteristic yellowish green-coloured

product. Marquis test gives similar qualitative output to amphetamine and methamphetamine [37].

On-site test to differentiate between primary amine (amphetamine) and secondary amines (e.g.

methamphetamine or MDMA) is enabled by Simon’s reagent. The test reagent consists of sodium

carbonate, acetyl aldehyde and sodium nitroprusside [33]. A secondary amine reacts with

acetylaldehyde to produce initially enamine that further reacts with nitroprusside to form a salt,

which is subsequently hydrolyzed into visibly distinguishable blue Simon-Awe complex [37].

2.4 Related work

The basis of this study relies on the assumption that the amphetamine molecules have some

affinity to the graphene surface and that the amine group affects the conductivity of CVD graphene.

Following sections summarize key publications that were used to formulate the hypothesis

investigated.

2.4.1 Amphetamine affinity to graphene

No studies focusing on amphetamine adsorption on graphene were found, but a theoretical study

on the interaction of amphetamine and carbon nanotubes (CNT) was found. The physisorption of

amphetamine on the single-walled CNT was estimated based on interaction energies calculated using

an all-electron linear combination of the atomic orbital density functional theory in combination with

generalized gradient approximation. The calculation established that oblique mode of adsorption was

most effective with adsorption energies up to -2 kcal/mol. The aromatic structure is estimated to form

an 11 ° angle with the CNT wall and the amine group is located parallel to the surface (figure 2-5) [38].

Based on these results, some physisorption interaction between aromatic carbon structures and

amphetamine molecules is possible.

As this is a theoretical study on defect-free CNTs, transferability of these calculation results to

interaction of amphetamine salts to graphene surface in an aqueous environment is not clear. Any

bound impurities or defects with for example bound oxygen groups or vacancies at dangling bonds

are bound to change the local density of electrons and thus the affinity and adsorption orientation of

binding molecules or elements [39]. The details of orientation and strength of amphetamine


15

adsorption on graphene is highly dependent on the graphene surface quality and the surrounding

environment.

Figure 2-5: Theoretical estimation of amphetamine molecule physisorption on CNT sidewall. Imaged sourced

from [38]

2.4.2 Graphene response to the exposure of n-type donor

The ambipolar semiconductor nature of graphene enables utilizing either type of charge carrier

to change the conductivity. Transferred CVD graphene on SiO2 substrate with inherent impurities and

graphene oxide result in the graphene being p-type doped. As a result, interaction with n-type donor

molecules results in a decrease of charge carriers and an increase in resistance. A common n-type

donor that is detected with graphene-based resistive sensors is ammonia gas – NH3. The adsorption

of gaseous analytes results in chemical doping of the single layer graphene while the scattering rates

are not influenced by these absorbed impurities because the honeycomb crystal lattice is not

disrupted. As the molecules are physisorbed on the surface, small adsorbed amounts on graphene can

be removed without harsh treatments. This was shown by Schedin et. al by showcasing how

conductance of the mechanically exfoliated single graphene flake field-effect transistor behaved when

exposed to NH3, CO, H2O and NO2 gas in concentration 1 part per million (p.p.m.). Additionally, it

was shown how the material regained its initial conductivity after annealing at 150 C and same

reversing response can be obtained by short-term UV treatment [5]. It can be estimated that

interaction with other molecules that behave as n-type dopants, such as amphetamine, would result

in a similar signal.

2.4.3 Signal enhancement by light excitation

Detecting single molecule absorption has been shown in mechanically cleaved graphene devices

that are fabricated using a non-scalable fabrication method of mechanical exfoliation [5]. The more

scalable and cost-efficient graphene production methods results in some inherent impurities that

require sensing optimization to fully take advantage of graphene properties [15]. A study by C.-M.

Yang et. al investigated the changes in monolayer transferred CVD-graphene based resistive sensor

response to acetone gas when combined with UV illumination. UV exposure to p-type doped graphene

has shown to move the Dirac point closer to intrinsic graphene as a n-type dopant would [40]. The

results showed an increase in response to the analyte by 10-fold when the setup was under constant

370 nm illumination. The UV excitation causes the adsorbed oxygen and water molecules at the

surface to detach leaving more of the graphene surface available for analyte binding. Additionally,

long UV exposure is likely to create more dangling bonds at the graphene and SiO2 interface

promoting further analyte adsorption [41].

11°


Previous research focus in the research group, where this thesis is written, investigated

amphetamine-type drugs’ influence on the conductivity of epitaxially grown graphene. To observe the

analyte presence, light with undefined intensity and wavelength was used to excite charge transfer

from analyte molecule to the n-type doped graphene resistor and the immediate current increase in

response to light was recorded. When using a broadband microscope lamp with an excitation

temperature of 2600 K no response was observed while a short excitation pulse of 3000 K resulted in

a sharp current increase [3]. Difference between these excitation parameters can be seen in

significantly higher intensity of light at wavelengths in the range of 300-1800 nm (figure 2-3) [42].

Absorption measurement of charge transfer complexes with the amphetamine-like drug has been

observed considerable response at longest 500 nm illumination, with peak absorption at

approximately 400 nm when combined with suitable acceptor molecule [7]. Considering this, it is

possible that signal obtained by Karlsson et. al. [3] is a result of ionization of amphetamine-type drug

adsorbed on the surface of the graphene by sufficiently powerful <500nm light excitation.

Figure 2-3: Spectrum of tungsten-halogen lamp at different filament excitation temperatures. Image sourced

from [42]

2.5 Summary

Applying nanotechnology in improving novel sensors has been the focus of increasing number of

researchers. The fundamental properties of sensors, selectivity and sensitivity, have been enhanced

through low-cost and scalable graphene-based sensing elements that have been investigated in this

study.

The electronic properties of graphene are well suited for monitoring changes in the proximity of

the nanomaterial. This has made this technology highly suitable for chemical sensors which aim to

detect changes of molecules in the surroundings. Simple resistance-based transducers have enabled

detection of low concentration polar molecules, such as ammonia, or charged particles by detecting

changes in pH. Characteristic conductance changes are expected by interaction with molecules of

certain properties.

Combining the potential of scalable low-cost sensors with the need for improved onsite analysis

techniques in forensic science has determined the analyte of interest in this study -amphetamine. The

amine group in amphetamine molecules is known to behave as an electron donor and graphene

conductivity changes in response to exposure to amphetamine salt solutions are investigated.

Materials and Methods | 17

3 Materials and Methods

The methodology used in the study is reasoned in section 3.1. Preparation of graphene-based sensor

is described in section 3.2. Section 3.3 introduces the material characterization techniques used. The

sensor testing setup and techniques are described in section 3.4 and the following section 3.5

describes how these experimental results were analyzed.

3.1 Research Process

The research was conducted by making the simplest devices possible with minimal interference

with the graphene layer. This method was chosen to avoid impurities that are caused by the chemical

treatment required during patterning of the graphene with standard lithography techniques as well

as during the selective passivation.

Each batch was characterized with surface analysis techniques to verify the quality of the

transferred single-layer graphene. The surface of the wafer may experience different conditions

during the transfer process and have non-homogeneous substrate structure which may affect the

adhesion. Well established graphene single-layer peaks obtained during Raman analysis were used to

determine the quality of the surface. Additionally, topography of the surface was analysed with atomic

force microscopy.

Resistance response to different conditions was measured with the aim to test analyte- and light-

induced response when in contact the graphene transduction element. First, control measurements

were conducted to determine the changes caused by light excitations alone. Secondly, the change

dependence on the surrounding gaseous environment was determined. Finally, resistance change was

measured for the analyte absorption. Control tests were performed on each device before the surface

was exposed to the analyte. If a change in sensor response was observed, the experiment was repeated

to ensure the repeatability of the signal.

3.2 Sensor fabrication

The sensor was fabricated by external collaborators in line with given specifications. A 4’’ 500 m

thick Si wafer was obtained from Si-Mat and mask aligning structures were etched on both sides of

the wafer. On both sides, the outlines of each chip were defined by photolithography and trenches

were sawn using a dicing tool to approximately 150 m depth to ease cleaving of each chip without

damage. The insulating SiO2 layer was thermally grown on the both sides. Oxide thickness was

measured with a laser interferometer (LEITZ MPV-SP) to be approximately 1000±20 nm. Using

photolithography, positions of the sensor electrode pads were etched from the oxide layer to leave

200 nm deep cavities for ensuring stability and minimizing the possible distortion in deposited

graphene over large steps at electrode edges.

Titanium (Ti)/Gold (Au) electrodes were deposited on the wafer by evaporation using a positive

photomask and lift-off process. The thickness of metal contacts deposited was 25 nm of Ti and 200

nm of Au. The step from oxide part to the electrode was measured using the profilometer to ensure

the alignment of previously etched cavities with the designated electrodes. The electrodes and TLM

structures were defined with dimensions and layout seen in figure 3-1. Processing for the control

wafer with sensors without graphene finished with these steps.

A monolayer of graphene was bought from Graphenea on copper (Cu) 4’’ foil. The transfer process

was done using the established process steps provided by the supplier and described in section 2.2.4.

PMMA layer was spin coated onto the graphene single layer on Cu substrate. This was followed by

etching away the Cu layer in FeCl3 solution. The PMMA with graphene is transferred to a water bath

with the final substrate, the patterned Si/SiO2 wafer with electrodes, is placed underneath and raised

18 | Materials and Methods

out of the bath with graphene-PMMA layer on top. The wafer was baked on a hotplate at 45 °C for 10

min. The carrier PMMA structure was removed by immersion in acetone solution for 24 hours. The

structure is secured by annealing the wafer at 45 °C for 10 min to remove trapped water impurities at

the interface. The processed chips were diced using a diamond pen and stored in ambient conditions.

Before each use, the chips were treated with isopropanol and dried in N2 flow.

Figure 3-1: Illustration of the sensor chip electrode dimensions. The green areas represent SiO2 and the teal

coloured areas are the contact pads. CVD graphene was deposited over the whole chip.

3.3 Material Characterization

The surface of the bare and graphene sensor on Si/SiO2 wafer was characterized using Raman

spectroscopy (iHR550, Horiba Jobin Yvon) with 633 nm laser source and atomic force microscope

(Digital Instruments Dimension 3000). Throughout the experiments, 2-point resistance

measurement was performed using a multimeter (Fluke 117 Digital Multimeter) for quick verification

of graphene layer condition. All analysis was performed in ambient conditions. These methods were

chosen based on the availability of the tools and reference data from previous publications

3.4 Experimental design for sensor

This section describes the measurement setup and how it was used during the testing. Equipment

models, material specifications and experimental conditions are included in detail.

3.4.1 Test environment

The electrical measurement setup, Agilent 34970A Data Acquisition unit combined with Keithley

2602A amperometer, was combined with a flow dynamic system that utilized 2 Harvard Aparatus 11

pico plus Elite syringe pumps for pumping solvent or analyte solution over the active sensing area

between the electrodes. The fluids were constrained within a polydimethylsiloxane (PDMS) flow-

chamber mounted on the sensor with a poly(methyl methacrylate) (PMMA) lid including the inlet

and outlet openings (figure 3-2). The tubing used was microfluidic PEEK tubing (IDEX Health and

Service LLC). Measurements were performed under a continuous flow of either 2 or 20 l/min. This

setup was used unchanged during most of the presented results unless otherwise stated.

The amphetamine sulfate and amphetamine hydrochloride analytes were provided by the

Swedish National Forensic Centre (NFC). All analytes were measured out and diluted in diH2O to

obtain the stated concentration (1 mg/ml-10 mg/ml) immediately before the measurement. Validity

8000 m

5900 m

6000 m

5700 m

Materials and Methods | 19

19

test was performed in 0.01x phosphate buffer saline (PBS) solution (Sigma-Aldrich). Any light

exposure to the analyte solution was minimized by keeping the analyte container in foil wrapping and

doing the experiments in dark. The background solution and analyte solution switching was done by

an automatic system following the following pattern:

1) 5 min background solution

2) 20 seconds analyte solution










Figure 3-2: Experimental setup for fluidic resistance change measurements. A) Illustrative schematic of the

setup with the devices connected. B) Illustration of the sensor setup with marked components: 1

– stage, 2- conductive chip holder, 3- the chip with the graphene-based transducer element, 4 –

PDMS cavity forming the solution chamber, 5 – PMMA lid with epoxy secured inlet and outlet

tubing, 7 – PEEK microfluidic tubing. C) Photograph of the sensor. Image adapted from [3]

3.4.2 Hardware/Software to be used

The data was recorded using Labview software. The analysis from raw data was done using

Microsoft Excel or OriginPro 8.5, the latter was also used for plotting the results.

3.4.3 Experimental environment optimization

Two methods were tested to improve the sensing signal amplitude. First, light excitation was enabled

by exposing 355nm LED or 470 nm Blue LED Array Light Source (Thor Labs) at approximately 4-8

cm distance from the device. Each light source wavelength range was characterized with StellarNet

EPP2000-UVN-SR Super range spectrometer with SpectraWiz software and Newport The Model

2832C DualChannel Power Meter for intensity measurements. To ensure the response only from

analyte to each light source, current changes were monitored during light exposure when no analyte

was present in the setup.

The second method used for optimizing the signal is based on turning the resistor-based system

into a field-effect transistor (FET) via utilizing the inherently slightly doped Si substrate as a back-

gate electrode. The same electrical measurement system was used with an additional gate electrode

connection to the conductive chip holder. The resistance between the electrodes and conductive

holder was measured with the multimeter before to ensure the chip suitability for the transistor. To

ensure the electric connection between the holder and substrate, a diamond pen was used to remove

some of the intrinsic silicon oxide layer on the back of the wafer and gallium–indium eutectic paste

was applied between the substrate and conductive holder. By applying a potential on the substrate

20 | Materials and Methods

acting as a gate, the Fermi energy in the graphene structure can be optimized. As the doping level is

unknown, the Dirac point was measured by sweeping the gate voltage and constant source-drain bias

potential of 50 mV. To ensure the integrity of the transistor, the leakage current was constantly

measured.

3.5 Assessing the reliability and validity of the data collected

To evaluate the reliability of these experiments the quality and consistency of the fabricated

sensor characteristics were compared. Raman spectroscopy and ohmmeter measurements were

conducted on chips from different wafer parts. Reliability of the sensing measurements was estimated

by repeating the same measurements of several chips.

The validity of the sensing measurements was ensured by minimizing the number of changed

variables during the analyte exposure. The experimental setup was secured and signal stabilized

before each experiment, the switching from baseline solution to the same solution containing the

analyte was controlled through a computer interface. When testing the potential signal enhancement

methods, light excitation or back gating, the response was monitored for blank samples first to

determine the magnitude of signal caused by the optimization alone. The signal magnitude during

analyte exposure was compared to determine the suitability of the methods for valid sensing.

Results and Analysis | 21

4 Results and Analysis

In this chapter, first the characterization results are presented with comparative analysis based

on previously published studies. Secondly, the selected results from sensing experiments are shown

and discussed. The following section with reliability and validity analysis discusses the results from

all experiments with explanations for potential artefacts. Finally, the results from characterization

and sensing are combined to explain the signal response.

4.1 Sensor characterization

The chips with the graphene transduction element were analyzed before they were used as

chemical sensors. Raman spectroscopy, atomic force microscopy and resistance measurement results

are analyzed and compared to published results in the following sections.

4.1.1 Raman spectroscopy

Raman spectroscopy analysis was done on 5 randomly selected sensors. The characteristic graphene

peaks were visible after all measurements. Figure 4-1 A shows how CVD graphene spectroscopy

results compare with chemically exfoliated graphene and blank substrate samples. The transferred

CVD graphene show clear peaks at 1597 cm-1 and 2647 cm-1 with >5 times intensity difference. The

chemically exfoliated graphene shows a considerable peak at 1340 cm-1 indicating a significant

amount of defects and impurities in the material. The double peak at 1585-1615 cm-1 is caused by G

resonance and high defect concentration [23].

Figure 4-1: Raman spectroscopy results: A) Comparison of CVD graphene with blank wafer and graphene

ink on the same substrate. B) Analysis of characteristic graphene G and 2D peaks with individual

offset, peak locations were determined by Gaussian fit and averaged over 5 sensors, intensity

ratio is determined from raw data.

As previous publication have stated, Raman peaks for intrinsic graphene are most prominent at

approximately 1580 cm-1 and 2650 cm-1 for characteristic G and 2D peaks [20, 23]. The measurements

on transferred CVD graphene show a considerable redshift which has been associated with p-type

graphene [22]. The substrate material, transferring process and storage conditions bring the

graphene layer into direct contact with SiO2 oxide species, H2O molecules in liquid as well as in the

atmosphere, PMMA molecules and atmospheric oxygen. These molecules have shown to be affected

by graphene by localizing the holes thus behaving as p-type dopants [5, 17, 39].

1000 1200 1400 1600 2600 2800 3000

2675

1615

1585

1340

Gink

CVD_graphene

noCVDchip

Inte

nsity

w. y-o

ffse

t

Raman shift [cm^-1]

1338

1597

Characteristic graphene peaks

2647

A

1540 1560 1580 1600 1620 2620 2630 2640 2650 2660 2670 2680

0

50

100

150

200

250

300

350

400

450Intensity(2D/G)=2.77±0.67

Xc=

2651

.0±1

.1

Inte

nsity

Raman shift [cm^-1]

Xc=

1597

.7±4

.9

B

22 | Results and Analysis

4.1.2 Atomic Force Microscopy

Results from AFM images showcased how the sensor surface is easily contaminated and difficult

to clean. Figure 4.2 A, B, D, E showcase the smoothened raw data results. The samples were cleaned

by rinsing with diH2O and IPA, followed by drying in N2 flow. Still, a considerable amount of

impurities can be seen on the surface. Comparing values for commonly used roughness parameters,

Ra and Rq, an analysis of the 10*10 m images, the bare substrate roughness seems significantly lower

compared to graphene. Analysis of the higher magnification images does not result in a large

difference between the 2 surfaces and the overlapping error bars showing the standard deviation

between different areas indicate the roughness between the 2 surfaces is the same. Published results

in a controlled vacuum environment have shown how the deposition of a graphene layer on the

substrate decreases the surface height variations and thus roughness [26]. The same conclusion

cannot be made based on the results of this study as the tested surfaces here were likely strongly

affected by high particle content in ambient conditions in which the devices are stored and tested in.

As these impurities remained after the surface was cleaned following the standard protocol, they are

presented during the sensor response measurements as well.

Si/SiO2 control Si/SiO2+CVD graphene Roughness analysis

Figure 4-2: AFM analysis results A) control Si/SiO2 wafer 10m*10m area. B) CVD graphene on Si/SiO2 wafer

10m*10m area. C)Average surface roughness parameters and deviation determined from selected

5 different areas in image A and B. D) control Si/SiO2 wafer 500nm*500nm area. E) CVD graphene

on Si/SiO2 wafer 500nm*500nm area. F)Average surface roughness parameters and deviation

determined from selected 5 different areas in image D and E. Rq – root mean square average of

profile height; Ra – arithmetic average of profile height deviations.

Rq Ra

0.0

0.5

1.0

1.5

2.0

Ro

ug

hn

ess [n

m]

Analysis method

Si/SiO2

+CVD graphene

Si/SiO2

Rq Ra

0.0

0.2

0.4

0.6

Ro

ug

hn

ess [n

m]

Analysis method

Si/SiO2

+CVD graphene

Si/SiO2

A B C

D E F


23

4.1.3 Resistance measurements

The resistance of the transducer area was measured before testing with the analyte. By placing

the multimeter probes on electrodes average resistance of 10 sensors was 1111.2 ± 55.3 Ω. However,

after mounting the chips in the sensor setup, the average resistance values obtained from 10 sensors

was 2813.9 ± 1310.2 Ω. The latter values were calculated from current values measured by electrical

measurement setup at 50 mV bias. The sensor setup resulted in much larger deviation and higher

resistance values for the transducer area.

The reason for this significant change can be estimated to be caused by the impurities introduced

to the surface while mounting the sensor with PDMS fluidic chamber and PMMA lid. Polymer

residues on graphene surface are known to degrade the electronic properties and for optimal

performance [19], additional cleaning steps are introduced to remove any impurities [43]. However,

as these components are required for incorporating the fluidic system used during these

measurements, these effects can only be minimized by careful mounting procedure and being as

precise as possible to minimize friction between the PDMS and graphene surface when securing the

lid.

Another feature of the setup that may cause the difference in resistance is that when securing the

lid and chamber, the pressure is applied on the graphene surface. The single layer nanomaterial is

highly sensitive to applied forces and several research groups have established the increase in

resistance with applied strain [44–46]. To limit the variation caused by the difference in pressure

applied while securing the lid, the manually securing by 2 screws should be replaced by an automatic

system or the graphene-based transducer can be incorporated in a fluid cavity during fabrication. The

latter would also minimize the contamination from surroundings and polymer fluidic chamber.

When incorporating the chip into the sensor setup, part of the sensor surface will be exposed to

water. The dipole moment of adjacent water molecules can shift the local Fermi level of the graph and

increase the conductivity through doping. At defect sites, the charge density difference between the

graphene surface and substrate interface is larger and thus enhanced charge transfer with the

adsorbed dipole is estimated to occur [47]. The concentration of graphene defects can vary between

the chips and as a result, the response to water exposure can result in variation in surface conductivity

further explaining the reason behind large deviation in graphene properties once incorporated into

the fluidic setup.

Measuring resistance of the transduction element showed significant variation in conductivity

before being introduced to the analyte of interest. These changes can be attributed to the sensor setup

that requires manually mounting polymer structures on the chip which inevitably introduces changes

to the electronic properties of graphene that are difficult to quantify and precisely define.

4.2 Sensor testing

The experimental results measuring the current change in response to exposure to amphetamine

salts is presented. The data presented in this section contains the strongest and repeatable signal

obtained during this study. Response to the analyte with and without light excitation is included.

Testing the chips in a transistor mode with back-gating is showed and discussed.

4.2.1 Response to analyte

The signal in response to analyte injection was observed in some sensors. The transferred CVD

graphene surface exhibited a repeatable negative signal (current decrease, resistance increase) in

response to amphetamine salt solution exposure. Amphetamine sulphate solution resulted in

response of ∆I≈1o0nA for 1mg/ml concentration and ∆I≈150nA for 5mg/ml concentration with


relative current change from 0.8% to 1.2% respectively. As measured noise was approximately Inoise=5

nA, the signal to noise ratio was 20 for low concentration solution. Amphetamine hydrochloride

solution gave a significantly stronger signal with maximum ∆I=800nA for 1mg/ml and ∆I=700nA for

5mg/ml with the relative current change from 4% to 3.5% respectively. The noise was approximately

the same thus the signal to noise ratio was about 140.

The increase in resistance (resulting in lower current) is in agreement with the estimation that

amphetamine would behave as an electron donor and due to opposite doping of CVD graphene

compared to epitaxial graphene on SiC substrate, the response is coherent with previously published

results [3]. However, the significantly higher response to hydrochloride salt is surprising as the molar

concentration of 1mg/ml amphetamine in amphetamine sulphate is 5.4 M while in 1 mg/ml

amphetamine hydrochloride it is 5.8 M which should not result in such significant difference. At

higher concentrations, 5mg/ml amphetamine sulphate solution is 13.57 M amphetamine while the

same concentration of amphetamine hydrochloride results in 29.12 M of amphetamine. It can be

estimated that the response difference between different concentrations of amphetamine solution

does not increase linearly with the increased analyte concentration. Further research is required to

support this theory.

The shape of the signal response is estimated to follow the binding curve of Langmuir adsorption

kinetics with exponential conductivity decay until equilibrium is achieved [48]. During these

experiments the full curve was not observed indicating the adsorption equilibrium takes over 320

seconds. In addition, several analyte exposure curves follow an unknown characteristic that is

inconsistent during repeated measurements. At section 47min-50min of graph A, 17-20min section

of graph B, section 31-33 min and 44-48 min of graph D on Figure 4-3. As these abnormalities are not

consistent, it can be estimated they are caused by unwanted air bubbles that may be trapped in the

fluidic setup from changing the liquids or from changes in tightness of fluidic connections. It is also

possible that the analyte solution can contain ionic impurities and undissolved crystals.

Figure 4-3: Electrical measurements of graphene-based transducer response to amphetamine salts. A)

Signal to 1 mg/ml amphetamine sulfate; B) Signal to 5 mg/ml amphetamine sulfate; C) Signal to

1 mg/ml amphetamine hydrochloride; D) Signal to 5 mg/ml amphetamine hydrochloride. All

measurements were done in dark, with applied 50 mV bias and 20l/min flow rate.

10 20 30 40 50 60

12.86 uA

12.88 uA

12.90 uA

12.92 uA

12.94 uA

12.96 uA

12.98 uA

13.00 uA

13.02 uA

13.04 uA

50 mV bias, 20 ul/min flow rate

Cu

rre

nt

Time [min]

diH2O

1 mg/ml AmpSul

0 10 20 30 40 50

12.40 uA

12.45 uA

12.50 uA

12.55 uA

12.60 uA

12.65 uA

12.70 uA

12.75 uA


Cu

rre

nt

Time [min]

diH2O

5 mg/ml AmpSul

0 10 20 30 40 50

18.8 uA

18.9 uA

19.0 uA

19.1 uA

19.2 uA

19.3 uA

19.4 uA

19.5 uA

19.6 uA

19.7 uA

19.8 uA

19.9 uA

20.0 uA

20.1 uA

20.2 uA

Cu

rre

nt

Time [min]

diH2O

1mg/ml AmpHCl

94

95

96

97

98

99

100


I/I_

ma

x [%

]

0 10 20 30 40 50

18.5 uA

18.6 uA

18.7 uA

18.8 uA

18.9 uA

19.0 uA

19.1 uA

19.2 uA

19.3 uA

19.4 uA

19.5 uA

Cu

rre

nt

Time [min]

diH2O

5mg/ml AmpHCl

95.5

96.0

96.5

97.0

97.5

98.0

98.5

99.0

99.5

100.0


I/I_

ma

x [%

]

A B

C D


25

Distinguishable and repeatable response to analyte solution is detected, but the origin of response

is yet to be determined. The analyte solution is known to have slightly acidic pH and previous studies

have shown that acidic solution can behave as a n-type dopant when exposed to transferred CVD

graphene on SiO2 [6]. Further experiments in neutralizing buffer solution are presented in the validity

analysis. Nevertheless, more in depth investigation is required to determine the response mechanism

and validity as an amphetamine sensing device.

4.2.2 Response to light excitation

The graphene resistor response to illumination showcases strong dedoping behaviour. The

current change in response to the exposure of UV light of 365 nm at relatively low intensity, figure 4-

4 A, and UV-vis 470 nm higher intensity, figure 4-4 B, illumination was observed and the changes

follow exponential decay characteristics. This result is explained by reactions with adsorbed oxygen

at the graphene surface and dangling bonds at the interface. The UV light exposure generates an

electron-hole pair. The surface of the graphene is known to contain several negatively charged

impurities, such as O2- and H2O-, that are likely to recombine with the generated holes enabling these

molecules to neutralize and possibly detach from the surface. This reaction leaves an unpaired

electron into the graphene surface resulting in n-type doping and conductance decrease in the p-type

transducer [40]. The desorption and adsorption reaction is reversible and once the UV light is

removed, the sensor recovers its initial conductivity [41, 47]. The results obtained in this study agree

with the published results.

To show the role of oxygen species in the response, experiments were conducted in ambient

conditions with approximately 21.6% oxygen and in N2 chamber under constant flow. The current

response in UV caused by desorption of impurities should be faster when the surrounding

environment contains less oxygen [49]. The results presented in figure 4-4 A showcase how the

current decay is faster and with higher magnitude in N2 environment as expected. In addition,

recovery of the conductance is considerably slower after UV excitation is stopped compared to

ambient conditions. Studies with signal enhancement in CVD graphene devices by UV excitation

exposed the analyte in a gaseous state in vacuum or inert environment to minimize the signal

difference due to ambient reactive impuritites [30, 41]. Response to UV light is influenced by the

adsorbed oxygen species and other impurities.

Figure 4-4: Electrical measurements of graphene-based transducer response to light excitation. A) Current

change in illumination at 365 nm with intensity of 400 W/cm2 when the dry graphene surface

was exposed to ambient conditions and in N2 flow. B) Current change in illumination at 470 nm

with intensity of 9.6 mW/cm2 when the graphene surface was incorporated into the fluidic system

with diH2O.

0 20 40 60 80 100

85

90

95

100

50 mV bias, dry sample

UV off

I/I_

ma

x [%

]

Time [min]

atmosphere

N2 chamber

UV 365nm

Intensity ~ 400W

0 10 20 30 40 50 60 70

80

90

100

I/I_

ma

x [%

]

Time [min] 50 mV bias, 20 ul/min flow rate

Light off UV-Vis 470 nm

Intensity ~ 9.5 mW

UV-Vis 470 nm

Intensity ~ 9.5 mW

A B


Publication with amphetamine-type analyte response enabled by light excitation used epitaxially

grown graphene on SiC substrate that has minimal defects at the interface and surface resulting in no

response to light excitation without analyte [3]. However, in devices used for this study, the resistance

change caused by the initial illumination is too dominating compared to the analyte response

presented in the previous section. Due to this, the analyte response was tested in constant

illumination once the response to the excitation light had become relatively stable. The same device

was studied in results shown in figure 4-3 D, figure 4-4 B and figure 4-5. The response to

amphetamine hydrochloride changed from 700 nA to 550 nA. The relative change in current response

is approximately the same (3.3 %). The response to the same concentration of analyte was not

increased by UV excitation.

Figure 4-5: Electrical measurements of graphene-based transducer response to analyte in constant

illumination at 470 nm with intensity of 9.6 mW/cm2.

4.2.3 Response to back gating

Shifting the graphene potential towards the Dirac point through gating mechanism has been shown

to successfully increase the signal in previous studies [5]. The resistor-based transducer was

converted into a transistor if there was no electrical contact between the electrodes and substrate. Out

of 9 tested devices, only 2 showed too high resistance between the electrodes and substrate to be

measured with the multimeter. During the characterization of these devices with the electrical

measurement unit, a significant leakage current was observed (figure 4-6). When applying 10 V gate

potential leakage current quickly increased over 1 A. The origin of this result is unknown as the

insulating oxide layer thickness is over 800 nm and similar devices with thinner insulating layer have

shown to be successful. Further research is required to enable converting these devices into field effect

transistors.

Figure 4-6: Electrical measurements of the tested field-effect transistor. IS-source-drain current; IG – gate

current; VG – gate potential; V_ds – source-drain bias potential

10 20 30 40

13.5 uA

14.0 uA

14.5 uA

15.0 uA

Cu

rre

nt

Time [min]

diH2O

5mg/ml AmpHCl

92

93

94

95

96

97

98

99

100

101

I/I_

ma

x [%

]


-10 -5 0 5 10

30 uA

32 uA

34 uA

36 uA

IS

VG V_ds=50mV

-5 uA

0 uA

5 uA

10 uA

IG


27

4.3 Reliability Analysis

The reliability of the presented results is highly dependent on the graphene layer quality and

consistency of the whole sensor setup. For example, a very low and high response to same

concentration of amphetamine salt solution was detected when using different chips. For example, 4

sets of results are presented in figure 4-7. Results in A show no signal response, results in B show very

high response of almost 3 A (18%) compared to 550 nA (3%) in results presented in previous section,

results in C show response 2.5 times smaller response with twice as high noise and results in D show

opposite response with increased conductance. Comparing the signal magnitude and enhancement

by additional light excitation between experiments done on different chips gives very inconsistent

results. This can be caused by changes in impurities adsorbed on the graphene surface and variability

in sensor assembly with a fluidic system.

Figure 4-7: Inconsistency of electrical measurements’ results of graphene-based chemical sensor response

to amphetamine. A) Response to amphetamine sulphate in constant UV excitation (365 nm, 400

W/cm2.B) Strong response to amphetamine hydrochloride. C) A weak response to amphetamine

sulphate with increased noise. D) Opposite current response to amphetamine sulphate.

The significant difference in current response exhibited by changing the transducer chip made

obtaining comparable results impossible. Due to this, the analyte response results presented in the

previous section are all performed on the same device with minimal changes to the setup. The was

reversibility of the response enabled to conduct multiple experiments on the same device. However,

the surface of graphene may have been influenced by earlier analyte exposure without significant

changes to the signal and based on these results it is not possible to ensure the reversible nature of

the response. To ensure the reliability of results, the graphene layer properties must be minimally

influenced, and the sensor system setup must be improved.

0.00 10.00 20.00 30.00 40.00 50.00

17.75 uA

17.80 uA

17.85 uA

17.90 uA

17.95 uA

18.00 uA


Cu

rre

nt

Time [min]

diH2O

5mg/ml AmpSul

0 500 1000 1500 2000 2500 3000 3500

5.0 uA

5.1 uA

5.2 uA

5.3 uA

5.4 uA

5.5 uA

5.6 uA

5.7 uA

5.8 uA

Cu

rre

nt

Time [s]

3 mg/ml Ampetamine Sulfate

diH2O


C D

0 2000 4000 6000 8000 10000 12000 14000

10 uA

12 uA

14 uA

16 uA

18 uA

20 uA

22 uA

24 uA

26 uA

28 uA

30 uA

Cu

rre

nt

Time [s]

diH2O flow

AmpSul 0.1 mg/ml flow

AmpSul 7.7 mg/ml flow

UV induced changes in ambient conditions with fluidic setup

UV off UV 365 nm

10 20 30 40 50 60

15 uA

16 uA

17 uA

18 uA

19 uA

20 uA


Cu

rre

nt

Time [min]

diH2O

5mg/ml AmpHCl

80

85

90

95

100

I/I_

ma

x [%

]

B A

C


4.4 Validity Analysis

To ensure the observed changes were caused by the solution changing, measurement with diH2O

in both syringe pumps was conducted and results are shown in figure 4-8 A. Minimal changes are

observed when switching between the two syringes. These results prove that the change in

conductance is unlikely to be caused by the fluidic setup and must be caused by the difference in the

chemical composition of the liquids.

Figure 4-8: A) Control measurement of current response to same solution in 2 separate syringe pumps. B)

Control measurements for analyte response in 0.01PBS buffer solution.

To evaluate if the change was caused due to change in the pH of the analyte solution, a set of

experiments was done using 0.01xPBS buffer solution as the background signal and solvent.

Repetitive signal of similar magnitude as in diH2O solvent, 150 nA, was observed in buffer solution

(figure 4-8 B). These results imply the signal is caused by interactions with the amphetamine

molecules in the analyte solution and not due to the change in pH, but further studies are required to

ensure the buffer capacity is substantial for neutralizing the analyte salt.

The response to analyte should increase with increased concentration. Response to significantly

different concentration of amphetamine hydrochloride is shown in figure 4-9. The same device

showed a 50 % increase in signal strength (an increase from 1 A to 1.5 A) in response to over 3-fold

increase of analyte concentration. These results exhibit how the signal increases as expected in

response to an increase in analyte concentration. However, the response kinetics do not show

characteristic exponential decay response as expected from adsorption of chemical compounds [49].

More experiments are required to ensure the observed signal is a result of amphetamine exposure.

Figure 4-9: Electrical measurements of graphene-based transducer response to amphetamine hydrochloride

of different concentration: A) 2.8 mg/ml, B) 10 mg/ml.

0 10 20 30 40 50

24.6 uA

24.8 uA

25.0 uA

25.2 uA

25.4 uA

25.6 uA

25.8 uA


Cu

rre

nt

Time [min]

Syringe 1

Syringe 2

A B

0 10 20 30 40 50

12.2 uA

12.4 uA

12.6 uA

50 mV bias, 20 ul/min flow rateC

urr

en

tTime [min]

0.01xPBS

5mg/ml AmpSul

97

98

99

100

I/Im

ax [%

]

A B


29

4.5 Summary

The graphene surface characterization and sensor resistance change measurements supported

the previously reported p-type doped graphene properties after transferring CVD graphene onto SiO2

substrate. Raman spectroscopy results ensured that the single-layer graphene had retained its quality

during the transferring process. The characteristic G and 2D peaks commonly used for determining

graphene were clearly observed with minimal traces of defect states. Peak positioning towards higher

wavenumber was coherent with previous studies of CVD graphene on SiO2 substrate and is related to

the p-type doping of the nanomaterial due to oxygen and water-based impurities at the surface as well

as interface. A similar conclusion was made based on the measurement of current response difference

when the graphene surface was exposed to UV illumination in ambient and N2 environment. Oxygen

and other defects behaving as electron acceptors have a significant influence on the performance of

the graphene devices investigated during this study.

The devices were stored, and the measurements were performed in ambient environment leaving

the sensing element exposed to impurities. The surface topology characterization by roughness

measurements shows larger variation in surface height than expected proving that even analysis of

500*500 nm image shows the minimal difference between the substrate with and without graphene.

The large variation in resistance measurements indicates there is a large variation in surface quality

between different chips which is likely to be caused by the difference in surface impurities.

Additionally, the low reliability of analyte response can be attributed to impurities that strongly

influenced the quality of the surface. To enable repeatability of results and predictable analyte

response, the surface of the sensor element should be enclosed and kept in a highly controlled

environment.

The sensor successfully detected the presence of amphetamine salts in diH2O. The graphene

surface conductance was decreased when analyte was present indicating the expected n-type doping

nature of the amine groups in amphetamine. Separating the analyte response from pH changes by

changing the solvent into buffer solution verified that signal response was not induced by general pH

change in analyte solution. Further research and device development are required to ensure and

explain how the resistance change is caused by the interaction with analyte molecules.

Influence of light excitation on the device response was investigated. While illumination with light

had a significant effect on the graphene conductivity without analyte, the relative signal magnitude to

analyte exposure did not change. Due to the large variation in signal response, the number of

comparable experiments was limited to this single experiment thus the effectiveness of this technique

cannot be concluded. In addition, this study was limited to investigating the effect of sub-500nm

wavelength light excitation. As broadband light has enabled to detect amphetamines in previous

studies, other excitation light regions should be investigated.

To summarize, the experiments conducted during this study showcased the feasibility of detecting

amphetamine salts by measuring resistance change in a graphene-based transducer. This result was

obtained despite a considerable amount of impurities on the graphene surface as shown by atomic

force microscopy, large resistance variation and inconsistent analyte response. Improved control of

the transducer properties is likely to result in increased response and reliability of the sensors.

Conclusions and Future work | 31

5 Conclusions and Future work

This final chapter describes the conclusion made based on the experimental results and literature

review. Limitations caused by the sensor setup are discussed and solutions are proposed to improve

the reliability and validity of the sensing mechanism.

5.1 Conclusions

Resistance based chemical sensors were successfully fabricated by cost-effective transferred CVD

graphene on SiO2 substrate. The produced transduction element enabled to detect a signal when

exposed to amphetamine salts in liquid. The expected n-type doping behavior, characterized by the

resistance increase in the inherently p-type doped graphene resistor, was observed. Strongest

recorded current change per analyte concertation was approximately 0.1 A/(mg/ml) for

amphetamine sulphate and 0.33 A/(mg/ml) for amphetamine hydrochloride. The response to

analyte in water as well as buffer solution was obtained to ensure validity. These results provide a

basic proof-of-concept that graphene-based resistive sensors can be utilized in forensic science for

detection of amphetamine.

However, for utilizing these devices in commercial applications, further work is required. The

results obtained during this study had large variability in response magnitude and type. The

characterization results indicated there are inherent differences in the sensor system properties and

resultingly the single-layer graphene transducer’s surface was difficult to control. It can be estimated

that an improved and more consistent setup design as well as controlled impurities on graphene

would enable to provide reliable sensors. In addition, the proposed signal enhancement methods,

through 470 nm light excitation and back-gating, can be further investigated through optimized

experimental design and different variables. The sensors fabricated and characterized in this study

showed potential as amphetamine detectors, but further research is needed to provide consistent

performance that would satisfy the basic requirements for on-site forensic analysis.

5.2 Future work

Several limitations were found in the methodology of this study and the drawbacks of the

experimental setup used clearly influence the analysis of results. Major improvements in the sensor

design are required to improve the reliability of results and enable quantitative analysis of the sensor

response. To enable use as intended on-site amphetamine sensor, selectivity is a major requirement

which is not investigated in this study at all. In addition, alternative signal enhancement strategies

used in previous studies can possibly increase the sensitivity and enable selectivity of the graphene-

based transducer. The following points are proposed to be the focus of future studies investigating the

suitability of graphene-based resistive sensors for amphetamine detection:

• Integration of the fluidic system on active graphene surface and passivation of the remaining during

fabrication in the cleanroom facilities to ensure minimal contamination of the surface and variation

between devices.

• Investigating options for modifying the graphene surface to increase affinity to amphetamine

molecules for a selective response.

• Adsorption and desorption kinetics evaluation based on the conductivity change in response to UV

excitation (desorption of oxygen species) and to analyte exposure (adsorption of amphetamine)

[50].

• Improving the sensitivity of graphene by increasing the number of defects in a controlled fashion

by substrate patterning or incorporating nanoparticles on the surface [30, 50, 51].

32 | Conclusions and Future work

• Enhancing the signal response by shifting the Fermi energy in the inherently p-type doped graphene

monolayer through electrolyte gating [50, 52].

• Evaluating the substrate conductivity changes and analyte response magnitude difference in

response to light excitation at wavelengths >500 nm with illumination intensities comparable to a

broadband microscopy lamp [30].

References | 33

References

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