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Citation: Kumar, R. (2020). Development of novel optical fibre sensors based on
upconverting and gold nanoparticles. (Unpublished Doctoral thesis, City, University of
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Development of Novel Optical Fibre Sensors
based on Upconverting and Gold Nanoparticles

Submitted by

Rahul Kumar
Thesis submitted for the degree of Doctor of Philosophy
Supervised byProfessor Tong Sun
andProfessor Kenneth T.V. Grattan

City, University of London
School of Mathematics, Computer Science and Engineering
EC1V 0HB, London, UK
September 2020

Table of Contents

Table of Contents
Table of Contents ...................................................................................................................... i
Table of Figures....................................................................................................................... vi
Table of Tables .......................................................................................................................xii
Acknowledgement ................................................................................................................ xiii
Copyright Declaration .......................................................................................................... xiv
Abstract................................................................................................................................... xv
Glossary of Abbreviations, Symbols and Chemicals ......................................................... xvi
Chapter 1 .................................................................................................................................. 1
1.1 Background ...................................................................................................................... 1
1.2 Aims and objectives of this work..................................................................................... 4
1.3 Structure of the thesis....................................................................................................... 5
1.4 Summary .......................................................................................................................... 6
Chapter 2 .................................................................................................................................. 7
2.1 Introduction ...................................................................................................................... 7
2.2 Nanoparticles ................................................................................................................... 8
2.2.1 Classification............................................................................................................. 8
2.2.2 Synthesis methods ................................................................................................... 11
2.2.3 Characterization techniques .................................................................................... 15
2.3 Upconverting nanoparticles ........................................................................................... 19
2.3.1 Introduction ............................................................................................................. 19
2.3.2 Choice of host lattice .............................................................................................. 21
2.3.3 Choice of dopant ..................................................................................................... 24
2.3.4 Improvement of upconversion efficiency ............................................................... 31
2.3.5 Applications of upconverting nanoparticles ........................................................... 35
2.4 Gold nanoparticles ......................................................................................................... 47
2.4.1 Introduction ............................................................................................................. 47iTable of Contents
2.4.2 Localized surface plasmon resonance ..................................................................... 48
2.5 Summary ........................................................................................................................ 49
Chapter 3 ................................................................................................................................ 50
3.1 Introduction .................................................................................................................... 50
3.2 Experimental section ...................................................................................................... 52
3.2.1 Chemicals and reagents........................................................................................... 52
3.2.2 Thermometer materials characterization – instrumentation used ........................... 53
3.2.3 Synthesis of UCNPs & UCNPs-PDMS composites ............................................... 53
3.2.4 Optical fibre thermometer design ........................................................................... 55
3.2.5 Optical thermometer characterization setup ........................................................... 56
3.3 Results and discussion ................................................................................................... 59
3.3.1 Characterization of the thermometer materials ....................................................... 59
3.3.2 Temperature response of UC powder-based thermometer ..................................... 62
3.3.3 Temperature response of UCNPs-PDMS composite based thermometer .............. 64
3.3.4 Comparison of performance with previously reported sensors .............................. 66
3.4 Summary ........................................................................................................................ 69
Chapter 4 ................................................................................................................................ 70
4.1 Introduction .................................................................................................................... 70
4.2 Methodology .................................................................................................................. 71
4.2.1 Chemicals and apparatus used ................................................................................ 71
4.2.2 Characterization instruments .................................................................................. 71
4.2.3 Synthesis of GNPs .................................................................................................. 72
4.2.4 Sensor preparation process ..................................................................................... 72
4.2.5 Characterization setup for solution refractive index and heavy metal detection .... 74
4.2.6 Modelling technique ............................................................................................... 75
4.3 Results and discussion ................................................................................................... 75
4.3.1 Characterization of GNPs ....................................................................................... 75ii

Table of Contents
4.3.2 Refractive index response of GNPs-coated fibre probe .......................................... 76
4.3.3 Heavy metal ion detection ability of GNPs-coated fibre ........................................ 77
4.3.4 Lead ion detection using MUA-incorporated GNPs coated fibre ........................... 78
4.3.5 Performance comparison with prior work .............................................................. 81
4.4 Summary ........................................................................................................................ 81
Chapter 5 ................................................................................................................................ 82
5.1 Introduction .................................................................................................................... 82
5.2 Background theory and algorithm formulation.............................................................. 84
5.3 Methodology .................................................................................................................. 88
5.3.1 Chemicals ................................................................................................................ 88
5.3.2 Chemical synthesis.................................................................................................. 89
5.3.3 Characterization ...................................................................................................... 89
5.4 Results and discussions .................................................................................................. 90
5.4.1 Comparison with TEM measurement ..................................................................... 90
5.4.2 Comparison with DLS measurement ..................................................................... 92
5.4.3 Theoretical Benchmarking of the algorithm ........................................................... 93
5.4.4 Application on additional synthesized samples ...................................................... 95
5.5 Summary ........................................................................................................................ 97
Chapter 6 ................................................................................................................................ 98
6.1 Summary of the work..................................................................................................... 98
6.2 Proposal for future works............................................................................................. 100
References ............................................................................................................................. 102
Appendix 1 ............................................................................................................................ 133
Appendix 2 ............................................................................................................................ 136
Appendix 3 ............................................................................................................................ 141
List of Publications .............................................................................................................. 143
Journal Papers .................................................................................................................... 143iii

Table of Contents
Conference Papers ............................................................................................................. 143iv

Dedicated to my grandfather B.D. Mishra
andparents D.S. Mishra and Geeta Mishrav

Table of Figures

Table of Figures
Figure 1. 1: The Lycurgus cup. Left and right images show the colour of cup when it isilluminated from outside (under reflection) and inside (under transmission) respectively. The
man illustrated in cup is the mythological King Lycurgus who is being dragged into theunderworld by Greek nymph Ambrosia, disguised in form of vine [1]..................................... 2

Figure 2. 1: Nanoparticles Classifications [20].......................................................................... 7
Figure 2. 2: (a) Schematic representation showing the splitting of energy levels in QDs andincrease in the band gap due to decrease in size [30]. (b) Photoluminescence of CdSe QDs
showing blue shift of emission on decreasing their diameter. These colloidal solutions are
excited with broadband UV source [31]. ................................................................................... 9
Figure 2. 3: Schematic showing (a) Perovskite having a ABX3 structures, where A is an organic(e.g. CH3NH3+) or alkali metal (e.g. Cs+) cation, B is a divalent metal cation (e.g. Pb2+, Sn2+)and X is halide anion (e.g. Cl-, Br-, I-)[40] (b) Metal Organic Frameworks (MOF) [43]. ...... 10
Figure 2. 4: (a) Schematic diagram showing core-shell of UCNPs. Blue, pink and yellow
represents the core, the inner shell and the outer shell respectively. (b) Photographs of theluminescence (1-3) NaGdF4:Yb,0.5%Tm,xEr@NaGdF4:Yb@NaNdF4:Yb (x= 0, 0.2, and 1%),
(4)

NaGdF4:Yb,1%

Er@NaGdF4:Yb@NaNdF4:Yb,(5-6)

NaGdF4:Yb,0.5%Tm,xEr@NaGdF4:Yb,15%Eu@NaNdF4:Yb (x = 1 and 0.2%), (7-9)
NaGdF4:Yb,0.5%Tm@NaGdF4:Yb,xEu@NaNdF4:Yb (x = 15, 10 and 5%). Excitation
wavelength is 800 nm. [50]. ..................................................................................................... 11
Figure 2. 5: Schematic of the typical co-precipitation method used for nanoparticles synthesis[53]. .......................................................................................................................................... 12
Figure 2. 6: (a) Typical 25 ml autoclave (source: internet). (b) Schematic showing crosssectional view of sealed autoclave. .......................................................................................... 13
Figure 2. 7: (a) Colloidal solution (2% concentration in cyclohexane solution) of various
nanoparticles obtained by hydrothermal process. (b) Schematic showing liquid-solid-solution
synthesis strategy achieved by hydrothermal process. Both figures are from reference [57]. 15
Figure 2. 8: Atomic structure of (Left) Rare-earth ions and (Right) Transition metal ions [79].
.................................................................................................................................................. 19
Figure 2. 9: Energy level diagrams showing lifting of degeneracy of trivalent Ln 3+ ions due tovarious effects. The energy levels are represented by 2S+1LJ where S, L and J represents total
spin, orbital momentum and angular momentum quantum number respectively [79]. ........... 20vi

Table of Figures
Figure 2. 10: (a) Schematic representation of cubic (top) and hexagonal (bottom) NaREF4
structure [108]. (b) TEM image of cubic and hexagonal phased NaYF4:Yb/Er (20/2 mol%).
The scale bar represents 100 nm [109]. (c) The variation of upconversion intensity, obtainedby integrating spectral intensity of emission spectra over wavelength in the range of 400-700
nm with Gd3+ concentration [108] . ......................................................................................... 23
Figure 2. 11: Energy level diagram showing (a) Excited State Absorption (ESA) and (b) Energy
Transfer (ET) between Sensitizer (S) and Activator (A) ions. Taken from [110]. .................. 24
Figure 2. 12: Schematic showing (a) two critical parameters for effective energy transfer, i.e.
distance between sensitizer-activator atom and spectral overlap between sensitizer emission(𝑓𝑒𝑚𝑆(𝐸)) and activator absorption (𝑓𝑎𝑏𝑠𝐴(𝐸)) [112]. (b) ET followed by ESA [110] . .... 25
Figure 2. 13: Energy transfer mechanism: (a) Successive Energy Transfer (SET) (b) Crossrelaxation (CR) (c) Cooperative Sensitization (CS) (d) Cooperative Luminescence (CL) [110].
.................................................................................................................................................. 26
Figure 2. 14: Schematic three levels energy diagram showing Photon Avalanche (PA)mechanism [110]. ..................................................................................................................... 27
Figure 2. 15: (a) Partial energy levels diagram showing upconversion phenomenon of Tm 3+
and Er3+ ions when Yb3+ act as a sensitizer. The dash-dotted, dashed, wavy and solid line
represent the NIR photon excitation, energy transfer, multi-phonon relaxation and emission
processes respectively [48]. (b) A typical upconversion spectrum of Tm3+ in visible region (c)Typical upconversion spectrum of Er3+ in visible region. (b) and (c) are taken from [118]. ... 29
Figure 2. 16: (a) Schematic showing single inert epitaxial layer grown over core (b) The 1.7
fold enhancement in upconversion after coating the 29 nm core (NaYF4: Yb, Er) with 2 nm
NaGdF4 layer [146]. ................................................................................................................ 32
Figure 2. 17: Upconverter encapsulated metals [154]. ............................................................ 33
Figure 2. 18: (a) Schematic representation of energy migration in case of various sublattices(b) TEM micrograph of KYb2F7:Er3+ (2 mol%) (c) Simplified partial energy showing
underlying energy transfer mechanism for four-photon upconversion. Taken from [162]. .... 34
Figure 2. 19: (a) Schematic showing immunolabeling of HeLa cell. HeLa cell after incubatedwith rabbit anti-CEA8 Ab-conjugated UCNPs (b) bright field (c) dark field and (d)superimposed image. Taken from [168]. ................................................................................. 35
Figure 2. 20: Schematic showing steps involved in PTT and PDT. ........................................ 36
Figure 2. 21: Schematic showing: (a) organic dye (acting as antenna) sensitized upconversion
process [143] (b) photocatalytic reaction process using TiO 2-upconverting core-shell
nanoparticles [178]................................................................................................................... 38vii

Table of Figures
Figure 2. 22: (a) Actual sized and magnified fluorescence image in the case of quantum dots(top) and UCNPs (bottom) [182]. (b) The printed paper with the upconversion ink in visible
light (top) and in 980 nm light (bottom) [183]. (c) Overlapped images printed with threedifferent 𝜏 − 𝑑𝑜𝑡𝑠 (top), having distinct lifetime of 52, 159 and 455 𝜇s (middle) and pseudo
colour is used to indicate the luminescence lifetime of each pixel (bottom) [184]. ................ 39
Figure 2. 23: The upconversion emission spectra of (a) CO2 sensor [188] (b)NH3 sensor. The
spectra are normalized to a peak at 655 nm [187]. .................................................................. 41
Figure 2. 24: Five different structures of nanoparticles realised using Gold (a) Schematic
representations (b) TEM images (c) Colloidal solutions showing tuneable optical properties
obtained by changing shapes of nanoparticles during synthesis [206]. ................................... 47
Figure 2. 25: (a) Schematic illustration of LSPR excitation for symmetric GNSs (b) Typical
UV-Vis spectrum of GNSs showing single plasmonic resonance peak. ................................. 48
Figure 2. 26: (a) Schematic illustration of LSPR excitation for asymmetric GNRs (b) Typical
UV-Vis spectrum of GNRs showing two resonance peaks. .................................................... 49

Figure 3. 1: Three necked glass flask used for synthesis of UCNPs. Inset shows photograph of
UCNPs dispersed in cyclohexane (illustrating the clarity of the solution). ............................. 54
Figure 3. 2: Optical fibre temperature probe constructed after coating silver paint on the UCNPPDMS tip. Inset shows green UC fluorescence emitted by UCNPs-PDMS composite coated tip(before the silver coating was applied) upon excitation with light from a 500 mW, 980 nm laser
source. ...................................................................................................................................... 56
Figure 3. 3: Characterization setup for measuring fluorescence of UCNPs in colloidal solution.
During measurement, external light was turned off................................................................. 56
Figure 3. 4: Schematic of the setup used for thermal characterization of the probes. ............. 57
Figure 3. 5: Photograph of the equipment used in the thermal characterization of probes (left).
The exploded view of the filter (right). .................................................................................... 58
Figure 3. 6: (a) TEM image of synthesized hexagonal phased-UCNPs. Inset shows the green
UC fluorescence from the UCNPs colloidal solution when excited using light from the 980 nm
laser source. (b) Photographs of the PDMS (marked as 1) and the UCNPs-PDMS composite.
.................................................................................................................................................. 59
Figure 3. 7: (a) UC emission spectra when UCNPs are dispersed in cyclohexane, UC powder& UCNPs-PDMS. R/G represents the integrated intensities of the red and green bands, shownby red and green colored areas in the lower spectrum shown (b) Partial energy level diagramviii

Table of Figuresof Yb3+/Er3+ showing the important radiative and non-radiative transitions involved in the UC
mechanism. The dash-dotted, dashed, wavy and straight (solid) lines represent the NIR photon
excitation, energy transfer, non-radiative relaxation and radiative emission processes
respectively. ............................................................................................................................. 60
Figure 3. 8: (a) ATR-FTIR response of UC powder and UCNPs-PDMS composite (b) GreenUC emission bands of Er3+ ions. IH is the area under curve from 514 nm to 532.3 nm
corresponding to the radiative transition 2H11/2 → 4I15/2 and IS is the area under curve from 532.8
nm to 562 nm corresponding to the radiative transition 4S3/2 → 4I15/2 (c) Variation of Intensity
ratio (IH/IS) with time due to laser source heating. The right axis shows the variation oftemperature with respect to the mean value. ............................................................................ 61
Figure 3. 9: UC powder: (a) Variation of green fluorescence with temperature. The figure has
been normalized to the maximum value (obtained at 297 K). The inset shows variation of I H
and IS with temperature. (b) Experimentally obtained ratio of IH and IS against temperature,juxtaposed with an exponential fitting using Eq. (3.1). ........................................................... 63
Figure 3. 10: (a) Linear fitting of the ratio obtained of IH and IS over the temperature range from298 K to 395 K (b) Absolute (left) and relative (right) thermal sensitivities obtained for the UC
powder...................................................................................................................................... 64
Figure 3. 11: UCNPs-PDMS composite coated probe: (a) Variation in green fluorescence bands
with temperature. The inset shows integrated emission intensities (b) Linear fitting of theexperimentally obtained ratio of (IH/IS), as function of temperature. ...................................... 65
Figure 3. 12: (a) Exponential fitting of the experimentally obtained ratio of (I H/IS) as functionof temperature, using Eq. (3.1) (b) Cyclic response obtained through repeatedly varying thetemperature from 296 K to 359 K (and back). The smoothened curve (dotted) was obtained by
calculating local mean from 20 neighboring points is shown as guidance for the eyes. ......... 66
Figure 3. 13: (a) Ramp-up response of the sensor (b) Normalized green fluorescence before
and after coating of commercial silver paint............................................................................ 67

Figure 4. 1: (a) Colloidal Solution (b) Image of the GNPs coated fibre, where the coating area
is clearly visible. The white bar at the bottom right represents the reference scale (1 mm). ... 72
Figure 4. 2: Schematic of the processes involved in the sensor preparation. .......................... 74
Figure 4. 3: (a) Schematic of the experimental setup used for the characterization of the GNPs
coated fibre. (b) TEM image of GNPs. .................................................................................... 75ix

Table of Figures
Figure 4. 4: (a) DLS measurement of the GNPs (b) Experimental UV-VIS spectrum obtained,with superimposed results of a model based on Mie scattering............................................... 76
Figure 4. 5: (a) Response of GNPs-coated fibre to increase in absorbance with increase in RI.
The vertical dotted line at 545 nm is given as guidance for eyes. (b) Shift in LSPR wavelength
in different refractive index media. .......................................................................................... 76
Figure 4. 6: Response of GNPs-coated fibre in (a) the Lead Nitrate (LN) solution (b) Afterremoved from LN solution, dried and monitored in air. .......................................................... 78
Figure 4. 7: (a) Absorbance spectrum of Au NP-coated fibre before and after coating with
MUA. (b) SEM image of GNPs-MUA-coated fibre after immobilization in Lead Nitrate (LN)
solution. The table shows the EDAX analysis of the highlighted section. .............................. 79
Figure 4. 8: Response of MUA-coated fibre in (a) the Lead Nitrate (LN) solution (b) Afterremoved from LN solution, dried and monitored in air (c) Pb2+ concentration versus LSPR
wavelength. .............................................................................................................................. 80

Figure 5. 1: Self-normalized modelled absorption spectra showing the red shift in theLongitudinal Localised Surface Plasmon Resonance due to an increase in (a) the Aspect Ratio(AR) and (b) the Permittivity of the surrounding medium (εm). .............................................. 85
Figure 5. 2: (a) The UV-Vis absorption spectrum of the chemically synthesized sample (solidline) and the spectrum obtained by fitting the longitudinal resonance (dash line). Inset is showna photograph of the GNRs solution (b) AR distributions curve obtained through themeasurement with the TEM images measurement (solid line) and fitting of the UV-Vis
spectrum (dashed line). The legend shows the mean value for both graphs. (c) TEM images
taken at three different places on the TEM grid. The scale bar represents 50 nm. ................. 90
Figure 5. 3: (a) The UV-Vis absorption spectrum of the chemically synthesized sample (solidline) compared with spectrum retrieved from AR distribution obtained from TEM measurement(dashed line). (b) Dependence of length and width of GNRs on AR obtained from TEM
measurement. ........................................................................................................................... 91
Figure 5. 4: (a) The UV-visible spectra extracted from the work of Eustin & Sayed [298] . (b)(e) Comparison of AR distribution obtained from the algorithm developed in present work withthe one reported in the same publication. ................................................................................ 92
Figure 5. 5: (a) Size Distribution of chemically synthesized GNRs obtained by using the DLS
technique (b) Quality of the fitting of the Absorption spectra generated by the test program,obtained by fitting the generated curve with the bounded and the unbounded coefficients. ... 93xTable of Figures
Figure 5. 6: (a) Fitted SSE as function of εm for the bounded coefficients. Inset shows theobtained minimum SSE for εm = 2.12. (b) Left: the figure compares the generated (test) AR
contribution with that generated by the algorithm for the bounded and unbounded coefficients.
Right: 'Zooming in' on the 3 ≤ AR ≤ 4 region from the main (Left) figure. .......................... 94
Figure 5. 7: (a) The absorption spectra of chemically-synthesized sample (solid line),
juxtaposed with the spectra obtained by fitting the longitudinal resonance (dashed line). The
dotted section highlights the mismatch around transverse resonance. (b) AR distributions
curve. The legend shows mean value and standard deviation. For both graphs, εm = 1.92 wasused. ......................................................................................................................................... 96
Figure 5. 8: (a) Measured (solid line) and fitted (dashed line) absorption spectra, for a low AR
sample. Dotted section qualitatively highlights the number of particles having AR ≤ 2. (b)Contribution of various AR values to obtain the fitted curve in (a). The SSE was a minimumfor εm = 1.97. ............................................................................................................................ 97xi

Table of Tables

Table of Tables
Table 2. 1: Some important characterization techniques for nanomaterials. ........................... 16
Table 2. 2: Host lattices used for doping lanthanide ions for upconversion process. .............. 21
Table 2. 3: The major emission wavelengths and corresponding energy transition level of someof typical activator ions [122]. ................................................................................................. 30
Table 2. 4: Summary of few important applications of upconverting nanoparticles (used indiverse fields) reported between 2010-2020. ........................................................................... 42

Table 3. 1: Silver coating of the tip. Given data is for Fig. 3.13(b). ........................................ 66
Table 3. 2: Comparison of key parameters of the performance of probes developed in this workwith those from Er3+/Yb3+ doped glass temperature sensors, reported in the literature. ......... 68

Table 5. 1 AR and corresponding contribution obtained from Generated, Fitted Bound, & Fitted
Unbound techniques................................................................................................................. 95xii

Acknowledgement

Acknowledgement
First and foremost, I would like to express my heartfelt gratitude to my supervisors Professor
Tong Sun and Professor Kenneth Grattan for their technical guidance, financial and moral
support that helped me immensely in successfully completing this research programme. It wasan honour and a privilege to work under such professional and kind-hearted experts in the field.
I have matured as a researcher in both technical and non-technical aspects because of theirguidance and erudite inputs during discussions.
I would also like to thank Dr. Lourdes Alwis and Leonardo Binetti for their continuous support
with material characterisation. I also want to thank Dr. Arti Agrawal for introducing me to City
Doctoral Fellowship and co-supervising me throughout the first year of my PhD degree.
Special thanks to my fellow researchers, Dr. Matthias Fabian, Dr. Miodrag Vidakovic, Dr. Hien
Nguyen, Dr. Bruno Rente, Dr. Kasun Dissanayak, Dr. Souvik Ghosh, Dr. Israt Kabir, Dr.
Papiya Dhara and Dr. Sunny Chug for discussions, suggestions and ideas. Without theirencouraging words and insightful chats, my journey would have been a much longer and alonely one.
I would like to thank my parents and siblings for their sacrifices and keeping me away fromfamily responsibilities, which enable me to concentrate on my research. I would like to extend
my warmest gratitude to my wife Nusrat Tamanna for making my stay in UK, a memorable
one. Without her love, support and encouragement, I could not have finished this thesis on
time.
Finally, I would like to pay my salutations to sages of India who preserved the spiritual
knowledge and transferred it selflessly from one generation to another. Be it yoga or
meditation, or devotional songs, these techniques kept me calm and focussed through thick andthin part of my journey.
In one’s life, there are contributions from many people, and it is not possible to mention
everyone here. However, I thank them all.

xiii

Copyright Declaration

Copyright Declaration
The author hereby grants powers of discretion to the City University Librarian to allow thethesis to be copied in whole or in part without further reference to the author. This permission
covers only single copies made for study purposes, subject to normal conditions of
acknowledgements.

xiv

Abstract

Abstract
In this work, the Upconverting and Gold nanoparticles were chemically synthesized, coated on
the multimode optical fibres and with their performance were evaluated for sensing two keys
environmental parameters, temperature and heavy metals present in the aqueous medium, eachof which has shown competitive performance with current devices.
In Upconverting Nanoparticles (UCNPs – NaYF4: (18%) Yb3+, (2%) Er3+), thermally coupledgreen band emission from excited Er3+ ions was used to create optical thermometer, working
in the useful range of 295 K – 473 K, with a sensitivity of 4.91 × 10-3 K-1, a temperature
resolution of ± 2.7 K and response time of ∼ 5 seconds. The mixture of UCNPs andpolydimethylsiloxane shows an excellent linear response (R2 = 0.991) in entire working rangeof the sensor. The highlights of the developed sensor are its linear response and low temperaturesynthesis where the required synthesis temperature is around 400 K less than the previously
reported Er3+ doped glass-based temperature sensors.

The colloidal solution of Gold Nanoparticles (GNPs) was synthesised, coated on the opticalfibre and suitably functionalized with MUA (HS(CH2)10CO2H) to make them selective towards
heavy metal ions present in the aqueous solution. The concentration of the heavy metal can be
determined from the link between binding rate and the shift of the localized surface plasmon
resonance wavelength. The Pb2+ ion sensitivity of the sensor thus created has been determined
to be 0.28 nm/mM.

At last, several colloidal solutions of Gold Nano Rods (GNRs) were synthesised, and their
quality was determined by developing an algorithm to readily calculate the aspect ratios (ARs)
distribution. This is achieved by theoretically fitting the localised longitudinal plasmon
resonance of GNRs obtained by UV-visible spectroscopy. The ARs distribution obtained fromthe use of the algorithm developed have shown good agreement with those theoreticallygenerated one as well as with the previously reported results. The comparison of obtained
results with experimentally derived results from the use of expensive transmission electron
microscopic images and dynamic light scattering technique shows that the algorithm developed
offers a fast and thus potentially cost-effective method to determine the quality of thesynthesized GNRs.
xv

Glossary of Abbreviations and Chemicals

Glossary of Abbreviations, Symbols and Chemicals
Abbreviations:
AFM

Atomic Force Microscopy

AR

Aspect Ratio

ATR-FTIR

BPO

AttenuatedTotal

Reflection

Fourier-

Transform InfraRed spectra
Bellman's dynamic programming Principleof Optimality

BSA

Bovine Serum Albumin

CEA

Carcinoembryonic Antigens

CR

Cross-RelaxationCR

Cooperative LuminescenceCS

Cooperative Sensitization

DI waterDeionized water

DLS

Dynamic Light Scattering

Dox

Antitumor Drug Doxorubicin

ECL

Electrogenerated chemiluminescence

EDS

Energy Dispersive Spectroscopy

EELS

Electron Energy Loss Spectroscopy

EPR

Enhanced Permeation and Retention

ES

Electrical Sensors

ESA

Excited State Absorption

ETU

Excited State Upconversion

FBGs

Fibre Bragg Gratings

GNPs

Gold

Nanoparticles(represents

nanospheres unless stated otherwise)

GNRs

Gold Nanorods

GSA

Ground State Absorption

J

Total Angular Momentum

L

Orbital Angular Momentum

L-LSPR

Gold

Longitudinal Localised Surface Plasmon
Resonancexvi

Glossary of Abbreviations and Chemicals
LED

light-emitting Diodes

LN

Lead Nitrate

LPGs

Long Period Gratings

LSA

Least Squares Approximation

LSPR

Longitudinal Surface Plasmon ResonanceLSSliquid–solid–solution

MOFs

Metal Organic Frameworks

NIR

Near Infrared

OF

Optical Fibre

OFS

Optical Fibre-based Sensors

PA

Photon Avalanche

PDT

Photo-dynamic therapy

PL

Photoluminescence

PTT

Photo-thermal Therapy

QDs

Quantum DotsRB

Rose Bengal dye

RERare-Earth

RI

Refractive Index

S

Total Spin

SEM

Scanning Electron Microscope

SET

Successive Energy Transfer

SSE

Summed Square Error

STEM

Scanning Transmission Electron Microscope

STM

Scanning Tunneling Microscope

T-LSPR

Transverse

LocalisedSurface

PlasmonResonance

TCL

Thermally Coupled Radiative Energy Levels

UCNPs

Upconverting Nanoparticles

UCNPs-PDMS

Upconverting

Nanoparticles-

Polydimethylsiloxane

WS-A

Energy Transfer Probability

XRD

X-ray DiffractionxviiGlossary of Abbreviations and Chemicals
Symbols :hPlank Constantc

Speed of Lightn

Refractive Index

𝜏𝑆

Intrinsic Lifetime𝑟𝑆−𝐴

Distance between sensitizer-activator

𝑄𝑎𝑏𝑠

Integrated absorption cross-section of theactivator

𝑆 (𝐸)
𝑓𝑒𝑚

Normalized emission line-shaped function of
the sensitizer

𝐴
(𝐸)
𝑓𝑎𝑏𝑠

Normalized absorption line-shaped functionof the activator

knr

Non-radiative relaxation rate constantΔΕ

Energy difference between populated leveland next lower energy levelℏ

Reduced Plank Constantω

Angularfrequency

oftheradiative

transitions
kB

Boltzmann’s constant

δE

Error in ΔΕ aross temperature

IS

Area under the emission intensity curve over
the wavelength range 532.8 nm to 562 nm

IH

Area under the emission intensity curve
between wavelength 514 nm and 532.3 nm

𝜆Wavelength𝑇

Temperature

δIH

Standard error in IH

δISStandard error in IS

𝑆𝐴

Absolute thermal sensitivity

𝑆𝑅

Relative thermal sensitivity

𝑅

The ratio of the integrated emission
intensities of the green bands𝑔Degeneracy of the given energy levelxviii

Glossary of Abbreviations and Chemicals
A

Emission cross-section

t90

Time taken to reach 90% of saturated levelt10

Time taken to reach 10% of saturated level𝛾

Absorption coefficient of the GNRs in thecolloidal solution

𝑁

Number of GNRs per unit volume

𝑉

Volume per particle

εmDielectric constant of the surrounding
mediumε1Dielectric constant of real part of thepermittivity for the gold

ε2Dielectric constant of imaginary part of thepermittivity for the gold

𝒆𝒙𝒑

𝑨𝝀𝒙

Experimentallyobtained

value

of

the

absorption at 𝜆𝑥(WS-A)

Energytransfer

probability

betweensensitizer and activator ions

Abbreviations of Chemicals used in this work:
C18H361-Octadecene

C19H42NBr

Cetyltrimethylammonium bromide (CTAB)

C2H5OH

Ethanol(C2H6OSi)n

Polydimethylsiloxane (PDMS)

C18H34O2

Oleic acid

C6H12

Cyclohexane

C6H8O6

Ascorbic acid

CH3OH

MethanolErCl3∙6H2O

Erbium(III) chloride hexahydrate

H2N(CH2)3Si(OCH3)3

3-Aminopropyl trimethoxysilane (APTMS)

H 2O 2

Hydrogen peroxide

H2SO4Sulphuric acid

HAuCl4.3H2O

Chloroauric acidxix

Glossary of Abbreviations and Chemicals
HS(CH2)10CO2H

11-Mercaptoundecanoic acid (MUA)

Na3C6H5O7.H2O

Sodium citrate tribasic dehydrate

NaBH4

Sodium borohydride

NaOH

Sodium hydroxide

NH4F

Ammonium fluoride

Pb(NO3)2

Lead nitrate

YbCl3∙6H2O

Ytterbium (III) chloride hexahydrate

YCl3∙6H2O

Yttrium (III) chloride hexahydratexxChapter 1

Chapter 1
Introduction
1.1 Background
Nanoparticles, having a size less than 100 nm in all three dimensions, have been known about
for many centuries, if not identified as such. The Lycurgus cup in the British museum, shownin Fig. 1.1, illustrate that even in 4th century AD, Roman craftsmen empirically knew of ways
to stain glasses with of gold and silver nanoparticles [1]. In seventeenth century, Kunckel
established the industrial manufacturing of stained glass with colloidal particles [2]. However,in 1857 Michael Faradays showed for the first time various practical approaches ofsynthesizing gold colloidal solutions, thus marking the birth of modern colloidal chemistry [3].
The advancement of quantum mechanics and the consequently burgeoning of various
nanoscale characterization instrumentation such as Transmission Electron Microscopy (TEM),
X-ray diffraction and Raman Spectroscopy has, in last 50 years, given better insight into size
related thermal, electrical, mechanical and optical properties of the materials [4].This deeper
understanding coupled with better controlled over the synthesis processes have led to several
organic and inorganic nanoparticles and their applications in various fields: these being as
diverse as imaging, energy harvesting, drug delivery, tissue ablation and sensing [5]. Amongthe several fields where the nanoparticles have been used, in this work their usage in sensing
has been explored because sensing is an important and growing sector. This is evident fromthe fact that overall projected market value of sensors is expected to reach $320 billion by 2025with a current compounded annual growth rate of >10% [6].

1Chapter 1

Figure 1. 1: The Lycurgus cup. Left and right images show the colour of cup when it is illuminated from outside(under reflection) and inside (under transmission) respectively. The man illustrated in cup is the mythologicalKing Lycurgus who is being dragged into the underworld by Greek nymph Ambrosia, disguised in form of vine
[1].

Currently, Electrical Sensors (ESs) dominate the global market due to their typically low cost,
relative ease of miniaturization and easy integration with available electrical and mechanicaldevices [7–9]. ESs depend on electrical parameters, typically voltage and current changes, as
the basis of their sensing mechanism, therefore, they are not often a natural choice for chemicalsensing because of material degradation or corrosion occurring in the presence of aqueous or
gaseous media. Further, ESs often can suffer from inherent low signal-to-noise ratios and may
be sensitive to external electromagnetic interference. However, many drawbacks of ESs
mentioned above can be overcome by the use of Optical Fibre-based Sensors (OFSs), as theirtransduction effect is entirely optical. In fact, initially optical fibres were developed mainly as
optical waveguides as an alternative to copper wires for the benefit of the telecommunicationindustry. However, they gradually became popular for sensing applications especially after
discovery of photosensitivity in optical fibre by Kenneth Hill in 1978 [10]. This has enabled
Fibre Bragg Gratings (FBGs) and Long Period Gratings (LPGs) to be written in the core of
optical fibre which has made fibre highly sensitive to external strain and temperature. The
availability of various types of optical fibres, such as multimode, single mode, small core,hollow core, photonic crystal fibre, and polymer-based fibre have given significant flexibility
to the sensor designer. The plethora of different optical fibres make OFSs promisingalternatives to ES, particularly for specialist or safety-critical situations where electrical sensors
often fail [11,12]. The development of new and better optical fibre sensors for a range ofchemical species is important for the burgeoning environmental sensing market and the need2

Chapter 1
for better monitoring, to allow remedial action to be taken to enhance the environment.
Consequently, this thesis focuses on developing novel & portable optical fibre sensors for
detecting heavy metals in an aqueous medium and with that temperature, using gold
nanoparticles and Upconverting Nanoparticles (UCNPs) respectively.
The name “upconverting” suggests in UCNPs, these nanoparticles upconvert Near Infrared(NIR) photons to visible photons by absorbing two or more NIR photons sequentially. Since
this upconversion is achieved by sequential absorption of photons rather than spontaneousabsorption (unlike in conventional two-photon generation), this effect can be achieved at muchlesser source power. The need for a low power source, exploiting the transparency of tissues
to NIR light has made these UCNPs a good candidates for biological imaging [13]. However,their sensing capabilities have not as yet been fully explored as relatively very fewer papers
have been reported on the potential use of UCNPs based sensors [14] and moreover, their
combination with optical fibre is even more limited. The research reported in this thesis hasaddressed this gap and has targeted the use of UCNPs and UNCPs-polymer composites todevelop portable optical fibre-based temperature sensors. The importance of temperaturesensing can be judged from the fact that around 75-80% of world’s sensors are temperature
sensors [15]. The two main advantages of the sensor addressed in this work over previously
reported temperature sensors are: the relatively inexpensive equipment needed for synthesis
which can be achieved in conventional chemistry synthesis laboratory and the linear responsein the useful range of 298 K to 493 K.
The development of an OFSs to detect heavy metal ions, a species important as it is often seen
as a contaminant in the environment (particularly in soil) and is harmful to human health is afurther focus of this work. The novelty addressed is targeting ease of manufacture, with an aim
to create a simple, portable and robust Longitudinal Surface Plasmon Resonance (LSPR)based OFS system, operating in reflection mode and designed to detect the lead ions (Pb2+).
Out of several heavy metal pollutants, lead is used to demonstrate the sensing capabilities ofthe developed sensor because lead poisoning is one of the global key issues and as per UN
report, every year approximately 0.8 million people die worldwide due to it [16]. The Lead
and/or lead based compounds are widely use in various household products such as batteries,
cosmetics, polyvinyl chloride toys, tin pots, water pipes and paints [17]. Recently, Nicolie etal. published an article highlighting unusual domestic source of lead poisoning [18].

3Chapter 1
Knowing the aspect ratio (the length divided by the width) distribution of asymmetric Gold
Nano Rods (GNRs) in a colloidal solution is important to achieve uniform and long selfassemblies, allowing their usage in various sensing applications [19]. Therefore, the last partof this thesis deals with the determination of aspect-ratio by examining theoretically spectral
Longitudinal Localised Surface Plasmon Resonance (L-LSPR) of the spectrum obtained fromthe UV-Visible spectroscopy of a GNRs’ colloidal solutions.

1.2 Aims and objectives of this work
The primary aim of this work is to harness the advantages associated with combining
nanoparticles, used as coatings on optical fibre to develop and then evaluate the performanceof nanoparticle-based optical fibre sensors for sensing two keys parameters important for better
environmental monitoring:1) temperature (through a simple to fabricate lost cost, low temperature approach) and2) heavy metals present in the aqueous medium
with the view of creating easy to fabricate, low-cost sensors, competitive in performance withcurrent devices.
Given that primary aim, the major objectives of the work undertaken and reported in this thesisare:•To conduct a literature review of nanoparticles, their synthesis and characterization
methods and determine the state-of-the-art of nanoparticle-based optical fibre sensor
research which underpins this work and thus to determine novel methods to measure bothtemperature and the presence of heavy metals, optimizing the use of resources in so doing.

•

To synthesize hexagonal phase UCNPs using a bottom-up approach and subsequently a
UCNPs-polydimethylsiloxane composite, prior to using them as the basis of creating asensing element in a novel optical fibre sensor probe.

•

To evaluate the fluorescence emission and thermal response of the developed OFSs andcompare their thermal and other performance aspects with those of previously reported
Er3+, Yb3+/Er3+ doped glasses.

•

To synthesize GNPs, coat them on optical fibre to realize reflection-based LSPR opticalfibre sensors and evaluate their performance for varying refractive indices.

4

Chapter 1•

To functionalize the GNPs-based LSPR optical fibre sensor probes appropriately to makethem selective to heavy metals ions and evaluate their sensitivity for various concentrationof Pb2+ ions present in the aqueous solution.

•

To synthesis GNRs with several different aspect ratios, measure their UV-Visible spectra
and use these spectra to determine aspect ratio distribution: thus to evaluate the quality ofsynthesized GNRs specifically needed for many potential applications for the advanced
sensor systems, by developing an appropriate algorithm.

•

To summarize the key results obtained throughout the project period, draw conclusions andoutline the directions for future research.

•

To disseminate the research output to wider audiences through publication in peer reviewed
journals and presentation at international conferences.

1.3 Structure of the thesis
The thesis spans into six chapters describing the work carried out to achieve the above set out
aims and objectives.
Chapter 1 discuss briefly the background to the work and the gaps in the market, setting out
clearly the prime aim and the key objectives and the structure of the thesis.
Chapter 2 focuses on the brief review of nanoparticles, relevant bottom-up synthesis processes
and characterization mechanisms. Afterwards, it discusses in detail about the fundamentals of
upconversion, choice of dopants, ways to increase upconversion efficiency and previously
reported applications. This chapter ends with short discussion on nanoparticles realised fromgold and use of LSPR phenomenon for sensing.
Chapter 3 describes the synthesis process undertaken to realise UCNPs and UCNPspolydimethylsiloxane composite, their coating methodology on multimode optical fibre andexperimental setup to realise a practical temperature sensor. This is followed by discussion of
the obtained results and finally comparison of the thermal response and other performanceissues of the sensors developed, with the previously reported lanthanide doped glass based
optical temperature sensors.
Chapter 4 reports the synthesis and characterization of LSPR based GNPs, their coating on the
optical fibre and functionalization to make it selective towards heavy metals ions. The responseof the developed sensor calibrated with various concentrations of lead nitrate aqueous solution
is discussed.
5Chapter 1
Chapter 5 expounds the algorithm developed to obtained aspect-ratio distribution of GNRs in
a colloidal solution from its UV-Vis spectrum. Further, the synthesis process of GNRs forvarious aspect ratios and the comparison of the results obtained from algorithm with TEM andDLS are presented.
Chapter 6 summarises the thesis with a critical evaluation of aims and objectives stated in
Chapter 1, thus highlighting the main achievements of this work. Finally, based on theexperience gained while working in the area of nanoparticle based optical fibre sensing, someinteresting ideas are been suggested which would be worth pursuing in the future research.

1.4 Summary
The brief background to the subject of nanoparticles, optical fibres-based sensors and an
exploration of the “gap in the market”, which led to fixing important aims and objective of thiswork are discussed in the first section. The next section explicitly delineates the aims andobjectives of this work followed by a discussion of the structure of thesis considering in detail,the contents of each chapter.

6

Chapter 2

Chapter 2
Literature review
2.1 Introduction
Nanoparticles, having dimension ≤ 100 nm in all three directions, show size and shapedependent properties such as their optical, magnetic, chemical, and electronic properties,
amongst others. These properties coupled with significantly higher surface to volume ratio thanthat is seen in their bulk counterpart makes them very attractive for several diverse applications
including sensing, imaging, drug delivery, security and energy harvesting and electronics, forexample.

Figure 2. 1: Nanoparticles Classifications [20].

The plethora of available nanoparticles can be classified in a way based on several criteria suchas their origin, chemical composition, physical structures (shapes) and applications, for7

Chapter 2

example, as shown in Fig. 2.1. It is not possible to consider here all the available nanoparticles:
therefore, in this chapter, several of the most frequently used nanoparticles in the field ofsensing and measurement will be introduced and two type of nanoparticles in particular i.e.,‘Upconverting’ and ‘Gold’ nanoparticles will be considered in detail, in the light of theirrelevance to the work discussed herein. Furthermore, the underlying mechanism of three of themost interesting and relevant ‘bottom up’ synthesis of nanoparticles and a brief overview of
the available characterization techniques will also be presented.
The structure of this chapter is as follows: next section is dedicated to nanoparticles, theirsynthesis and characterisation techniques. The following section to that deals about
upconverting nanoparticles, their fundamentals and the several interesting applications
reported in the literature during last ten years. The second last section deals about nanoparticles
derived from gold and basic of localised surface plasmonic resonance. The last section
summarizes the complete chapter.

2.2 Nanoparticles
2.2.1 Classification
A. Quantum dots:
Quantum Dots (QDs) are semiconductor-based nanoparticles having diameter in the range of
2-10 nm [21]. Because of their size being smaller than the exciton Bohr radius, their energy
levels show a discrete quantization effect, as seen in Fig. 2.2(a) and consequently this gives
rise to their different electrical and optical properties from their bulk counterparts [22]. It canbe seen from the schematic shown in the figure that the energy band gap in case of QDs isdependent on the size of the nanoparticles and this increases on decreasing of the size of the
QDs. This effect, popularly known as the quantization effect, causes a ‘size-based’
photoluminescence effect, as shown in Fig. 2.2(b), where on decreasing the size of the CdSe
QDs considered, the emitted wavelength shifts to higher energy photons, i.e., red to blue
wavelength due to increase in energy band gap. A number of the other important QDs that havebeen reported in literature are those bases on materials such as ZnO, InP, HgS, ZnS and CdS[21]. Unlike organic dyes, QDs do not suffer from the deleterious photobleaching effect andtherefore, several applications based on QDs have been reported in the literature such as
fluorescence based bioimaging [23], solar cells [24], and optoelectronics devices such as LEDs
[25,26], lasers [27] and optical amplifiers [28]. However, a more full potential of the8Chapter 2

applications and the use of QDs is limited by their cytotoxic effect which is still under study
[29].

(a)

Bulk Band Structure

Quantum Dots(b)

EnergyConduction
Band
Band
Gap
4.2 nmValenceBand

3.9 nm3.0 nm

2.5 nm2.0 nmDecreasing Size

Figure 2. 2: (a) Schematic representation showing the splitting of energy levels in QDs and increase in the band
gap due to decrease in size [30]. (b) Photoluminescence of CdSe QDs showing blue shift of emission on
decreasing their diameter. These colloidal solutions are excited with broadband UV source [31].

B. Metallic nanoparticles
Metal nanoparticles, due to availability of free electrons exhibit unique properties that are notfound in other nanoparticles. These free electrons interact with the oscillating electric field of
the incident electromagnetic radiation and at the resonant frequency this shows enhanced lightabsorption, scattering and local confinement of the electric field in the nanoscale region atparticles surfaces. This phenomenon, known as LSPR is used in developing several
applications in sensing [32], photothermal therapies [33,34], surface enhanced spectroscopies[35], optical waveguides [36] and photocatalysts [37]. The most commonly used nanoparticles
are those using Al, Cu, Au and Ag. Magnesium nanoparticles showing plasmonic effects are
relatively new in the field [38]. The underlying physics of LSPR is discussed in the second lastsection of this chapter.

C. Metal halide perovskite
Perovskites are all inorganic or inorganic-organic nanoparticles represented by the chemical
formulae ABX3, where A is an organic or alkali metal cation, B is a divalent metal cation and
X is a halide anion binding to both cations, as shown in the schematic in Fig. 2.3(a). They
9

Chapter 2

exhibit strong absorption which can be tuned from the visible to NIR region by appropriatelychanging the anionic and cationic components. Due to the small exciton binding energies, large
carrier mobilities, and long and balanced charge diffusion length, they have shown important
potential in sensing [39], photovoltaic solar cells, light-emitting diodes (LED), photodetectors
and transistors [40–42].

Figure 2. 3: Schematic showing (a) Perovskite having a ABX3 structures, where A is an organic (e.g. CH3NH3+)or alkali metal (e.g. Cs+) cation, B is a divalent metal cation (e.g. Pb2+, Sn2+) and X is halide anion (e.g. Cl-,
Br-, I-)[40] (b) Metal Organic Frameworks (MOF) [43].

D. Metal organic frameworks:
Metal Organic Frameworks (MOFs) are also inorganic-organic hybrid crystalline porous
structures which consist of a regular array of positively charged metal ions (acting as node)surrounded by organic ligands (acting as linker), thus giving raise to hollow cage-like structure,
as shown in Fig. 2.3(b) [44]. To date, more than 20,000 different MOFs have be reported in
the literature [43]. Due to their large internal surface area (100 -10000 m2g-1), MOFs have beenused several applications including sensing [45], gas & liquid storage and purification [46] andelectrochemical energy storage [47].
E. Upconverting nanoparticles:
Upconverting Nanoparticles (UCNPs) are fluorescent particles which absorb two or more low
energy photons, mostly in the Near-Infrared (NIR) and emit a single photon in the visible
region [13]. This upconversion process (𝜆𝑎𝑏𝑠𝑜𝑟𝑏𝑡𝑖𝑜𝑛 > 𝜆𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛 ) differs from traditional twophoton absorption and second-harmonic generation in the sense that the former is a sequential
but the latter two are spontaneous processes. Upconversion process being sequential in nature
can be achieved at much lesser laser overall power. The two essential requirements for thesequential upconversion, i.e. ‘ladder shaped’ energy levels and a long excited state lifetime can
10Chapter 2

readily be obtained in rare-earth elements. Therefore, the majority of UCNPs reported inliterature are realised using rare-earth ions. The typical UCNP consists of an inorganic
crystalline host lattice (which provides an active site of dopants), activator ions (acting as aluminescence centre) and sensitizer ions (used to increase the NIR absorption efficiency;transfer the energy to the activator during de-excitation) and usually represented by “Hostmatrix: Sensitizer (mol%), Activator (mol%)” [48]. For example, in NaYF4:Yb3+ (18%), Er3+(2%), NaYF4 is the host matrix, Yb3+ is the sensitizer, Er3+ is an activator and Y3+:Yb3+:Er3+
ions are in a mole ratio of 80:18:2. In a few cases, one or more inert or suitably doped shells
are grown around the core [49]. In one of such UCNPs was developed by Zhong et al., where
they grew two shells on the core [50]. A schematic of nanoparticle is shown in Fig. 2.4(a). By
varying the composition of the dopant, the authors have shown that the emitted fluorescenceof the developed UCNPs lies the visible spectral range, as shown in Fig. 2.4(b). Considering
the relevance of UCNPs in this work, both fundamentals and their key applications are
discussed in more details in the next section.
(a)

(b)

800 nm

Green

1

2

3

4

5

6

7

8

9

Blue
Nd3+

Red

Er3+
Eu3+

Tm3+

Gd3+

Figure 2. 4: (a) Schematic diagram showing core-shell of UCNPs. Blue, pink and yellow represents the core,
the inner shell and the outer shell respectively. (b) Photographs of the luminescence (1-3)
NaGdF4:Yb,0.5%Tm,xEr@NaGdF4:Yb@NaNdF4:Yb (x= 0, 0.2, and 1%), (4) NaGdF4:Yb,1% Er@NaGdF4:Yb@NaNdF4:Yb, (5-6) NaGdF4:Yb,0.5%Tm,xEr@NaGdF4:Yb,15%Eu@NaNdF4:Yb (x = 1 and 0.2%), (7-9)
NaGdF4:Yb,0.5%Tm@NaGdF4:Yb,xEu@NaNdF4:Yb (x = 15, 10 and 5%). Excitation wavelength is 800 nm.
[50].

2.2.2 Synthesis methods
There are several bottom up synthesis methods for nanoparticles described in the literatureincludinginert

decomposition,

Gas-condensation,

sonochemical(ultrasonic)

processing,

sol-getco-precipitation,

microemulsion,

chemicalprecipitation,andhydrothermal/solvothermal synthesis, for example. Out of these processes, the underlying
principle of three of these processes i.e. coprecipitation, hydrothermal/solvothermal and seed-11

Chapter 2

mediated method have been described below in details, given their relevance to the synthesisof Upconverting and Gold nanoparticles (and rods) considered in this thesis.

A. Coprecipitation
Coprecipitation, as the name suggest, involves the simultaneous occurrence of nucleation,
growth coarsening and/or agglomeration when anion and cation solutions are mixed, as
depicted in the flowchart in Fig 2.5. Nucleation, where a large number of small particles areproduced is a primary and key step. These small particles grow into large particles following
an Ostwald ripening process and once the supersaturation condition is reached, thenprecipitation happens. The precipitate is often filtered and calcinated (heated at hightemperature in presence of air or oxygen). Calcination not only increases the crystallinity ofmaterial but also removes any impurities present on the surface. The major advantages of thecoprecipitation process are: short reaction time, mild reaction conditions, simple protocols andinexpensive equipment [51]. However, this method is not applicable to uncharged species.
Further, traces of impurities become precipitated with the product and it does not work well if
reactants have very different precipitation rates [51]. Coprecipitation methods are mostly
preferred for synthesizing oxide-, fluoride- or oxyfluoride-based nanophosphors like Fe3O4[52].

Figure 2. 5: Schematic of the typical co-precipitation method used for nanoparticles synthesis [53].

B. Seed-Mediated method
12Chapter 2

The seed-Mediated method has been traditionally used for synthesizing noble metal
nanoparticles with different shapes and sizes [54]. It typically involves two steps: the synthesisof the seed and their growth (by introducing in growth solution containing metal precursors,
reducing agents and shape directing agents). This method gives better control over thenanoparticle shape and size by isolating nucleation and growth as two separate synthesis steps,
unlike in the process involving spontaneous nucleation and growth such as co-precipitation[55]. This method is used in the current work for synthesizing gold nanorods of various aspectratios, as described in detail in Chapter 5.

C. Hydrothermal/Solvothermal method
In the hydrothermal/solvothermal method, chemical synthesis is performed in sealed container
under high temperature (often above critical point of solvent) and pressure. This is generally
carried out in specialized vessels, known as autoclaves. A photograph of one of these
autoclaves (25 ml in volume) and a schematic showing cross-section view of the sealed
autoclave is shown in Fig. 2.6(a) and 2.6(b) respectively. The difference between thehydrothermal and the solvothermal method is in the kind of solvent used i.e. in hydrothermal
method, water is used as solvent whereas in the solvothermal solution nonaqueous solution,
mainly organic solutions are used as the solvent [56]. The shape, size distribution andcrystallinity of final product can be manipulated by adjusting parameters such as reaction
temperature, reaction time, solvent type, surfactant type and precursor type [51].

(a)

(b)

Outer Stainless-Steelbody

Outer Cap

Outer Cap
Upper disk

(b)

Inner
TeflonReactorChamber

Teflon Chamber

Solution

Solid Reagent
Upper Stainless-Steel disk

50 nm
Stainless-Steel rod for locking

Outer body

Figure 2. 6: (a) Typical 25 ml autoclave (source: internet). (b) Schematic showing cross-sectional view ofsealed autoclave.

13

Chapter 2

Wang et al. have reported synthesis of metals, semiconductors, fluorescent, magnetic anddielectric nanoparticles using the hydrothermal reaction [57]. A photograph of some of theirsynthesized nanoparticles stabilized in cyclohexane is shown in Fig. 2.7(a). In the same work,
the authors proposed the phase transfer and separation mechanism occurring at the interfacesof the solid, liquid and solution (liquid–solid–solution (LSS)) as an underlying mechanism ofnanoparticle synthesis. For example, for the preparation of the noble metal nanocrystal, 20 mlof aqueous solution containing a noble metal salt like (AgNO3, HAuCl4), 1.6 gm of sodium
linoleate (C18H31NaO2), 10 ml ethanol (C2H5OH) and 2 ml of linoleic acid (C18H32O2) was
added in 40 ml autoclave under agitation. This mixing give raise to formation of three phases:
ethanol and linoleic acid (liquid phase), sodium linoleate (solid phase; as it is not soluble),water-ethanol containing noble metal ions (solution phase), as depicted through the schematicin Fig. 2.7(b). The noble metal ions spontaneously went through phase transformation by ion
exchange across the interface of sodium linoleate (solid) and water-ethanol solution (solution)and form noble metal linoleate whereas free sodium ions enter into the aqueous phase (marked
as 1 & 2 in Fig. 2.7(b)). Subsequently, at the designated temperature (which is different fordifferent metals), the ethanol present in solution and liquid phases reduces the noble metal ions
to noble metal at liquid-solid or solid-solution interfaces (marked as 3). Concurrently, the insitu generated linoleic acid adsorbed on the surface of the noble metal nanoparticles with thealkyl chains on the outside, thus making the surface hydrophobic. These nanoparticles being
incompatible in hydrophilic surroundings spontaneously settle at bottom of the container(marked as 4) from where they are collected, washed and re-suspended in suitable liquid toachieve stable colloidal solution.

In this work, for the synthesis of UCNPs a solvothermal process is used, as it is safer thanhydrothermal process. This is described in detail in Chapter 3.

14

Chapter 2

(a)

Pd

Rh

Pt

(b)
LiquidAg

C2H5OH+C18H32O2

PbS

Ag2S

ZnS

CdSe

Semiconductors
YF3

La(OH)3
BaTiO3
TiO
2
ZrO2

3
Solid
2

4

C18H31NaO2CxHyMO2
Reaction

CdS

ZnSe

Phase Separation

Noble metals

Reaction

Au

4

3

Mn+

Na+

1

C2H5OH + H2O

Solution

Rare-earth

Figure 2. 7: (a) Colloidal solution (2% concentration in cyclohexane solution) of various nanoparticles
obtained by hydrothermal process. (b) Schematic showing liquid-solid-solution synthesis strategy achieved byhydrothermal process. Both figures are from reference [57].

2.2.3 Characterization techniques
The characterization techniques for nanoparticles can be broadly classified into two types:
imaging and analysing. Table 2.1 gives brief summary of frequently used both types ofcharacterisation techniques.

15

Chapter 2
Table 2. 1: Some important characterization techniques for nanomaterials.

Characterization Techniques

Obtained Features•

Size & Shapemicroscope (NSOM)•

Topography

Confocal microscopy

•

Near

field

scanning

Transmission

opticalElectron

Microscope (TEM)

Comments

Reference•

Resolution: ~ 50 nm[58,59]Size & Shape•

Lateral Resolution: 100-200 nm

[60]

•

Topography•

Vertical resolution: 400-500 nm•

3D imaging

•

Size

•

Uses transmitted electrons•

Composition•

Operating voltage: 100kV-3MV•

Crystal structure•

Sample thickness: 50-100 nm

•

With

high

resolution[61,62]TEM(HR-TEM)

resolution = 0.02 nm
Scanning Electron Microscope

•

Size

•

Uses secondary and backscattered electrons

(SEM)

•

Microstructure•

Operating voltage: 1kV-3 kV•Composition•

Thin coating of conducting layer is needed to•Topography•

Grain orientation[63,64]

avoid charging if material is not conducting.

16

Chapter 2

Scanning Transmission Electron•

Microscope (STEM)

Surface and interfacial•

Resolution: At atomic level

[65]

[66]

segregation•

Chemical composition

Scanning Tunneling Microscope

•

Image

•

Based on Quantum tunnelling

(STM)

•

Chemical composition•

Atomic level resolution•

Atom movement•

Used for characterizing conducting surfaces•

Common mode of operation: Constant-current
mode & Constant-height mode

Atomic Force Microscopy (AFM)•

Topography•

Variation of STM•

Surface mapping•

Used for characterizing both conduction and•Mechanical properties[67]

non-conducting surfaces•

Common mode of operation: Contact mode &Non-contact mode

Energy Dispersive Spectroscopy
(EDS)

•

Chemical composition•

Usually associated with SEM, TEM and STEM•

Detection limit: 0.1 wt% (bulk materials)•

Inner shell’s electron is knock out by incident[68]electron beam and relaxation of electrons fromouter shell to inner shell produces X-ray.

17

Chapter 2

Electron

EnergyLossSpectroscopy (EELS)•

Chemical composition•

Chemical bonding•

Usually associated with TEM and STEM not [69]SEM•

Measure energy loss of inelastic scatteredelectrons

Infrared (IR) Spectroscopy

Raman Spectroscopy

X-ray Diffraction (XRD)

Dynamic Light Scattering (DLS)•

Chemical composition••

Chemical bonding

•

Size

•

Use laser source normally in UV spectrum•

Chemical bonding•

Complementary to IR spectroscopy

•

Size

•

Use X-ray for measurement, as its wavelength [73]•Crystal orientation•

Strain•Based on Bragg’s law of diffraction

•

Size

•

Measure temporal fluctuations of the light [74]•Surface potentials

Fouriertransformed

infrared(FT-IR) [70,71]

spectroscopy is another variation of this type[72](~ 0.1 nm) is same as atomic spacing of solids.

scattering intensity caused by hydrodynamic
motions in solution.
•

Mostly used for colloidal solution

18

Chapter 2

2.3 Upconverting nanoparticles
2.3.1 Introduction
Photon upconversion, as introduced in the previous section, is a non-linear phenomenon
whereby two or more low energy photons are absorbed sequentially by metastable, long lived
energy states [75,76]. Nicolaas Bloembergen, a Dutch-American physicist conceived this idea
in 1959, during his work on developing an infrared photon detector [77]. He thought ofcounting infrared photons absorbed sequentially by rare-earth or transition metal ions doped ina crystalline material. Unfortunately, due to lack of coherent pumping source he could not
realize this idea at that time, but he shared Noble Prize in Physics in 1981 for his pioneering
work in the field of non-linear optics. The first experimental demonstration of upconversion
was reported by Francois Auzel in 1966 by using Yb3+ ions to sensitize Er3+ and Tm3+ [78].

6s2Host ions5d(0 or 1)

Host ions

5s2 5p6

Host ions4s(1 or 2)

4f(2 to 14)

3d(1 to 10)

1s2-4d10

1s2-3p6

Core

Core

Unfilled Shell

Unfilled Shell

Shielding electron

Bonding Electrons
Host ions

Unfilled Shell

Host ions

Host ions

Bonding Electrons
Host ions

Rare Earth Ion(Lanthanide series)

Host ions

Transition Metal ions
(1st series-Iron Group)

Figure 2. 8: Atomic structure of (Left) Rare-earth ions and (Right) Transition metal ions [79].

The efficient upconversion is achieved using rare-earth elements comprising La, Ce, Pr, Nd,
Pm, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu because of a ‘ladder-like’ arrangement of theenergy-levels having similar spacing and long-life time of the excited states. These elements
are called rare-earth because of the difficulty in extracting them from the earth and their low
availability in nature (106 times less abundant than silicon) [79]. Some of transition metal ions,such as Ti2+, Ni2+, Mo3+ have also shown upconversion, if they are doped in suitable hostmatrix. However, as shown in Fig. 2.8, in case of lanthanide ions, the optically active electronspresent in the 4f shell are partially shielded from influence of external crystal field by its outer19Chapter 2

shells (5s, 5p, 5d and 6s) electrons. This screening from the external crystal field gives raise to
sharp and well-defined spectral features similar to free ion spectra, whereas in contrast, in thecase of transition metal ions, the electrons in the unfilled 3d shell are weakly shielded by onlya single 4s outer shell. Therefore, optical transitions in this case are strongly coupled to thelattice and susceptible to vibrational motions of the host lattice ions (electron-phonon
coupling), thus resulting in broad and undefined spectral features (except in few cases like theR1 and R2 lines of Cr: Al2O3 sharp line is observed) [79].

Central Field

Coulombic Field

Spin-orbit
coupling

Representation:

Representation:

2S+1L

2S+1L

4f95d

5S

4f10

5F
5I

Weak Crystal
Field

J

5I
4
5I
5
5I

6

5I
7
5I
8

For 5 I: S = 2, L = 6
Degeneracy = 1001 Degeneracy = 65

For 5 I5 : J = 5
Degeneracy = 11

No degeneracy

Figure 2. 9: Energy level diagrams showing lifting of degeneracy of trivalent Ln 3+ ions due to various effects.
The energy levels are represented by 2S+1LJ where S, L and J represents total spin, orbital momentum andangular momentum quantum number respectively [79].

The ladder shaped levels in 4fn electronic configuration of trivalent lanthanide ions occur due
to strong electronic repulsion, spin-orbital coupling and the crystal field. For example, in thecase of 4f10, as shown in Fig. 2.9, the total degeneracy in central field approximation is 1001.
However, due to the mutual repulsion of electrons (Coulombic interaction), the degeneracy inthe total spin (S) and the orbital angular momentum (L) is removed. The split energy levels are
represented by 2S+1L and the degeneracy at each energy level is given by (2S+1) × (2𝐿 + 1).
The degeneracy at this level, i.e. the degeneracy in the total angular momentum (J) is further
removed by interaction between S and L (spin-orbital coupling). The energy level at this stage
is represented by (2S+1)LJ and the available degeneracy (2J+1) is finally removed by the weak
crystal field. Therefore, in the free atom each level is reduced to (2J+1) degeneracy but only
when lanthanide ions are doped in a host crystal, this degeneracy is removed. This highlights
20Chapter 2

the importance of host matrix in upconversion process which will be discussed in the next
subsection.
2.3.2 Choice of host lattice
The choice of host lattice is important as the structure of the host lattice determines the distance
between the dopant ions, their relative spatial positions, their co-ordination number and typesof surrounding anions [76]. In the literature, several oxides, fluoride, molybdate, vanadate, etc.
based lattices have been reported. A few of these examples are given Table 2.2. Among thereported lattices, fluoride-based lattices have generally shown high upconversion efficiencies
due to their low phonon energies. The low phonon energy supresses the non-radiative losses
as a greater number of phonons is needed simultaneously to make the transition, thus increasing
the lifetime of the excited states [80].
Table 2. 2: Host lattices used for doping lanthanide ions for upconversion process.

Host Matrix

ExamplesReferences

Oxide

Y2O3, Lu2O3, LaO3, Gd2O3[81–86]

Oxysulfide

Y2O2S, Gd2O2S, La2O2S[87,88]Oxyhalide

GdOF, YOF

[89,90]

Phosphate

LaPO4, LuPO4, YbPO4[91,92]

Molybdate

La2(MoO4)3[93,94]Tungstate

NaY(WO4)2[95,96]

Gallate

Gd3Ga5O12[97]

Vanadate

YVO4

[98]

Fluoride

LaF3, YF3, LuF3, NaYF4,[99–106]

LiYF4, NaGdF4, KY3F10,
KGd2F7, BaYF5

Similarly, the cation site with low symmetry yields higher upconversion efficiency because thelow site symmetries exert uneven crystal-field around the dopant ion, which not only favours
removing the degeneracy of the free-ion states but also increases the 4f-4f transition
21

Chapter 2
probabilities [107]. For example, anisotropic hexagonal phased Na(RE)F4 (RE = Yb3+ or Er3+
or Y3+) exhibit one order of magnitude enhancement in upconversion in comparison to cubic
phased Na(RE)F4 [108]. It can be seen from their schematic representations, given in Fig.
2.10(a) that in the cubic phase equal number of F- cubes contain cations and vacancies whereas
in the hexagonal phase, an ordered array of F- ions offers two type cation sites: one occupied
by Na+ and other randomly occupied by Na+ and RE3+ [108]. The transition from the cubic to
the hexagonal phase can be controlled by controlling the set of experimental variables such astemperature, nature of solvent, reaction time, concentration of metal precursors and size. For
example, a higher temperature and large reaction time favours formation of hexagonal phase
whereas smaller size favours cubic phase due to high surface tension. The TEM images of
cubic and hexagonal phased NaYF4 co-doped with Yb3+ and Er3+ are given in Fig. 2.10(b).
Wang et al. in the same reference, reported that the phase transition of NaYF4 crystal fromcubic to hexagonal can be achieved at much lower temperature and quicker by substituting Y3+(r = 1.159 𝐴̇) with larger sized lanthanide ions such as Gd3+ (r = 1.193 𝐴̇) [108]. They varied
the concentration of Gd3+ and found that for ion concentration more than 30 mol%, purehexagonal phased NaYF4 was obtained. However, the maximum upconversion intensity was
at 15 mol%, as shown in Fig. 2.10(c). The decrease in intensity with increasing Gd 3+ doping
might be due to severe lattice distortion, defect development and electronic influence of the
Gd3+ ions.

22

Chapter 2

(a)

(b)

(c)
3.0

Intensity (a.u.)

Pure Hexagonal
2.0
1.0
Cubic Hexagonal
0.0
0

10

20
30
40
50
Gd3+ concentration (mol%)60

Figure 2. 10: (a) Schematic representation of cubic (top) and hexagonal (bottom) NaREF4 structure [108]. (b)TEM image of cubic and hexagonal phased NaYF4:Yb/Er (20/2 mol%). The scale bar represents 100 nm [109].
(c) The variation of upconversion intensity, obtained by integrating spectral intensity of emission spectra overwavelength in the range of 400-700 nm with Gd3+ concentration [108] .

23

Chapter 2

2.3.3 Choice of dopant
The dopant ions where luminescence takes place, are known as the activator. As shown throughsimple three levels energy diagrams in Fig. 2.11(a), the electron in the ground state (depictedby |1⟩) of the activator ions absorbs an incoming photon and is raised to the intermediate energy
level |2⟩. This process is known as Ground State Absorption (GSA). The intermediate energy
level |2⟩, being a metastable state has a longer lifetime and thus the excited electron has anopportunity to absorb another incoming photon (may or may not be of same wavelength) andafter its absorption it goes to final energy level |3⟩. This is known as Excited State Absorption(ESA). The radiative transition of electron from level |3⟩ to ground |1⟩ emits the light, having
a photon energy almost twice as that of the incoming radiation. In case of Tm3+, it absorbs 4
such NIR incident photons and emits blue fluorescence [13].

Figure 2. 11: Energy level diagram showing (a) Excited State Absorption (ESA) and (b) Energy Transfer (ET)between Sensitizer (S) and Activator (A) ions. Taken from [110].

The quantum efficiency of ESA is very low due to the Laporte-forbidden intra 4f transition.
Therefore, in most of the reported UCNPs, the NIR absorption efficiency of the UCNPs isfurther increased by co-doping the host-matrix with another set of rare-earth ions known as asensitizer. The sensitizer ions (e.g. Yb3+) having higher absorption cross-section in NIR regime,
absorb the incident wave and undergoes excitation from the ground state to the higher state.
These excited electrons while de-exciting back to ground state, transfer the energy to thenearest activator ions, as shown through schematic diagram in Fig. 2.11(b). This transfer ofenergy from sensitizer to activator is known Energy Transfer (ET). There are several factors
which determines the success of ET and according to Dexter’s theory [111], the energy transfer
probability (WS-A), assuming dipole-dipole interaction is given by Eq. 2.1

24

Chapter 2
3ℎ4 𝑐 4𝐴 (𝐸)
𝑓𝑆 (𝐸)𝑓𝑎𝑏𝑠

𝑄

𝑊𝑆−𝐴 = 64𝜋5𝑛4𝜏 × 𝑟6𝑎𝑏𝑠 × ∫ 𝑒𝑚
𝑆

𝑆−𝐴

2.1

,

𝐸4

where ℎ, 𝑐, 𝑛, 𝜏𝑆 and 𝑟𝑆−𝐴 are Plank’s constant, the speed of light, the refractive index, theintrinsic lifetime of the sensitizer and the distance between the sensitizer and activator
respectively. 𝑄𝑎𝑏𝑠 is the integrated absorption cross-section of the activator and the last
integration term gives the overlapping area between normalized emission line-shaped function
𝑆 (𝐸))of the sensitizer (𝑓𝑒𝑚and the normalized absorption line-shaped function of the activator
𝐴 (𝐸))(𝑓𝑎𝑏𝑠
ions. From Eq. 2.1 it can be seen that two critical parameters which determines theenergy transfer probability between the sensitizer and the activator ions are 𝑟𝑆−𝐴 and thespectral overlap between the sensitizer emission and the activator absorption, as shown throughthe schematic diagram seen in Fig. 2.12(a).

(a)

(b)

ET
NIR

Visible
S

A

|3 ⟩

∅�

rS-A
|2 ⟩
� )

Energy (E)Sensitizer emission (� �� �

|2 ⟩

∅�

|1 ⟩

|1 ⟩
S

A

Activator Absorption (� �� � � � )Intensity
Figure 2. 12: Schematic showing (a) two critical parameters for effective energy transfer, i.e. distance between𝑆sensitizer-activator atom and spectral overlap between sensitizer emission (𝑓𝑒𝑚(𝐸)) and activator absorption𝐴(𝑓𝑎𝑏𝑠(𝐸)) [112]. (b) ET followed by ESA [110] .

There are several variations of ET reported in the literature, these variation depending on thecurrent state of activator ions [110]. For example, if ET is used to excite the electrons alreadypresent in intermediate excited state to the final state, then this is known as Excited State
Upconversion (ETU). By contrast, in some cases, ET is used to excite the electrons present inground state of the activator and these excited electrons absorb incoming photons for theirsuccessive excitation, as shown schematically in Fig. 2.12(b). In Successive Energy Transfer(SET), sensitizer ions only absorb the incoming photons, and the activator ion is promoted
25

Chapter 2

from the ground state to the intermediate state and from the intermediate state to the final state
via two consecutive ETs, as shown in Fig. 2.13(a). If the sensitizer and activator ions are
identical and both absorb incoming photons as GSA. However, subsequently the activator ion
goes to a higher state by ET and the sensitizer goes back to its ground (or lower) energy state
after transferring its energy. This is known as Cross-relaxation (CR) and is depicted
schematically in Fig. 2.13(b). In Cooperative Sensitization (CS), as shown in Fig. 2.13(c), twosensitizer ions are involved and both transfer the energy simultaneously to a single activatorion, thus promoting it to higher excited state. There is no need for an intermediate metastablestate in this case. In cooperative luminescence (CR), the two sensitizers transfer their energy
to virtual emitting level which emits upconverted photon on de-excitation, as shown in Fig.
2.13(d).

Figure 2. 13: Energy transfer mechanism: (a) Successive Energy Transfer (SET) (b) Cross-relaxation (CR) (c)Cooperative Sensitization (CS) (d) Cooperative Luminescence (CL) [110].

In Photon Avalanche (PA), the sensitizer ion excites to higher state, through GSA and ESA.
However instead of de-exciting directly to the ground state, the electron goes back to its
intermediate state and transfers the released energy to its neighbouring (identical ion), thus
exciting it to intermediate state, as shown in the Fig. 2.14 [113]. These two ions in the26

Chapter 2intermediate state (say |2⟩) will again cause excitation to the higher state (say |3⟩) byabsorbing incoming photons and again de-excite to an intermediate state and in turn this excites
two more neighbouring ions to the intermediate states. At this state, there will be four ions inintermediate state and again they will undergo excitation and de-excitation to produce eightions in the intermediate state. After the end of these several steps, there will be huge reservoirof ions in the intermediate state. This process was first reported by Chivian et al. [114] in 1979.

Figure 2. 14: Schematic three levels energy diagram showing Photon Avalanche (PA) mechanism [110].

Out of the upconversion processes mentioned, the SET strongly dominates other processes andYb3+ is often used as sensitizer due to its simple energy level configuration [13]. Furthermore,
the concentration of activators in a given UNCP has to be optimum, as on increasing theconcentration beyond that, there will be a decrease in the quantum efficiency. This decrease inquantum efficiency is observed because the excitation energy of the interior ions migrates
through the CR process and eventually decays non-radiatively at the inner or surface defects.
Typically, the concentration of Er3+ and Tm3+ ions are kept less than 3 mol% and 0.5 mol%27

Chapter 2
respectively whereas for the sensitizer (usually Yb3+), it is doped in a high concentration (1820 mol%) [13,48].
As mentioned above, the non-radiative transition between the energy levels plays an importantrole in determining the population density at the intermediate and emitting levels andconsequently, the quantum yield of UCNPs. It can be seen from the multi-phonon, nonradiative relaxation rate constant knr, given in Eq. 2.2, that the non-radiative rate not only
depends on the choice of the host lattice but also on the energy gap between levels [115].
𝑘𝑛𝑟 ∝ 𝑒𝑥𝑝 (−𝛽

Δ𝐸
)
ℏ𝜔𝑚𝑎𝑥

2.2

where 𝛽 is empirical constant of the host, ΔΕ is the energy difference between populated leveland next lower energy level and ℏ𝜔𝑚𝑎𝑥 is the highest energy vibrational mode of the hostlattice. Therefore, for the given host lattice, the activator ions having larger energy difference
are less likely to undergo a non-radiative transition. Moreover, non-radiative decay plays animportant role in the surface quenching effect where the energy from the inner ions propagatesto the surface ions and get lost non-radiatively [116]. The incomplete coordination
environments, the weak crystal field and exposure to high oscillators arising from the surface
impurities, ligands or solvent make the surface ions act an energy sink [117]. Due to the surface
quenching effect, the upconversion efficiency of nanoparticles (having large surface-volume
ratio), is less than seen in their bulk counterpart.
The Jablonski diagram illustrating important radiative and non-radiative energy transition
responsible for upconversion of Tm3+ and Er3+ ions when they are co-doped with Yb3+ is shownin Fig. 2.15(a). Here Yb3+ is acting as sensitizer, has only one excited 4f level of 2F5/2 and it
transfers the energy to the nearest Tm3+ or Er3+ ions through SET. In the visible band, Tm3+shows three prominent peaks corresponding to three transitions, whereas Er 3+ shows fourpeaks, as shown in Fig. 2.15(b) and Fig. 2.15(c) respectively.

28

Chapter 2

1D

(a)

2

1G

2H

9/2

4F
3/2
4F
5/2
4
4F
7/2

Energy

2H
11/2
4S
3/2
3F

4F

2

3F

3

3H
3H

4I

4
2F
5

3F

9/2

9/2

4I
11/2

5/2

980 nm

4I

13/2

4

3H

6

Tm3+

Yb3+

(b)

2F

7/2

4I

Er3+

15/2

630

700

Wavelength (nm)560
630
Wavelength (nm)

700

2H
�
11/2 → � � � /�� � /�
��
9/2 →

420

4F
�
9/2 → � � � /�

560

2H

1G →3F
4
4

Intensity (a.u.)3
4 → H6490

4S�
3/2 → � � � /�

420

1G

1D →3F
2
4

Intensity (a.u.)

(c)

490

Figure 2. 15: (a) Partial energy levels diagram showing upconversion phenomenon of Tm3+ and Er3+ ions whenYb3+ act as a sensitizer. The dash-dotted, dashed, wavy and solid line represent the NIR photon excitation,energy transfer, multi-phonon relaxation and emission processes respectively [48]. (b) A typical upconversion
spectrum of Tm3+ in visible region (c) Typical upconversion spectrum of Er 3+ in visible region. (b) and (c) aretaken from [118].

29

Chapter 2

Table 2.3 shows major emission wavelength and corresponding energy level transitions of few
activator ions. Among them, Ho3+, Tm3+ and Er3+ are widely used as activator and interestingly
for all these three activators, Yb3+ acts well as sensitizer [119]. Even though, these three ionshave multiple emission peaks (ref. Table 2.3), it is possible to supress all the peaks except one.
In 2011, Wang et al. reported that doping Ho3+, Tm3+ and Er3+ in KMnF3 crystal results insingle band upconversion. They observed the lowest energy peak in all three cases i.e. peakcentred around at 650 nm in Ho3+ and Er3+ and 800 nm for Tm3+. The reason for suppressionof the higher energy peaks is efficient non-radiative energy transfer from the higher levels to
Mn2+ and then back to the activator at a lower level [120] . One year later, Tian et al. showed
the same effect in NaYF4: Yb3+, Er3+ (18/2 mol %) by replacing the concentration of Y3+ usedwith 30 mol% Mn2+ ions [121]. This single band upconversion was independent of the external
temperature, the excitation laser power and the amount of the dopant Yb3+ (0-28 mol%).
Table 2. 3: The major emission wavelengths and corresponding energy transition level of some of typicalactivator ions [122].

Activators Major

Emission Corresponding Energy transitions References

wavelength (nm)Pr3+489, 526, 548, 618,

3

P0→3H4,1

I6→3H4,

3

P0→3H6, [123–127]

652, 670, 732, 860

3

Sm3+

555, 590

4

G5/2→6H5/2, 5G5/2 →6H7/2[128,129]Eu3+590, 615, 690

5[128,129]

Tb3+

490, 540, 580, 615

5

P0→3F2, 3P1→3F3, 3P0→3F4, 1I6→ 1G4

D0→7F1, 5D0→7F2, 5D0→7F4
D4→7F6,

5

D4→7F5,

5

D4→7F4, [128,129]

5

D4→7F3

Dy3+

570

4

F9/2→6H13/2[128,129]

Ho3+

542, 645, 658

5[130–132]Er3+411, 523, 542, 656

2

S2→5I8, 5F5→5I8
H9/2→4I15/2,

2

H11/2→4I15/2, [91,130,133,134]

4

S3/2→4I15/2, 4F9/2→4I15/2

Tm3+

294, 345, 368, 450,1

I6→3H6,1

I6→3F4,

1475, 650, 700, 800

1

1

G4→3H6,

1

D2→3F4,

D2→3H6, [135,136]
G4→3F4,

3

F3→3H6, 3H4→3H630

Chapter 2

2.3.4 Improvement of upconversion efficiency
The one of key drawback of UCNPs is its low upconversion efficiency (maximum reported todate is still 5% for irradiation below 100 W/cm2 ) [137,138]. In the literature, several methods
have been proposed to increase the upconversion efficiency such as the core-shell method [13],super high-power or broad-band excitation [139,140] , plasmonic enhancement [140],
manipulating the local crystal field around activator ions by locally distorting the crystal lattice[120,141], energy clustering at the sub-lattice and the use of synthetic infrared dyes to amplify
the sensitization process [142–144]. Among the these, the following three techniques areelaborated details in due to their frequent use in the literature their underlying novelty.
A. Core-shell technique
One way to prevent losses by surface quenching effect is to passivate the surface of UCNPs by
a growing few nanometers of epitaxial shell layer, as shown by the schematic in Fig 2.16(a).
This technique was first reported by Yi and Chow in 2007, where they grew a 1.5 nm inert
shell of NaYF4 on 7.7 nm hexagonal phased NaYF4: Yb, Er (or YB, Tm) core. After
passivation, the upconversion was enhanced by a factor of 7.4 and 29.6 for Er3+ and Tm3+
respectively [145]. They further coated core-shell structures with 25% octylamine and 40%
isopropylamine modified poly(acrylic acid) (PAA) to make it water soluble. After the successof this homogenous shell growth, researchers have not only demonstrated an upconversion
efficiency improvement with the heterogenous shell i.e. a shell having a different chemicalcomposition than the core but also a doped shell with other rare-earth ions to achieve several
unique properties. For example, Liang et al. reported 1.7 times enhancement of upconversion
on coating a single layer of NaGdF4 on NaYF4: Yb, Er, as shown in Fig. 2.16(b) [146].
Similarly, Li et al., coated 16 monolayers (~ 8 nm) over the core through one pot successive
layer-by-layer synthesis [147]. Capobianco and co-worker showed that doping NaGdF4 shellwith Yb3+ further increases the NIR absorption and thus the overall upconversion efficiency incomparison to the inert shell [148]. A few research groups have coated silica shell on core or
core-shell UCNPs in to make them water soluble/stable and thus enabling them suitable forbiofunctionalization [13,146,149].

31

Chapter 2

(a)

1.2

(b)

NaYF4: Yb, Er

Intensity (*105 a.u.)

NaYF4: Yb, Er@NaGdF4

Core

Shell

0.8

0.4

0.0
450

550

650

750

Wavelength (nm)Figure 2. 16: (a) Schematic showing single inert epitaxial layer grown over core (b) The 1.7 fold enhancement
in upconversion after coating the 29 nm core (NaYF4: Yb, Er) with 2 nm NaGdF4 layer [146].

B. Plasmonic enhancement
Plasmonic resonance involves large collective oscillation of free electrons in response to theexternal electromagnetic (EM) waves when the frequency of the incident EM waves matches
the plasma frequency of the used plasmonic structure. At plasmon resonance, the incident EM
field gets locally concentrated, and this concentration of electric and magnetic fields can beused to enhance absorption and the emitter’s radiative decay rate. However, the same process
also enhances the non-radiative decay rate and if structures are not properly designed, insteadof enhancement, quenching is observed. Therefore, for enhancement, the spectral overlap
between the plasmon resonance and absorption and/or emission frequencies of the UCNPs,
polarization, field overlap (relative distance between plasmonic structures and UCNPs),
plasmonic structure materials and incident pump power have to be carefully considered [150].
For example, Lu et al. reported a 38.8× enhancement with an incident power density of 2
kW/cm2, but the enhancement reduced to 4.4×, on increasing the pump power above 40
kW/cm2 [151]. Similarly, a 5 nm increase or decrease of the distance between UCNPs andmetallic nanospheres film from its optimum distance of 10 nm, reduces the enhancement from45× to 5× [152].

Plasmonic structures made of noble metals such as gold and silver are mostly used forupconversion enhancement [150]. Amongst these, even though silver has low losses at
plasmonic resonance, in several cases gold showed better enhancement. For example, Deng etal. showed that with silver nanoparticles the enhancement in green and red emission were ~32

Chapter 2
4.4 and ~ 3.5 respectively whereas with a Au nanoshell the observed enhancement was ~ 9.1(for green) and 6.7 (for red) [153]. These results show that several other factors including
spectral overlap or field overlap play prominent effect in the upconversion enhancement.

(a)

(b)

(c)

(d)

Figure 2. 17: Upconverter encapsulated metals [154].

In the literature, several variations of localized plasmonic structures such as rods, core-shell[155], core-spacer-shell [153,156], prism [157], spheres [158] as well as extended structures
including waveguides [159], arrays of holes [160] or pillars [161] have been reported. Among
the reported localized structures, two prominent variations are where the metal is core and the
UCNPs are deposited on top of it (upconverter encapsulated) or the UCNP is a core and metal
is deposited on the top (metal encapsulated). Some of the reported upconverter encapsulated
structures are seen in Fig. 2.17.

C. Energy clustering at subatomic level
As discussed previously, an increase in the doping concentration of the sensitizer or activator
leads to quenching of the upconversion which can be attributed to migration of the excitationenergy to the lattice or surface defects. This propagation of energy is more likely in the case ofhighly symmetric structures such as cubic phased NaYF4 and CaF2, where energy can travel
isotopically in all three directions, as shown in the schematic in Fig. 2.18(a; type 1). In contrast
to that, for structures like NaEuTiO4, the propagation of energy between Eu3+-Eu3+ ions is more
restricted in a plane due to the relative distance between the planes, as shown in Fig. 2.18 (a;type 2). This transfer of energy can further be restricted to 1D chain crystal lattices (shown in
Fig. 2.18 a; type 3) and it is often observed between Eu3+-Eu3+ in EuMgB5O10. Based on thesefindings, Liu and his co-workers realized that the migration of energy depends essentially on
position of dopants than their doping concentration and went on localizing the energy exchange
within arrays of discrete Yb3+ tetrad clusters as shown in Fig. 2.18(a; type 4) [162]. Thus,
33

Chapter 2

minimizing the long-distance energy migration losses, they demonstrated for the first timefour-photon upconversion (violet emission) from Er3+ ions by synthesizing orthorhombic
KYb2F7:Er3+ (2 mol%; 98 mol% sensitizer ions) nanoparticles. The TEM image of
nanoparticles as shown in Fig. 2.18(b). The simplified partial energy showing underlying
energy transfer mechanism for four-photon upconversion is given in Fig. 2.18(c).

Figure 2. 18: (a) Schematic representation of energy migration in case of various sublattices (b) TEM
micrograph of KYb2F7:Er3+ (2 mol%) (c) Simplified partial energy showing underlying energy transfer
mechanism for four-photon upconversion. Taken from [162].

34

Chapter 2

2.3.5 Applications of upconverting nanoparticles
A. Biological Imaging
The usage of UCNPs for biological imaging over other down-converting conventional
fluorophores such as organic dyes and QDs offers advantages in term of narrow and wellseparated (from excitation) emissions, immunity towards photo-bleaching and photo-blinking(often reported in organic dyes) and low cytotoxicity (unlike QDs) [163]. Furthermore, the NIR
radiation in comparison to UV has better penetration in human tissues, high signal to noise
ratio (due to lack of background autofluorescence) and less photo-damage.

In the literature, authors have reported the usage of UCNPs for several imaging applications
such as in in-vitro cell and tissue imaging, in vivo organism and animal imaging, fluorescence
diffuse optical tomography and multimodal imaging [163–167]. Often, UNCPs are madeselective to a certain target by a coating antibody. For example, Wang et al. linked rabbit antiCEA8 antibody to silica-coated amino-modified UCNPs to make it selective to HeLa cells[168]. On incubating antibody modified UCNPs with HeLa cells in physiological conditionsfor 1 hour, the carcinoembryonic antigens (CEA) present on HeLa cell membrane react withthe attached antibody, thus resulting in labelling of HeLa cells with UCNPs, as shown in Fig.
2.19(a). The bright and fluorescent images shown in Fig. 2.19 (b-d), prove high selectivity withthis kind of immunolabeling. Similarly, Jiang et al. used anti-Her2 antibody and folic acidconjugated NaYF4: Yb, Er UCNPs for labelling and fluorescent imaging of SK-BR-3 cells andHT-29 cells, respectively [169].

Figure 2. 19: (a) Schematic showing immunolabeling of HeLa cell. HeLa cell after incubated with rabbit antiCEA8 Ab-conjugated UCNPs (b) bright field (c) dark field and (d) superimposed image. Taken from [168].

35

Chapter 2

B. Cancer therapy
The nanoparticle-based Cancer therapies proposed have advantages over traditional cancer
therapies like chemotherapy and radiotherapy in terms of better selectivity and localized
treatment. Through nanoparticles, the cell apoptosis (death) is caused by two popular two
popular methods i.e. by localized thermal ablation (known as Photo-thermal therapy (PTT))
and/or by creating oxygen/water deficiency inside cells with the help of a photosensitizer(known as Photo-dynamic therapy (PDT)). The photosensitizer is a special chemical compound
which generates radical oxygen at a particular optical wavelength. The generated radical
oxygens react with available oxygen or water present inside the cell thus causing theirdeficiency. In PDT, normally nanoparticles act as a carrier.

The common steps involved in PDT or PTT are shown through schematics in Fig. 2.20. In
short, the nanoparticles are injected in blood and having size in nanometres, they travel
unhindered across the body with the help of blood circulation. After 24-72 hours (dependingon the nanoparticles involved) these nanoparticles get accumulated in tumor cells which isfavoured by the enhanced permeation and retention (EPR) property of cancer cells. Due to
EPR, the cancer cells (in order to multiply fast) extract more nutrients from the blood and retain
them for longer time. Sometimes antibodies may be coated on nanoparticles to increase cellselectivity. Once nanoparticles are accumulated inside cells, cells apoptosis can be carried out
by shining a suitable radiation on the cells. The unused nanoparticles are ejected out of bodythough urine and the same technique is also used for localized drug and gene delivery.

Figure 2. 20: Schematic showing steps involved in PTT and PDT.

36

Chapter 2

In the literature, several groups have reported in-vivo and in-vitro usage of UCNPs for PDT,PTT and drug delivery [170–172]. However, since UCNPs cannot generate a heating effectunlike GNPs, they have to conjugate with some other NIR absorbing dye to perform PTT. For
example, Chen et al. coated UCNPs (NaGdF4:Yb:Er) with bovine serum albumin (BSA) for
better stability in physiological environments and further conjugated them with Rose Bengal(RB) and IR825 dye for PDT and PTT respectively [173]. The RB absorbs the upconverted
green light emitted from UNCPs to induce photodynamic cell killing, but, the absorbance ofIR825 does not overlap with upconversion excitation and emission wavelengths, thus enabling
nanoparticles to experience photothermal ablation under were 808-nm laser irradiation. The
main challenge with this method still lies in treating a tumour buried deep inside the tissue.

C. Energy conversion
In the solar spectrum, the percentage of NIR light is ~ 55 % in comparison to visible and UV
radiation which are at ~43% and ~5%, respectively. Therefore, the ability of UCNPs to convert
light in NIR spectral region to visible and UV radiation is a particular benefit for the field ofenergy conversion, especially for applications such as solar cells or the use of the TiO2 based
photocatalytic reaction [174–176]. Li et al. used NaYF4:Yb3+/Er3+/Gd3+ nanorods with Au
nanoparticles or shells and spin coated on hydrogenated amorphous silicon (a-Si:H) to obtain16 to 72-fold enhancement in a short circuit current [177]. In this work, narrow-band 980 nm,
1100 mW laser light source was used for excitation. The performance of the UCNPs can befurther increased, if their narrow-band excitation is engineered to allow broadband excitation.
One of such schematics was proposed by Hummelen and his team, where they used the broadband absorption of organic dyes to sensitize the upconversion process through Forster resonanttransfer process, as shown in Fig. 2.21(a) [143]. As a proof of concept, the authors used acarboxylic acid-functionalized derivative of commercially available cyanine dye to excite 𝛽phased NaYF4: Yb, Er with light from 800 nm, 2 mW continuous wave laser and reported ~3300 enhancement in the overall upconversion emission. The possibility of tailoring theabsorption of organic dyes to the entire NIR range makes this method really a versatile anduseful.

37

Chapter 2

Figure 2. 21: Schematic showing: (a) organic dye (acting as antenna) sensitized upconversion process [143] (b)photocatalytic reaction process using TiO2-upconverting core-shell nanoparticles [178].

In contrast to solar cells, the photocatalytic reactions using TiO2 as a photocatalyst, needs UVlight for initiation as the band gap of TiO2 is around 3.2 eV [179]. Among the semiconductor
based photocatalysts, TiO2 is preferred because of several associated advantages such asstability, high photoactivity, low-cost, and being non-hazardous to humans and theenvironment [180]. As with only 5% of solar spectrum in the UV (on earth), using solar light
as a photocatalyst is a highly non-efficient process. Therefore, in 2010, Qin et al.
developed YF3:Yb3+, Tm3+/ TiO2 core/shell nanoparticles to utilize the NIR region of the solar
spectrum where they upconverted the incident NIR to UV with the help of Tm3+ ions, as shownin the schematic in Fig. 2.21(b). Similarly, Obregon et al., doped TiO2 with Er3+ and showed
an improvement in the photocatalytic efficiency for both the UV and NIR spectrum [181]. The
reason for the increased efficiency in the UV was attributed to an enhanced electronic charge
separation process in the presence of Er3+ ions and an increase in NIR absorption due toupconversion process. A review paper dedicated to upconversion based semiconductor
photocatalysts has been recently published [179].
The reported work, showing ‘proof of concept’ research, highlights the rich potential of UCNPs
in the field of energy conversion. However, actual devices designed specifically for ‘out-oflaboratory’ usage are still far away, as most of works reported used NIR laser or simulated
sunlight irradiation. The use of actual sunlight irradiation and subsequent optimization of thedevice configuration needs to be performed before any commercial devices could realisticallybe made available on the market.

38

Chapter 2

D. Securities
UCNPs are good candidates for security applications including barcodes, fingerprint
detections, security printing with upconversion ink, and multiplexed encoding [112,182–185]
for example. Illustrating Wang et al. coated NaYF4:20%Yb, 2%Er with lysozyme binding
aptamer to detect fingerprints on the problematic surfaces, i.e. those surfaces which show
strong fluorescence on UV excitation like household marble, as shown in Fig. 2.22(a) [182] .
It can be seen from the figure that the obtained fingerprint in case of using quantum dots ismasked by the strong background fluorescence of the marble (top) whereas in the case of NIR
excitation, the high signal to noise ratio and consequently a clear image (bottom). Similarly,
Xu and his team produced upconverting nanoparticle-based inkjet ink to print high resolution
and high throughput anti-counterfeit patterns [183] .One of such printed patterns is shown in
Fig. 2.22(b).

Figure 2. 22: (a) Actual sized and magnified fluorescence image in the case of quantum dots (top) and UCNPs(bottom) [182]. (b) The printed paper with the upconversion ink in visible light (top) and in 980 nm light(bottom) [183]. (c) Overlapped images printed with three different 𝜏 − 𝑑𝑜𝑡𝑠 (top), having distinct lifetime of52, 159 and 455 𝜇s (middle) and pseudo colour is used to indicate the luminescence lifetime of each pixel(bottom) [184].

The conventional fluorescence colour coding schemes suffer from drawbacks like spectral
overlap and background interference, thus increasing the complexity of the setup needed. In
2014, Lu et al. demonstrated new luminescence lifetime decay (temporal) multiplexing by
precisely tuning the decay lifetime of Tm3+ ions, co-doped with Yb3+ in NaYF4 nanocrystals(called ‘𝜏 − 𝑑𝑜𝑡𝑠’) [184]. The authors varied the decay lifetime (in the blue bands) of 𝜏 − 𝑑𝑜𝑡𝑠from 25.6 𝜇𝑠 to 662.4 𝜇𝑠 by changing the relative distance between the Tm3+ and Yb3+ ions,39

Chapter 2

achieved simply by manipulating their doping concentrations. Figure 2.22(c) shows one of theapplications of 𝜏 − 𝑑𝑜𝑡𝑠 in security, where three 𝜏 − 𝑑𝑜𝑡𝑠 with a distinct lifetime of 52, 159
and 455 𝜇s was used to print three overlapping images. The top image shows the unresolved
image with intensity-based luminescence technique which can be resolved with time-resolved
scanning.
E. Optical storage
In 2010, Yan and his co-workers designed a rewritable optical storage approach with a nondestructive readout mechanism by depositing a monolayer of 𝛽 −NaYF4: Yb, Er using bottomup assembly method and subsequently coating organic photochromic diarylethene derivatives
on it [186]. The used organic dye shows photoisomerization on shining UV light (𝜆 = 325 𝑛𝑚)
and thus reduced photoluminence (PL) around 540 nm (represents state “0”) and on shining
visible light (around 550 nm) reverse photoisomerization happens PL was restored to its
original value (represents state “1”). Therefore, authors used visible light and UV light for
writing and erasing the data respectively. Since, the absorption of dye matches with Er3+
upconversion emission, the change in intensity of PL on NIR exposure can be used to read thestored data. The usage of NIR wavelength for readout reduces the chance of destructive readoutbecause NIR photons do not have enough energy to trigger any molecular transition in the dye.
F. Sensors
UCNPs have been used to realise sensors in several fields to detect (but not be limited to) fields
such as biomolecules, chemical ions, gases, pH, mechanical force and temperature [14,187–
192]. Since, the luminescence of UNCPs is quite stable and is affected by the external
environment, for sensing in most of the cases, they are used as nano-lamps, i.e. to photoexcite
some other suitable chemical dyes or materials, whose absorption or emission is dependent on
the substance being sensed. For example, to detect O2, the UCNPs (NaYF4: Yb, Tm) was
incorporated with a cyclometalated iridium(III) coumarin complex [Ir(CS)2 (acac)] in a thinlayer of ethyl cellulose [193]. The absorption peak of [Ir(CS)2 (acac)] at 468 nm overlaps withthe 455 nm and 475 nm emission peaks of Tm3+ ions and its O2 sensitive emission peak present
at 568 nm is then used for detection. The same group (led Wolfbeis), demonstrated sensing ofpH and consequently acidic gases like CO2 and NH3 using the same principle [187,188,194].
The change in spectrum of NaYF4: Yb, Er due to the variation of CO2 and NH3 is given in Fig.
2.23. The dyes used for sensing CO2 and NH3 were bromothymol blue and phenol red
respectively.
40

Chapter 2

Figure 2. 23: The upconversion emission spectra of (a) CO2 sensor [188] (b)NH3 sensor. The spectra arenormalized to a peak at 655 nm [187].

For temperature sensing, the ratiometric emission from the thermally coupled radiative energy
levels (TCL), i.e. influenced by the population of these levels are related through Boltzmann’sconstant is normally used [15,195,196] . For TCL, the energy difference between the adjacentradiative level should be between 200 cm-1 and 2000 cm-1, as for energy levels having an energy
difference above 2000 cm-1 are not thermally coupled and for energy difference below 200 cm1, the radiations from these two levels are hard to differentiate [197]. Some of the TCLs used

are Er3+: 4S3/2/2H11/2; Tm3+: 3F2,3/3H4; Nd3+: 4F7/2/4F3/2, 4F7/2/4F5/2, 4F5/2/4F3/2; Ho3+: 5G6/3K8[197]. The presence of the natural inbuilt ‘reference’ reduces the influence of the external
condition on the sensor performance. The UNCPs are used to measure the temperature insidebiological cells as well as the lanthanide ions which are doped in glasses to developed
temperature sensors [195,198]. The combination of UCNPS and polymers has not been
explored in the literature for temperature sensing application and a study of work in that fieldform the basis of the research of this thesis, which will be discussed in more details in the next
chapter.
Table 2.4 summarises few important diverse applications of upconverting nanoparticles
reported between 2010-2020.

41

Chapter 2
Table 2. 4: Summary of few important applications of upconverting nanoparticles (used in diverse fields) reported between 2010-2020.

Applications

UCNPs

Associated modifications

Excitation

Comments

Reference

Wavelength
Sensing
CO2

NaYF4: Yb, Er

bromothymol blue (BTB)

980 nmGreen band emission of UNCPs [188]overlaps with the absorption of
BTB.

NH3

NaYF4: Yb, Er

phenol red

980 nmThe absorption of phenol red [187]overlaps

with

green

band

emission of UNCPs.
O2

Hg2+ ions

NaYF4: Yb,Tm

NaYF4: Yb (20cyclometalated

iridium 980 nm

UCNPs

and

iridium(II) [193](III) coumarin complex

complex is incorporated in a[Ir(CS2 (acac)]thin layer of ethyl cellulose.

ruthenium complex (N719) 980 nm

Emission of Er3+ around (541 [192]mol%), Er (1.6nm) overlaps with absorption ofmol%), Tm (0.4N719 which is sensitive to Hg2+

mol%)

ions.

Emission

from

Tm3+

(around 801 nm) is used forreference.

42

Chapter 2

Temperature

NaYF4: Yb, Er

Embedded in PDMS

980 nmLinear response is observed [199]between 295 K – 495 K.

Nano

to

Micro- 𝛼, 𝛽 −NaYF4: 18% Mn2+

newton forcesYb, 2% Er

UC excitation =The crystal field changed by [200]980 nmapplying mechanical force. The

PL

excitation= reported force is per particle.

488 nmCancer Therapy
Drug delivery

NaYF4: Yb,Tm @NaYF4 core-shell+ mesoporous
silica cell

antitumor drug
doxorubicin (Dox)980 nmDox could be selectively [170]releasedthroughthephotocleavage of the o nitrobenzyl (NB) caged linker
by the converted UV emission
from UCNPs.

Energy Harvesting
Photocatalytic

𝛽 −NaYF4:

activity

Tm

Yb, TiO2

980 nmThe emission of Tm3+ ions [175,176,178]
matches with absorption of
TiO2 (in UV).

43

Chapter 2

Yb3+ -doped ZrO2
(28 mol%)-

980 nmEnergy transfer to host lattice [201]through multiphonon relaxation
cause thermal radiation.

Solar Cells

𝛽- phased NaYF4: Derivative of cyanine dye, 800 nm
Yb, ErBroad-band emission of IR-806 [143]is absorbed by Er3+ ions.

IR-780 (called as IR-806 in
paper)
Security
relative •Fluorescence life- NaYF4:Yb3+, Tm3+

Variation

time multiplexing

distance between Tm3+ and

in

Yb3+

Excitation time Lifetime changes is observed by [184]= 200 𝜇𝑠•changing

relative

distance3+
Detection time between Yb (sensitizer) and= upto 3.8 ms

Tm3+ (activator) which was
obtained by varying the doping
concentration.

Upconverting•

Inkjet printer Ink•

For green•

Hydrophobic ink :980 nmMinimum resolution: 200 𝜇𝑚

fluorescence

90:10 to 70:30 v:v

Printing speed: 12 pages per

NaYF4:Yb3+,

cyclohexane: glycerol

minuteEr3+

trioleate

For blue
fluorescence:

•

[183]

Hydrophilic ink :85:15 to 65:35 v:v
ethanol-water solution
44

Chapter 2
NaYF4:Yb3+,(1:9 v:v

Tm3+

ethanol:water):glycerol+

Sodium

Sulfonate

Dodecyltocontrolsurface tension
FingerprintNaYF4: 20% Yb3+, lysozyme binding aptamer

detection

2% Er3+980 nmUsing cocaine binding aptamer, [182]cocaine detection is possible

LasingMicrolaser~5

NaY0.99Tm0.01F4

Coated@NaY0.8Gd0.2F4

polystyrene beads

on

𝜇m •
•

Excitation:

Based on whispering gallery [202]1064 nmmode.

Lasing: 800 nm

Miscellaneous
Optical storage

𝛽 −NaYF4:
Er3+

Yb3+, diarylethene derivatives•

Read: 980 nm

The used organic dye shows an [186]•Write: visible

absorption band centred aroundband

550 nm (represents state “0”) on

Erase:325 nm

shining•visible

light

and,

disappears (represents state “1”)on exposing it to UV.

45

Chapter 2

Super microscopy

NaYF4:Yb3+, Tm3+

High

concentrationof •Tm3+ ions (8 mol%)•

Excitation =Based on Stimulated Emission [203]980 nm

Depletion (STED) techniques.

(Gaussian)Resolution obtained = 28 nm

Depletion
808

=
nm

(doughnut
shape)
RGB

Temporal NaYF4 doped withcolour tuning

Core-shell Nanocrystal•

Yb3+, Nd3+, Tm3+,•

Ho3+ and Ce3+•

808 CW (for

Nd3+ and Yb3+ was used as [204]Blue emission)

sensitizer for 808 nm and 980

3+980 short pulse nm excitation respectively. Ce(for Greenwas co-doped with Ho3+ in theemission)same shell layer to facilitate the980 nm long

red emission of Ho3+.

pulse (for Red
emission)
Electrogenerated

NaYF4: Yb (20chemiluminescence mol%), Er (2%)(ECL)

Graphene. Na2S2O8 wasused as co-reactant.

-4 V to 0 V

An improvement of 4.96-fold in [205]
ECL was observed on using
Graphene. NaYF4/Yb,Er was
excitedbytheoxidation-

reduction excitation pathway.
46

Chapter 2

2.4 Gold nanoparticles
2.4.1 Introduction
Among the reported metallic nanoparticles, nanoparticles realised from gold are of great
importance because of their inertness, biocompatibility, well understood synthesis methods andsurface modification processes and the possibility of synthesizing them in various sizes andshapes such as rods, spheres, shells, cubes, cages, as shown in Fig. 2.24. Moreover, due tolonger circulation in the blood, gold nanoparticles are widely used for biomedical purposes.
Specifically, nano-shells and nano cages are preferred for drug delivery and the use of a nanostars are preferred where large surface areas are needed.

Figure 2. 24: Five different structures of nanoparticles realised using Gold (a) Schematic representations (b)TEM images (c) Colloidal solutions showing tuneable optical properties obtained by changing shapes ofnanoparticles during synthesis [206].

Even though, the evidences show the usage of GNPs for centuries, even since the Roman
Empire, it was in 1857 that Michael Faraday first synthesised of colloidal solution of GNPs inscientific ways and studied its optical properties [3]. Turkevitch, in 1951, reported a simple
method of realising a stable colloidal solution of ~20 nm (average diameter) GNPs. These
nanoparticles were reduced from their ionic state and stabilized with citrate ions [207]. Thissynthesis process, known as the Turkevitch method, is still one of the most widely used

47

Chapter 2

methods because of its simplicity. In 1994, Brust et al., introduced straightforward ways toobtain thiol-capped, highly stable GNPs [208]. Similarly, the simple and convenient approachof seeded growth synthesis of asymmetric GNRs was reported in 2001 [209], which thenopened the door for a number of GNRs based applications.
Like other metallic nanoparticles, the majority of the applications are based on the LSPR effectobserved in the visible wavelength region, as is discussed in the next subsection.
2.4.2 Localized surface plasmon resonance
The plasmonic resonance is defined as in-phase oscillation of free electrons of metals in
response to the oscillating electric field component of incident EM wave, as shown
schematically in Fig. 2.25(a). In case of symmetric structures like gold nanospheres or nanocages, nano shells only a single resonant peak is observed as shown in Fig. 2.25(b). Mie in
1908, developed the theory explaining the LSPR effect in the spherical nanoparticles ofarbitrary size [210]. However, now with the advancement of computers and computational
software, mostly simulations are used to design and study the effect of LSPR, especially in thecase complicated structures.
(a)

(b)

Metal
sphereElectron cloudAbsorbance (a.u.)1

Electric
field

0.8
0.6
0.4
0.2
0
400

500

600

700

800

Wavelength(nm)Figure 2. 25: (a) Schematic illustration of LSPR excitation for symmetric GNSs (b) Typical UV-Vis spectrum of
GNSs showing single plasmonic resonance peak.

In case of asymmetric structures, such as GNRs, electrons can oscillate in two different
directions. If the oscillation of the electrons is along the longer dimensions, it is known asLongitudinal LSPR (L-LSPR), whereas, if the oscillation of electrons is in the shorter
dimension, it is known as Transverse LSPR (T-LSPR), as shown through the schematic in Fig.
2.26(a). These two different SPR resonances give raise to two distinct peaks in UV-Vis
spectrum at shown in Fig. 2.26(b). The larger peak, corresponding to L-LSPR is highly
sensitive to the external refractive index (surrounding the GNRs) and can be tuned from thevisible to the NIR region by simply changing the aspect ratio of GNRs, (ref. Fig. 5.1(a)).
48

Chapter 2

(a)

(b)

Electroncloud
Metal rod
Longitudinal electron Oscillation
Electric
field

Absorption (a.u.)Electric
field

1

0.5

Longitudinal
plasmon band
Transverse
plasmon band

0
400

600

800

1000

Wavelength (nm)Metal rod
Electron cloudTransverse electron Oscillation

Figure 2. 26: (a) Schematic illustration of LSPR excitation for asymmetric GNRs (b) Typical UV-Vis spectrumof GNRs showing two resonance peaks.

The model describing the response of GNRs has been developed by Gans in 2005 [211]. Thismodel will be dealt in more details in Chapter 5 of this thesis, where it is a pivotal indevelopment of an algorithm to determine the distribution of aspect-ratio of GNRs in a
colloidal solution.

2.5 Summary
In this chapter, a comprehensive review of the underpinning work on nanoparticles with themain focus on Upconverting and Gold nanoparticles has been presented. In the beginning,several important nanoparticles relevant from the point of view of sensing, emphasizing theirsynthesis and characterization techniques have been introduced. Thereafter, the underlying
physics of upconverting nanoparticles and their applications have been discussed in detail. This
Chapter ends with brief discussion of gold nanoparticles and the related LSPR effect.
The review shows that research into upconverting nanoparticles is still in a nascent stage. Even
though, a number of promising applications have been demonstrated in the past two decades,
although commercial products based on the work outlined are still far away, mostly due to low
quantum efficiency and bulky characterization system. The latter problem has thus beentackled in the work of this thesis and addressed, to an important extent, by using a portable
optical fibre-based characterization system, as shown through the current work and which will
be explained in detail in the subsequent Chapters.

49

Chapter 3

Chapter 3
Optical fibre thermometry using ratiometricgreen emission from an upconverting
nanoparticles-polydimethylsiloxane composite
3.1 Introduction
The importance of temperature measurement to industry can be judged from the fact thatapproximately 75-80% of the sensors available on the market are temperature sensors [212].
Among the available range of temperature sensors, fluorescence-based temperature detection
is distinctive over conventional electrically-based detection for a number of reasons, including
intrinsic safety and immunity to stray electromagnetic radiation, for example [213,214].
Optical fibre-based temperature sensing devices using fluorescence from a well-chosen,
appropriate material respond well to the demand for reliable and low-cost sensors needed forrugged environments, such as monitoring of transformers in a transmission grid andtemperature monitoring in oil refineries, coal mines, electrical transport infrastructure and fire
detection, where conventional measurement techniques may not be safe or subject tointerference [15,195]. Optical fibre grating-based sensors can measure elevated temperatures,
but often use expensive interrogation systems [215], whereas in comparison, fluorescencebased detection can provide a lower-cost alternative solution due to relatively inexpensive
excitation and detection techniques of the optical signals involved [216].
The most commonly used down-converting fluorescent materials, (i.e. those where λexcitation <λemission) for temperature sensing are organic dyes and quantum dots [217,218]. However,organic dyes frequently suffer from a photo-bleaching effects, especially in the vapour phaseand therefore cannot be used for extended periods [219]. Further, most quantum dot-based
devices have problems with cytotoxicity and often use an excitation wavelength in theultraviolet part of the spectrum, where prolonged exposure may cause photodecomposition of
the samples [220]. These problems associated with down-converting materials can beovercome by using another class of fluorescent materials know as up-converting (UC)materials where, as the term “upconversion” suggests, the emission of the shorter wavelength50Chapter 3
results from absorption of two or more longer wavelength (and therefore less energetic)
photons. By comparison with conventional nonlinear UC techniques such as simultaneous twophoton absorption and second-harmonic generation, UC is achieved by sequential absorptionof two or more such photons. Rare-earth (RE) group elements (mainly Er3+, Ho3+ and Tm3+)
are a natural choice for low pump-intensity UC because of their ladder-like metastable energy
bands, naturally created in the 4fn electronic configuration due to electronic repulsion and spinorbit coupling [13,78,112]. This has been discussed in details in the previous chapter of thisthesis. Furthermore, such RE3+ ions based on UC typically exhibit large anti-Stokes shifts[112], sharp emission lines [221] and temperature-dependent emissions, provided the tworadiative energy levels have an energy difference of between 200 cm-1 and 2000 cm-1 [222–224]. The populations of these thermally coupled levels (TCL), related through the Boltzmann
distribution, provide a natural ratiometric temperature detection approach, in that way reducing
the influence of external conditions on the sensor performance and creating an inbuilt‘reference’ channel [196,197,225,226].
As can be seen from the literature, Er3+ (or the combination of Er3+ and Yb3+) has been widelyused as a dopant in various types of glasses, such as tellurite [227–229], fluorotellurite [230],
oxyfluoride [231,232], fluoroindate [233,234], chalcogenide [235] and fluorophosphate [236]glasses, serving as the basis of various fluorescence-based temperature sensors. A detailed
review of various upconversion-based temperature sensor schemes has been produced by Zhao
et al. in recently published review paper [237]. Since the doping of RE3+ ions in glass isgenerally performed in the molten phase, a high temperature environment for the synthesis isneeded (with temperatures usually rising to more than 900 K). Furthermore, the experimental
arrangements needed for the operation of several of the sensors reported are relatively complex(requiring lenses, collimators, a bulky spectrometer etc.) and thus are expensive and susceptible
to environmental effects [227,230,232,235,236], making them less well suited to be usedoutside the laboratory. To avoid the problems that are experienced when a high temperatureenvironment is used during synthesis, in this work an UCNPs-polydimethylsiloxane (PDMS)
composite has been explored as the basis of the sensor system itself – one that is created atmuch lower temperatures (583 K) than glasses.
The characterization of these potential sensor materials (prior to their incorporation in thesensor probe itself) is done using where a sample of this UCNPs-PDMS composite was dip
coated on a multimode, larger diameter, optical fibre (chosen to allow the maximum excitation
light to be delivered to the sensor head and light collected from it), with an inexpensive portable

51

Chapter 3
USB-based spectrometer being used to record fluorescence. The use of optical fibre also
provides the advantage of high signal-to-noise ratio, potentially long distances being possible
between the point where the sensing is occurring (particularly valuable in applications such as
mining) and offering reliability of performance in corrosive & harsh environments [238].
Since, it was not possible to dope RE3+ ions directly into the PDMS, a hexagonal-phased UCNP(NaYF4: (18%) Yb3+; (2%) Er3+) composite was used as the basis of the sensor material. Thisapproach was preferred over the use of other UC nanoparticle materials because of their highUC efficiency [239]. Similarly, PDMS was chosen over other polymers because of its goodchemical stability, resistance to water, low cost and good optical properties in the visible-near
infra-red (NIR) region (such as high transparency and low autofluorescence [240]). Moreover,
PDMS shows good adhesion to glass, which further simplifies the coating process onto opticalfibres and thus increases the durability of the sensor created.
In this work, UCNPs have been chemically synthesized using a solvothermal method and its
fluorescence emission has been explored and recorded, in three different media i.e. in a nonpolar solvent (cyclohexane), in powder and in PDMS. Following that, the UC powder itself
and the UCNPs-PDMS composite materials created have been coated onto multi-mode opticalfibre, to form the basis of the temperature sensors designed, ready for evaluation. The opticalfibre thermometer schemes thus developed has been characterized and a ‘figure of merit’ forthe sensors obtained. This has been designed to make a cross-comparison of key parameters
more easy: the figure of merit has been determined from the data captured on the temperaturerelated change in the ratios of the integrated emission intensities of the two green emission
bands, from the Er3+ ions.

3.2 Experimental section
3.2.1 Chemicals and reagents
For the chemical synthesis of the UCNPs, the following chemicals were used: Yttrium(III)chloride hexahydrate (YCl3∙6H2O; 99.99%; Acros Organics), Ytterbium(III) chloride
hexahydrate (YbCl3∙6H2O; 99.90%; Acros Organics), Erbium(III) chloride hexahydrate(ErCl3∙6H2O; 99.90%; Sigma Aldrich), Ammonium fluoride (NH4F; ≥98.0%; Acros Organics),
Sodium Hydroxide (NaOH, 97+%; Sigma Aldrich), Methanol (CH3OH; Analytical Grade,
Fisher Scientific), Ethanol (C2H5OH; HPLC grade; Fisher Scientific), Oleic acid (C18H34O2;
90%; Sigma Aldrich), 1-Octadecene (C18H36; 90%; Sigma Aldrich), Cyclohexane (C6H12; >52

Chapter 3
95%; Acros Organics), and silver conductive paint (Electrolube). PDMS (SYLGARD 184) was
purchased from Dowsil. All chemicals were used as received without any further purification.
3.2.2 Thermometer materials characterization – instrumentation used
The TEM imaging was done using a Model JEM-1010, operating at an accelerating voltage of
80kV. The hydrodynamic diameter of the UCNP was calculated using a Zetasizer Nano ZEN
3600 (Malvern Instruments). The attenuated total reflection Fourier-Transform InfraRed(ATR-FTIR) spectra were obtained using a Perkin Elmer Frontier Spectrometer.
3.2.3 Synthesis of UCNPs & UCNPs-PDMS composites
The hexagonal phase UCNPs used in this work were chemically synthesized using asolvothermal process, by slightly modifying the procedure described elsewhere [146]. Insummary, 0.8 mmol of YCl3∙6H2O, 0.18 mmol of YbCl3∙6H2O and 0.02 mmol of ErCl3∙6H2O,
15 ml of 1-octadecane (acting as solvent) and 6 ml of oleic acid (acting as surfactant)were added to a 50 ml three-necked round-bottom glass flask. As shown in Fig. (3.1), the firstneck of three necked flask was used for pouring chemicals into the flask whereas second neckand third neck was connected to Schlenk line (for contolling Argon flow) and vacuum pump
respectively. Heating was applied to the above mixture, taking it to a temperature of 433 K for
30 mins in an inert (argon) environment to dissolve the lanthanide salts while stirring at 350
rpm (throughout the synthesis process the solution was kept stirred at this speed). After coolingthe solution to room temperature i.e. ~297 K, 2.5 mmol of NaOH and 3.9 mmol of NH4F
dissolved in 3 ml and 10 ml methanol solution respectively were added dropwise, using a 20
ml syringe. This is a crucial step because NaOH and NH 4F rapidly react to form a
NaF precipitate which tends to stick to the walls of the beaker and the amount of NaF added tothe solution determines the size and shape uniformity of the UCNPs thus created [241].
Therefore, to avoid the NaF sticking to the walls of the beaker, instead of mixing the NaOH
and NH4F methanol-based solutions in a beaker and then transferring the NaF precipitate to thesyringe, these methanol-based solutions were mixed directly in the syringe itself forconvenience. Afterwards, the resultant solution was kept stirred at 323 K for 30
minutes to complete the NaF nucleation process. In the next step, the methanol was completely
removed from the solution by gradually heating it to 383 K (alternating between argon flow
and vacuum pressure during the ramping process) and once the temperature reached 383 K, it
was maintained there for 10 minutes under vacuum conditions. Thereafter, the solution wasquickly ramped up to 583 K (at a rate of 10 K/min) and kept at that temperature for one hour53Chapter 3
under argon protection, before cooling down naturally. Once the solution was cooled down, it
was transferred to a 50 ml centrifuge tube, mixed thoroughly with 5 ml of ethanol and theresultant solution was centrifuged at 3500g for 3 minutes. After discarding the supernatant, thewhite-colored precipitant was re-dispersed into cyclohexane and again precipitated by adding
8 ml of ethanol, following which centrifugation (3500g for 3 minutes) was carried out. The
previous step was repeated once more by replacing 8 ml of ethanol by 4 ml of ethanol and 4
ml of methanol. Finally, the precipitant was re-dispersed in 4 ml of fresh cyclohexane to obtain
Argon(In/Out)
Chemicals (In)
Vacuum pump(Out)

Hot PlateFigure 3. 1: Three necked glass flask used for synthesis of UCNPs. Inset shows photograph of UCNPs

dispersed in cyclohexane (illustrating the clarity of the solution).

a stable, transparent UCNPs colloidal solution (concentration: 0.05 mg/μl), as shown in theinset of Fig. (3.1).
UCNPs-PDMS composite was obtained by using a technique involving modification of thesteps used by Wang et al. [108]. As a first step, UCNPs’ colloidal solution, PDMS base solution
and the curing agent were placed (in a ratio 10:10:1 (by volume)) in a glass beaker and mixed
thoroughly. The bubble trapped in the resultant solution, while mixing, was removed bydegassing it in a vacuum chamber for half an hour. Afterwards, the solution was left overnight,
at room temperate and pressure. The following morning, the partially cured solution was heatedto 354 K (below the cyclohexane flash point) for an hour to ensure the complete removal of
the cyclohexane, while at the same time completing the curing process.

54

Chapter 3
3.2.4 Optical fibre thermometer design
A 5 cm long polymer clad silica multimode Optical Fibre (OF), having 1000 μm core diameter(FT1000UMT; Thorlabs) was used as the basis of the temperature probe itself. An OF with a1000 μm core diameter was chosen because this larger diameter (than used for typical‘communications-grade’ fibre) not only provides a much large surface area for coating,excitation and recollection of the UC fluorescence but also offers good mechanical strength tothe probe. To increase the light coupling efficiency, both end facets were sequentially polishedflat using 5 μm, 3 μm and 1 μm grit polishing sheet (LFG series, Thorlabs). Finally, 1 cm ofpolymer jacket was removed from one end of the fibre, which was glued to a SMA connector(11050A; Thorlabs) while from another end 1.5 cm of polymer jacket and 5 mm of cladding
were removed. The bare facet was used for coating with the UC powder and UCNPs-PDMS
composite to create the probes.
For the UC powder coating, first UCNPs were precipitated from a 500 μl of colloidal solution
by adding 500 μl of ethanol followed by centrifugation (3500 g, 3 mins). After discarding thesupernatant, the bare end of the OF was inserted into the precipitate to attach some UC powder
to the fibre tip. Finally, the UC powder-coated OF was dried overnight and heated at 354 K foran hour (the following morning) to remove any residual traces of cyclohexane.
To coat the UCNPs-PDMS composite, the 3 mm of optical fibre was dipped in the UCNPsPDMS composite solution, obtained by mixing UCNPs and PDMS and removing the trappedbubbles that were seen and which would deteriorate the optical quality of the probe material(as described above). It was then left for one minute and slowly taken out using a lab-jack. As
in the case of the UC powder, the UCNPs-PDMS was left overnight at room temperature andpressure and the next morning heated to 354 K for an hour. Another 5 mm layer of PDMS wascoated on the fibre, following the same procedure but with the exception of replacing the
UCNPs-PDMS solution by PDMS. This PDMS coating passivates the Er3+ ions present on thesurface of UCNPs-PDMS, thus nullifying the impact of the surrounding environment on the
UC fluorescence. Since the OF probe was designed to operate in reflection-mode, silver paintwas coated on the tip by dipping it into commercially-obtained silver paint, thus to enhance thereflection of UC fluorescence. The probe created in this way is shown in Fig. 3.2. In that figure,the inset shows the visible (green) UC fluorescence emitted by the UCNPs-PDMS-coated tip,upon excitation using light from a 500 mW, 980 nm wavelength (λ) laser source. Before

55

Chapter 3
evaluating the temperature sensing performance of the probe, it was annealed at 503 K for 3
hours to stabilize it.

Figure 3. 2: Optical fibre temperature probe constructed after coating silver paint on the UCNP-PDMS tip.
Inset shows green UC fluorescence emitted by UCNPs-PDMS composite coated tip (before the silver coating
was applied) upon excitation with light from a 500 mW, 980 nm laser source.

3.2.5 Optical thermometer characterization setup
In all the experiments carried out to investigate the fluorescence-based performance of thesensor probe, light from a continuous-wave 980 nm diode laser (JDSU 2900 series) with a fibre
pigtail and a maximum achievable power (of 500 mW) was used for excitation. The UC
fluorescence emitted was acquired using a portable spectrometer (Maya-type 2000PRO; Ocean
Optics). The UC spectrum of the colloidal solution was recorded using the setup created andshown in Fig. 3.3. As it can be seen in the figure, the laser source and the spectrometer wereconnected to 1 cm cuvette holder (CUV-ALL-UV; Ocean Optics), set at 90o to each other tominimize the amount of scattered source light reaching the spectrometer.

From
SourceUCNPTo Detector

Figure 3. 3: Characterization setup for measuring fluorescence of UCNPs in colloidal solution. During
measurement, external light was turned off.

56

Chapter 3
The UC powder and the UCNPs-PDMS were coated onto the OF, following the steps describedin the preceding subsection and characterized using the setup schematically shown in Fig. 3.4.
As can be seen from the Fig. 3.4, the laser source and the spectrometer were connected to thetwo ends of 2x1 fibre bundle ( = 230 µm; Ocean Optics), while the third was connected to thecoated OF probe through an SMA connector (SMA905, L-com). A 2 mm thick NIR rejection
filter ( = 11.9 mm; BP550; MidOpt) was placed in the path of the spectrometer to avoid its
saturation from the reflected source light. The actual photograph of the equipment, highlighting
the portability of setup is shown in Fig 3.5. The NIR filter was mounted on a 1 cm cuvetteholder (CUV-UV; Ocean Optics; shown in the exploded view of Fig 3.5) as it provides a naturalalignment between the incoming and the outgoing fiber, thus making the setup both simple andreadily portable when required. The UC spectrum was recorded over the wavelength range
from 400 nm to 700 nm (at a resolution of 1 nm), with an integration time of 1 second, using
the Spectra Suit software package (Ocean Optics).
2x1
Coupler

Laser Source(980 nm )Mini
Spectrometer

Thermocouple

NIR reject
FilterFibre Probe
LaptopSand BathHeaterFigure 3. 4: Schematic of the setup used for thermal characterization of the probes.

In the experiments which were set up to investigate the temperature performance of the probe,a heater (RCT Basic; IKA) equipped with a thermocouple (ETS-DS; IKA; minimum resolution= 0.1 K) was used to regulate and control the temperate of a sand bath (SiO2; 50-70 meshparticle size; Sigma Aldrich) or air bath, to provide a stable temperature zone for thecalibration. The sand bath, due to its excellent thermal properties, was used to decrease theramping-up time, minimize the temperature fluctuations and achieve a uniform temperature
distribution, which facilitated the calibration of the probe. For each temperature, the meanvalue of six replicated readings, taken at intervals of 1 minute, was recorded.

57

Chapter 3
Thermocouple
2x1
coupler

Spectrometer

SourceExploded View

Sand
Bath

Out Fibre

In
InFibreFibre

NIR reject Filter

FilterHeaterLaptopFigure 3. 5: Photograph of the equipment used in the thermal characterization of probes (left). The exploded view ofthe filter (right).

58

Chapter 3

3.3 Results and discussion
3.3.1 Characterization of the thermometer materials
A TEM image of the synthesized UCNPs used is shown in the Fig. 3.6(a). It can be seen fromthe figure that the synthesized UCNPs are of uniform size and have a clear hexagonal shape,
as desired. The mean hydrodynamic diameter of the UCNPs was found to be ~56 nm from the
DLS measurement made. The inset of Fig. 3.6(a) shows the green visible UC fluorescenceemitted by the synthesized colloidal solutions on excitation with light from a 500 mW, 980 nm
diode laser. Figure 3.6(b) shows photographs of the PDMS (marked as 1) and the UCNPsPDMS composite (marked as 2) and the UCNPs-PDMS when excited with light from a 980
nm diode laser (marked as 3). It can be seen from the same figure that the UCNPs-PDMS
composite is less transparent than the pristine PDMS. This loss of transparency on adding the
UCNPs to the PDMS results from the agglomeration of the UCNPs to form strong scattering
centers, as observed and reported in the literature for other inorganic-organic nanocomposites[242,243]. The loss of transparency does not have significant impact on its usage as atemperature sensing material.
(a)

(b)

1

2

1

PDMS
(white light)

2

UCNP-PDMS(white light)

3

UCNP-PDMS(980 nm light)

3

Figure 3. 6: (a) TEM image of synthesized hexagonal phased-UCNPs. Inset shows the green UC fluorescencefrom the UCNPs colloidal solution when excited using light from the 980 nm laser source. (b) Photographs of
the PDMS (marked as 1) and the UCNPs-PDMS composite.

Figure 3.7(a) shows the UC emission spectra recorded using the spectrometer mentioned, for
UCNPs in three different media: in cyclohexane, as powder and in PDMS. It can be seen thatin all the three media the UC fluorescence shows three distinctive peaks (marked as 1, 2 and 3
on the figure) and these comprise two ‘green’ bands (peak = 525 nm & 545 nm) and one ‘red’
band (peak = 650 nm). The electronic transitions responsible for these peaks are shown inrelation to the energy level diagram given in Fig. 3.7(b). As previously described in the59Chapter 3
literature [13,78,112], the energy level 4I11/2 is populated through several routes but the energy
transfer (ET) from Yb3+ (2F5/2 (Yb3+) + 4I15/2 (Er3+) → 2F7/2 (Yb3+) + 4I11/2 (Er3+)) and throughground state absorption (GSA; 4I15/2 (Er3+) + photon → 4I11/2 (Er3+)) are dominant. Further,
contrasting the ET and the GSA mentioned above, the probability of the occurrence of ET isgreater than GSA, due to the higher absorption coefficient of the Yb3+ ions (when compared tothat for Er3+ ions) at the input wavelength used [13,229]. For the green band emission, electrons
excited from 4I11/2 to 4F7/2 through ET (2F5/2 (Yb3+) + 4I11/2 (Er3+) → 2F7/2 (Yb3+) + 4F7/2 (Er3+))
or excited state absorption (ESA; 4I11/2 (Er3+) + photon → 4F7/2 (Er3+)), quickly settle into morestable states 2H11/2, 4S3/2, through non-radiative phononic relaxation. The emission bands
around 523 nm and 545 nm arise due to the radiative transition of electrons from 2H11/2 → 4I15/2
and 4S3/2 → 4I15/2 respectively. For the red band transition (4F9/2 → 4I15/2), the energy level 4F9/2
is populated via two major routes. The first of these is through the de-excitation of electrons
from 4I11/2 to 4I13/2 through phononic relaxation and then excitation from 4I13/2 to 4F9/2 throughET (2F5/2 (Yb3+) + 4I13/2 (Er3+) → 2F7/2 (Yb3+) + 4F9/2 (Er3+)) or ESA (4I13/2 (Er3+) + photon →4

F9/2 (Er3+)). In the second route, 4F9/2 becomes populated through non-radiative relaxation from

4

S3/2.
(a)

(b)

4F

In Cyclohexane

2H
11/2
4S
3/2

R/G = 0.34

TCL

2
4F

UC Powder
2
1

EnergyIntensity (a.u.)

7/2

3

R/G = 0.74

1980 nm

9/2

3
4I
9/2
4I

2F
5/2

11/2

UCNP-PDMS
4I
13/2

R/G = 1.04

500

550

600

650

700

Wavelength (nm)

Yb3+

2F

7/2

Er3+

4I
15/2

Figure 3. 7: (a) UC emission spectra when UCNPs are dispersed in cyclohexane, UC powder & UCNPs-PDMS.
R/G represents the integrated intensities of the red and green bands, shown by red and green colored areas in
the lower spectrum shown (b) Partial energy level diagram of Yb 3+/Er3+ showing the important radiative andnon-radiative transitions involved in the UC mechanism. The dash-dotted, dashed, wavy and straight (solid)lines represent the NIR photon excitation, energy transfer, non-radiative relaxation and radiative emission
processes respectively.

60

Chapter 3

Figure 3. 8: (a) ATR-FTIR response of UC powder and UCNPs-PDMS composite (b) Green UC emission bands of
Er3+ ions. IH is the area under curve from 514 nm to 532.3 nm corresponding to the radiative transition 2H11/2 →I15/2 and IS is the area under curve from 532.8 nm to 562 nm corresponding to the radiative transition 4S3/2 → 4I15/2

4(c) Variation of Intensity ratio (IH/IS) with time due to laser source heating. The right axis shows the variation oftemperature with respect to the mean value.

As discussed in the previous paragraph and is evident from the energy level diagram shown in
Fig. 3.7(b), the intensities of the red and green emissions are related through the non-radiativetransitions between 4I11/2→4I13/2 and 4S3/2→4F9/2, which in turn are strongly affected by thesurface properties of the particles, such as surface defects, proximate impurities, surface states,
attached ligands, etc. [244]. Therefore, it can be seen from Fig. 3.7(a) that the Red to Greenratio (R/G) is different for all three media. The increase in the R/G ratio in the powder form, incomparison to the colloidal solution UCNPs, has been observed previously and has been
attributed to an increase in the cross-relaxation energy transfer between the Er3+- Er3+ surface
ions, due to the clustering of the Er3+ ions in the powder [245]. In the case of the UCNPsPDMS composite, the observed R/G was highest among the three media considered. This could

61

Chapter 3
be due to the combined effect of cross-relaxation between the Er3+ - Er3+ ions at agglomerated
sites and an increase in the non-radiative relaxation between the 4S3/2 and 4F9/2 levels, causedby the presence of the CH3 lateral chain of the PDMS near the surface. As can be seen fromthe ATR-FTIR of the UCNPs-PDMS composite, shown in Fig. 3.8(a), the vibrational energyof the C-H stretching (2962 cm-1) is closer to the energy gap of 4S3/2→4F9/2 (3200 cm-1), thusincreasing the probability of multiphoton relaxation on the transition 4S3/2 → 4F9/2.
3.3.2 Temperature response of UC powder-based thermometer
As mentioned above, the ratio of the integrated emission intensities of the green bands underquasi-thermal equilibrium follows Boltzmann’s distribution, in accordance with Eq. (3.1).
𝐼

𝑔𝐻 𝜔𝐻 𝐴𝐻𝐼𝑆𝑔𝑆 𝜔𝑆 𝐴𝑆

𝑅= 𝐻=

(

−𝛥𝐸

)

(

−𝛥𝐸

)

𝑒 𝑘𝐵𝑇 = 𝐵𝑒 𝑘𝐵𝑇 ,(3.1)

where IH is the area under the emission intensity curve between wavelength the 514 nm and532.3 nm, as shown by the purple area in Fig. 3.8(b) and IS represents the area under theemission intensity curve over the wavelength range 532.8 nm to 562 nm (shown by yellow areain Fig. 3.8(b)) 𝑔, ω, and A are the degeneracy of the given energy level, the angular frequencyof the radiative transitions from the same energy level to the ground level and the emission
cross-section respectively, ΔE is the energy gap between the 2H11/2 and 4S3/2 levels, kB is
Boltzmann’s constant and T is the temperature. The pre-exponential constant B is given by(𝑔𝐻 ω𝐻 𝐴𝐻 ⁄𝑔𝑆 ω𝑆 𝐴𝑆 ). The area under the curve was calculated using Simpson’s rule and ΔE
was obtained by calculating the difference between the barycenter of I H and IS and thecorresponding standard error, δE, is the error in that difference across temperature. The
barycenter of the corresponding emission was calculated using Eq. (3.2) and the value obtainedof ΔE = 718.14 ± 6.46 cm-1 is in good agreement with the previously reported values [232,246].
−1∑𝜆𝜆21 𝜆𝐼(𝜆)7𝐸 = 10 ∗ ( 𝜆)∑𝜆2 𝐼(𝜆)1(3.2)

Before calibrating the response of the sensor to the external change in temperature, any selfheating due to the laser source that may be present was monitored, over a period of 2.5 hours.
Fig. 3.8(c) shows the fluctuation of the intensity ratio (IR) over that period (left axis) and thecorresponding temperature fluctuation on the right axis (the mean value of the fluctuation of
the IR is considered as a reference). It can be seen from the figure that the temperature variation
is within the temperature resolution of the sensor (± 2.7 K: calculation shown later). Moreover,the IR of the sensor remained the same even on reducing the laser source power by half, i.e.

62Chapter 3
250 mW. These results prove that it is a reasonable assumption that any heating due to the laser
source is unimportant.
The variation in the intensity of the green fluorescence of the UC powder, recorded with anincrease in temperature from 298 K to 398 K, is shown in Fig. 3.9(a). It can be seen from themain figure and the inset that IH increases and IS decreases with the increase in temperature.
The ratio of IH and IS as function of temperature, as shown in Fig. 3.9(b), fits excellently (R2 =0.999) with the function shown in Eq. (3.1), thus indicating that the increase in I H and thecorresponding decrease in IS are due to the thermal transfer of electrons from energy level 4S3/2
to 2H11/2. The value of ΔE = 777.15 cm-1, obtained from the fitting, is in good agreement withthe value obtained from a barycenter calculation (718.14 ± 6.46 cm-1). The value obtained forthe pre-exponential factor B also matches well with previously reported values in literature[227,247,248]. Since, the Eq. (3.1) does not take into account the temperature-dependent nonradiative transition rates from 4S3/2 and 2H11/2, the close fitting of the experimental data to Eq.
(3.1) shows that the phonon-assisted non-radiative recombination rate is insignificant over the
given temperature range, for the UC powder. Moreover, the intensity ratio variation, withtemperature can also be approximated to a linear function over the given temperature range,
with R2 = 0.996, as shown in Fig. 3.10(a).

Figure 3. 9: UC powder: (a) Variation of green fluorescence with temperature. The figure has been normalized tothe maximum value (obtained at 297 K). The inset shows variation of IH and IS with temperature. (b)Experimentally obtained ratio of IH and IS against temperature, juxtaposed with an exponential fitting using Eq.
(3.1).

The absolute thermal sensitivity (SA) and the relative thermal sensitivity (S R) of thethermometer are given by Eq. (3.3) and Eq. (3.4) respectively. It can be seen from Fig. 3.10(b)that SA increases with temperature and the maximum value obtained for S A was (4.91 ± 0.02)

63Chapter 3
×10-3 K-1 at 394.9 ± 0.5 K, whereas SR monotonically decreases from (12.53 ± 0.03)×10-3 K-1
to (7.15 ± 0.02)×10-3 K-1 with the increase in temperature from 298.2 ± 0.1 K to 394.9 ± 0.5 K.
The minimum resolution of the temperature (𝛿𝑇) that could be determined using Eq. (3.5) andEq. (3.6), was ± 2.7 K. In Eq. (3.6), δIH and δIS are the standard errors (standard deviation
divided with the square root of the number of repeated measurements made, i.e. 6 in the presentcase) in IH and IS respectively.
𝑆𝐴 =

𝑑𝑅
∆𝐸
= 𝑅(
)
𝑑𝑇
𝑘𝐵 𝑇 2

(3.3)

𝑆𝑅 =

1 𝑑𝑅
∆𝐸
=(
)
𝑅 𝑑𝑇
𝑘𝐵 𝑇 2

(3.4)

𝛿𝑅
𝑆

, 𝑤ℎ𝑒𝑟𝑒

(3.5)

𝛿𝐼𝐻 2
𝛿𝐼𝑆 2
) +( )
𝐼𝐻
𝐼𝑆

(3.6)

𝛿𝑇 =

𝛿𝑅 = 𝑅√(

Since the adhesion of the UC powder to the optical fibre was not strong in comparison to

Figure 3. 10: (a) Linear fitting of the ratio obtained of IH and IS over the temperature range from 298 K to 395 K (b)Absolute (left) and relative (right) thermal sensitivities obtained for the UC powder.

UCNPs-PDMS composite, the probe lifetime reduces considerably as the coating is lost fromthe fibre, with time, in normal use.
3.3.3 Temperature response of UCNPs-PDMS composite based thermometer
The variation in the green fluorescence bands of the UCNPs-PDMS composite-coated probe isshown in Fig. 3.11(a). It can be seen from the main figure and the inset (showing the integrated
intensity) that that rate of decrease of I S with temperature is more than for the UC Powder,whereas in contrast to IS, the rate of increase in IH is smaller. Furthermore, the variation of the64Chapter 3
ratio of IH/IS with temperature, as shown in Fig. 3.11(b), shows an excellent linear fit (R 2 =0.99), but unlike the UC powder, this does not fit as well (R2 = 0.89) with Eq. (3.1), as shownin Fig. 3.12(a). In the above fitting, ΔE = 727.65 cm-1 (calculated from Eq. (3.2)) was used.
The low R-squared value illustrates that thermal transfer of electrons from 4S3/2 → 2H11/2 is notstrictly governed by the Boltzmann distribution. The deviation of the thermal response of the
UCNPs-PDMS composite from the Boltzmann distribution can be attributed to the increase in
the temperature-dependent non-radiative transitions [249] due to presence of the PDMS
chemical bonds, as revealed from the ATR-FTIR spectrum (ref. Fig. 3.8(a)), in the vicinity ofthe surface of Er3+ ions.

Figure 3. 11: UCNPs-PDMS composite coated probe: (a) Variation in green fluorescence bands withtemperature. The inset shows integrated emission intensities (b) Linear fitting of the experimentally obtained
ratio of (IH/IS), as function of temperature.

The performance of the sensor created using this material shows a linear temperature response
and the same sensitivity of (2.90 ± 0.40) × 10-3 K-1 across its working temperature range, a
positive feature not usually shown by earlier Er 3+, Er3+/Yb3+ doped glass-based temperature
sensors. The reduction in the thermal sensitivity of the UCNPs-PDMS composite (with respect
to the UC powder (4.91± 0.02) × 10-3 K-1 ) is again due to the reduction in the energy transfer
efficiency, owing to the high non-radiative losses. The same pattern was observed in the caseof glass-based temperature sensors where glasses having high phonon energies (such silicate
and oxide-based glasses) show a lower sensitivity in comparison to glasses having a low
phonon energy, such as tellurite glass [229]. The cyclical response of the sensor and thesmoothened curve obtained by calculating the mean from 20 neighbouring points is shown byboth solid and dotted lines respectively, by varying the temperature from 296 K to 359 K (and65

Chapter 3

Figure 3. 12: (a) Exponential fitting of the experimentally obtained ratio of (IH/IS) as function of temperature, using
Eq. (3.1) (b) Cyclic response obtained through repeatedly varying the temperature from 296 K to 359 K (and back).
The smoothened curve (dotted) was obtained by calculating local mean from 20 neighboring points is shown as
guidance for the eyes.

back) is shown in Fig. 3.12(b). The figure shows that sensor exhibits repeatable reading when
exposed to periodically varying temperature. The response time of the sensor, (defined as thetime seen on the rising curve between a 10% and 90% peak level i.e. (t90-t10)) was found to be~ 5 seconds, as shown on Fig. 3.13(a). The temperature resolution ± 2.7 K, calculated using
Eq. (3.5) & Eq. (3.6), was the same as that for the UC powder. Also, although the silver coatingon the tip of sensor is not essential, it increases the overall UC green fluorescence intensity by~ 23%, as shown in Fig. 3.13(b) and corresponding area under the curve is given in Table 3.1.
Table 3. 1: Silver coating of the tip. Given data is for Fig. 3.13(b).

Area under blue curve (arbitrary units)

13.5

Area under red curve (arbitrary units, as above)

11.0% increase in intensity

22

The UCNPs-PDMS composite probe shows a repeatable temperature response, measured overa period of several months, benefitting from the good adhesion between the PDMS and theoptical fibre (OF) used.
3.3.4 Comparison of performance with previously reported sensors
In order to compare the performance of the probes developed and, in this work considered,their thermal responses were compared to those of a number of others using publishedinformation from the literature, collating published data on Er3+ or Er3+/Yb3+ doped glass-based66

Chapter 3(b)Intensity Ratio (IH/IS)

0.55
0.5
0.45
Responsetime= t90-t10

0.4
0.35
0.3

t10

50

t90

100

150

Normalized Intensity

(a)

after
before

1
0.8
0.6
0.4
0.2
0
500

520

540

560

580

Wavelength (nm)Time (second)

Figure 3. 13: (a) Ramp-up response of the sensor (b) Normalized green fluorescence before and after coating ofcommercial silver paint.

temperature sensor devices. The minimum sensitivity value of the sensors reported has been
extracted from the sensitivity curve of the work of Rohatgi et al [250], using the webplot
digitizer tool. As can be seen from Table 3.2, the UCNPs-PDMS-based temperature sensor
developed shows a maximum sensitivity of 2.9×10-3 K-1 within the temperature range of 295473. The sensitivity and temperature range (which is determined by substrate/host matrix used)of UCNP-PDMS based sensor is not much better than previously reported glass-based sensors,
however, the real strength of this sensor lies in:
1) Low temperature fabrication. As depicted in Table 3.2 (column 2), UCNPs-PDMS
needs around 400 K less temperature for fabrication in comparison to glass based
sensors. This enables one to realise the sensor simply using hot plate rather than hightemperature furnace. Furthermore, PDMS can be easily dip coated on the fibre. These
two characteristics reduces the fabrication complexities, thus saving time, effort andoverall cost needed to realise the sensor.
2) Linear Response. Unlike most of the sensors previously reported, the maximum
sensitivity of this device remains constant across the full operating temperature range,emphasizing the value for applications where such a strongly linear response isdesirable. As discussed earlier, this linear response is attributed to increase in nonradiative losses due to presence of the vibrational energy of the C-H stretching (2962
cm-1) closer to the energy gap of 4S3/2→4F9/2 (3200 cm-1), thus highlighting theimportance of using PDMS.
3) Longevity: The use of PDMS increases the longevity of the sensor in comparison to one
based on UNCPs powder because of better adhesion of PDMS to the optical fibre and67

Chapter 3
allowing better heat distribution thus preventing the burning of nanoparticles andincreasing the operational temperature range.
Table 3. 2: Comparison of key parameters of the performance of probes developed in this work with those from
Er3+/Yb3+ doped glass temperature sensors, reported in the literature.

Doped material as

Maximum

Smax (Temp) Smin (Temp)

the basis of thesynthesis10-3 K-1 (K)sensortemperaturetemperatureneeded (K)Range (K)

UCNPs-PDMS

SensorResponse

10-3 K-1 (K) Operational583

2.9 (295)

2.9 (295)

295-473583

4.9 (395)

3.5 (295)

295-395

Literature
ReferenceLinearThis work

composite
UC Powder

Exponential/ This work
LinearEr3+/Yb3+: tellurite973

8.9 (473)

2.1 (278)

278-473

glass
Er3+/Yb3+: TeO2–

Piecewise[229]

Linear1023

2.8 (690)

2.1 (300)

300–690

Exponential

[227]

1073

5.4 (568)

3.6 (298)

298-568

Exponential

[251]

1173

3.6 (493)

2.1 (293)

293-493

Linear

[228]

1373

3.1 (423)

1.8 (83)

83-423

Exponential

[252]

1373

2.6 (592)

0.5 (298)

298–650

Exponential

[247]

1473

2.7 (450)

1.8 (250)

250–450

Exponential

[232]

1723

3.3 (296)

1.8 (723)

296–723

Exponential

[253]

1823

14 (300)

5.4 (480)

300–480

Exponential[254]

WO3 glassEr3+/Yb3+:
fluorotellurite
glassesEr3+/Yb3+:
germinate tellurite
glass
Er3+: Bi3Ti1.5W0.5O9
ceramic
Er3+: PbO-Ga2O3SiO2 glass
Er3+: oxyfluoride
glass
Er3+/Yb3+: silicate
glass
Er3+: KYb2F7
nanocrystal influoride glass
ceramics

68Chapter 3
Er3+/Yb3+: K3LuF6

1823

14 (300)

2.1 (773)

300-773

Exponential

[255]

1823

6.1 (500)

3.8(300)

300-500

Exponential

[256]

1863

3.7 (563)

2.3 (303)

303-563

Exponential[257]

nanocrystal inoxyflouride glass
ceramic
Er3+: Sr2YbF7glass
ceramics
Er3+/Yb3+: βNaGdF4nanocrystals glass
ceramic

3.4 Summary
In the work carried out using ratiometric green emission of an upconverting nanoparticlepolydimethylsiloxane composite, simple, yet practical designs for optical fibre-based
thermometers using both UC powder and UCNPs-PDMS composite have been developed andtheir performance reported. The sensor materials have been synthesized and coated on amultimode optical fibre, to create useable sensor platforms – then and the best of these wasselected and explored further. Even though the UC powder showed a higher thermal sensitivity
than the UCNPs-PDMS composite (SUC powder = (4.91 ± 0.02)×10-3 K-1; SUCNP-PDMS = (2.90 ±0.40)×10-3 K-1), the latter is preferable for many applications over the former due to the stablecoating arising from the good adhesion between the PDMS and the optical fibre. The optimum
UCNPs-PDMS coated thermometer thus created shows an excellent linear temperature
response over the important range 298 K to 493 K, with a same order of sensitivity as had
previously been reported for several Er3+/Yb3+ doped glass-based sensors, but achieved more
simply through a room temperature coating technique. The work has emphasized theadvantages of the low temperature synthesis process: the ease of the coating technique, thesimple and portable characterization setup used and the creation and optimization of aphysically robust probe, all demonstrating the value of this low temperature approach to createa practical and inexpensive sensor system, which can be undertaken in a typical chemical
synthesis laboratory.

69

Chapter 4

Chapter 4
Optical fibre-based heavy metal detection
using the gold nanoparticles
4.1 Introduction
Contamination of water by heavy metal ions (especially mercury, cadmium, and lead) cancause serious environmental problems and human and animal health problems because of theiracute, chronic toxicity to biological organisms [258]. Therefore, sensors to detect heavy metal
ions in an aqueous solution are particularly needed to protect the environment. In this regard,
spectroscopic-based techniques such as atomic absorption spectroscopy and inductively
coupled plasma spectroscopy are amongst the most commonly used methods [259,260].
However, the well-known drawbacks of spectroscopic techniques, such as portability of theequipment (and thus use outside the laboratory), the initial cost of a sensitive spectrometer andonerous sample preparation methods have seen the emergence of new techniques based on
nanotechnology. A number of nanoparticle-based heavy metal techniques have been reported
in the last two decades and among the varieties of nanoparticles available, GNPs offer uniqueadvantages in terms of a high Refractive Index (RI)-sensitive LSPR peak, coupled to resistanceto oxidation, ease of fabrication and well-understood surface chemistry [261,262]. Mishra etal. have, for example, incorporated poly-(n-vinyl-2-pyrrolidone) ((C6H9NO)n) as a capping
agent to create a LSPR-based mercury ion sensor [263]. Similarly, Youngjin Kim et al. havedemonstrated a colorimetric sensor using the aggregation of 11-Mercaptoundecanoic acid
(MUA; HS(CH2)10CO2H) functionalized GNPs in presence of heavy metal ions [264].
Coating GNPs on an optical fibre (OF) to create a simple-to-fabricate, yet effective sensor
probe offers several advantages, including ease of remote sensing capabilities, a potentiallyhigh signal-to-noise ratio and resistance to electromagnetic interference. As a result, several
GNPs coated optical fibre LSPR-based metal ion sensor designs have been explored in theliterature [265–271]. For instance, monoclonal antibodies on GNPs coated OFs have beenshown to have an affinity towards the Pb2+- Ethylenedinitrilotetraacetic acid (EDTA;(HO2CCH2)2NCH2CH2N(CH2CO2H)2) complex. Even though the sensor can detect at the parts

70

Chapter 4

per billion (ppb) level, the steps involved to prepare a reliable sensor and implement aneffective detection system are quite complicated and thus usually time consuming for theoperator.
The key novelty of the work in this Chapter comes from targeting ease of manufacture, creating
a simple, portable and robust LSPR-based OF sensor, operating in reflection mode anddesigned to detect the heavy metals especially Pb2+ is reported. The focus in this research is toshow proof of concept by detecting Pb2+ because it is one of the most harmful, yet common
heavy metal found polluting water, often from industrial ‘run-off’, in the developing world.
Thus, recognizing the need of portable sensor to detect heavy metal, in this work, OF coatedwith indigenously synthesised GNPs is developed and its capability for detecting “heavy
metals” is tested by dipping in known concentrations of aqueous solutions of lead nitrate.
However, on finding no change in its response, the developed probe is further coated with
MUA to make it selective towards heavy metals ions. After functionalization of MUA, achange in amplitude as well as the resonance frequency is observed with change inconcentration of the Pb2+ ions, arising from the binding of the Pb2+-COOH (carboxyl) group,
thus being indicative of the concentration of the Pb2+ in the solution.

4.2 Methodology
4.2.1 Chemicals and apparatus used
The following chemicals used were purchased from Sigma-Aldrich: Chloroauric acid
(HAuCl4.3H2O), Sodium citrate tribasic dehydrate (Na3C6H5O7.H2O), 3-aminopropyl
trimethoxysilane (APTMS; H2N(CH2)3Si(OCH3)3), 97%, Lead nitrate (Pb(NO3)2) and MUA.
In addition, Methanol (CH3OH; Analytical Reagent Grade), Hydrogen Peroxide (H 2O2; 37%)
solution and Sulphuric acid (H2SO4; 95% Laboratory Reagent Grade) were purchased from
Fisher Scientific. Silver paint (Electrolube) was purchased from e-bay. The chemicals wereused as received from the manufacturer. The multimode OF used, type FT1000UMT, waspurchased from Thorlabs.
4.2.2 Characterization instruments
The UV-visible spectrum of the synthesized GNPs was obtained using a LAMBDA 35 UV/VIS
spectrometer (Perkin Elmer Inc.), allowing monitoring over the wavelength range from 400
nm to 800 nm (in steps of 1 nm). TEM images were taken at an accelerating voltage of 80 kV
and giving 400k magnification. Energy Dispersive X-Ray Analysis (EDAX) was done using

71

Chapter 4

a device sourced from Oxford Instruments. The DLS measurement was performed using a
ZetaSizer Nano ZEN 3600 (Malvern Instrument).
A tungsten halogen light source, (type LS-1) and a Maya-type 2000PRO were used as thesource and the detector respectively, to allow the response of the coated fibre to be acquired.
Both components were purchased from Ocean Optics.
4.2.3 Synthesis of GNPs
The GNPs were synthesized by reducing the gold ions present in chloroauric acid with the helpof citrate ions, following the steps described in previous work reported in the literature [272].
The approach used 20 mL of 1.0 mM HAuCl4.3H2O which was placed in a 50 ml round bottom
flask and heated until a rolling boil was achieved. While stirring at 900 rpm, 2 mL of the 1%
solution of Na3C6H5O7.H2O, acting as reducing agent was rapidly added. This solution wasthen stirred for a further 10 mins, before removing the external heating. At the end of this step,
the color of the solution was cardinal red, as expected, due to the formation of the GNPs colloid,
as illustrated in Fig. 4.1(a).

(a)

(b)
GNP coated portion

Silver paintFigure 4. 1: (a) Colloidal Solution (b) Image of the GNPs coated fibre, where the coating area is clearly visible.
The white bar at the bottom right represents the reference scale (1 mm).

4.2.4 Sensor preparation process
The synthesized GNPs were then coated on the optical fibre sample discussed, where adiameter of ~1000 µm was used (as this large diameter provides a greater coating surface area),in that way to create the sensor probe used in this work. Before the coating was carried out,
both ends of the fibre were carefully polished, as described in Chapter 3 (ref. section 3.2.4),
and at one end 2 cm of polymer jacket and the cladding was carefully removed. After removalof the cladding, the GNPs were coated on the cleaned fibre, using the steps described inliterature [238]. This process can be summarized as follows: the fibre was washed and72

Chapter 4hydroxylized with Piranha solution, following which it was cleaned several times in running
distilled water and then sonicated in distilled water to ensure complete removal of the last tracesof the piranha solution. After drying the fibre in an oven for 1 hour at 393 K, the unclad fibre
section was functionalized with APTMS solution in methanol (5% v/v) for 4 hours. This step
was followed by washing the functionalized area with methanol and in the end by distilledwater. The fibre was placed in an oven at 373 K, overnight, to dry it completely. The next day
the functionalized part of the fibre was dipped in synthesized GNPs solution for 6 hours tocreate a stable and uniform coating, which was visible from the naked eyes, as illustrated inFig. 4.1(b).
The GNPs immobilized area is made selective to the Pb2+ ions by using MUA as a cross-linker.
MUA has two terminal functional groups, one being the thiol group and another being thecarboxyl group. The thiol group (one of the two terminal functional groups) in the MUA
becomes attached to the GNPs via a strong Au-S covalent bond, whereas its other terminalgroup stays unattached (‘dangling’). This dangling carboxyl group, chemically bound withheavy metals ions, thus makes the fibre selective to the heavy metal ions present in the solution.
The MUA is coated on the fibre following the steps described in the literature [273]. Insummary, the sensor probe was incubated in 0.3 mM aqueous solution of MUA containing anequivalent amount of sodium hydroxide for 1 hour in at 323 K, where a water bath was used tomaintain the constant temperature. After the unbound MUA had been removed in ethanol, thefibre was thoroughly rinsed with distilled water and dried using hot air from a heat gun.
The functionalization of the heavy metal on the MUA-GNPs-coated fibre was performed bydipping the optical fibre in a given heavy metal solution for 1 hour. After this, the fibre wastaken out of the solution and dried using the air from the heat gun. The schematic of the steps
described are shown in Fig. 4.2.

73

Chapter 4

H2N

OH

O

Si

H2N

Si

H 2N

Si

H2N

H2O2:H2SO4

Si

OH

O
O

O

O

Core

Core

Core

O
O
O

OH
Piranha Cleaning

APTES treatment

Au coating

O
HN

Au

S

C
O

OH

HN

Au

S

C

OH

Core

O
O

Si

C

O

HN

Si

Au

S

C

HS

OH

Si

HN

Au

Si

HN

Au

Si

HN

Au

O

O

O

O
O

HO

Core

Si

O

O
O
O

MUA coating
M2+ (M = Pb, Cd)
O
O

Si

HN

Au

S

C
O

O

Si

HN

Au

S

C

O

Core

O
O

O

O
O

M

Si

HN

Au

S

C

O

Figure 4. 2: Schematic of the processes involved in the sensor preparation.

After the functionalization was completed, the fibre was coated with silver paint at the distal
end to create a sensor to be used in reflection mode, in that way allowing the light to interact
twice over the length of the immobilized area effectively, thus increasing the interaction timewith the attached heavy metal ions.
4.2.5 Characterization setup for solution refractive index and heavy metal detection
A schematic of the experimental setup developed is shown in Fig. 4.3(a). The broadband
tungsten light source used was connected to one end of 1x2 fibre coupler (Ocean Optics, dia.
~ 600 µm). The other two ends of the fibre coupler were connected to the spectrometer and the
GNPs-coated fibre, where due to the presence of the silver coating at the tip of the GNPs-coatedfibre, the spectrometer was able to collect the reflected light. The real time absorbance spectrum
observed over the wavelength range from 400 to 900 nm (and taken with step sizes of 1 nm)
was monitored and recorded on the laptop used. The spectrum of the bare (not GNPs-coated)
1000 µm fibre was used as the basis of creating the background signal.

74

Chapter 4

(a)

A

B

(b)

C
A: Broadband Light Source
B: Spectrometer
C: Computer

Cladding

Source light
Reflected light

Fibre core

50 nm

Figure 4. 3: (a) Schematic of the experimental setup used for the characterization of the GNPs coated fibre. (b)TEM image of GNPs.

4.2.6 Modelling technique
The Mie scattering matrix elements, assuming uniform spherical GNPs, were calculated for the
wavelength varying from 400 nm to 800 nm at step size of 1 nm using home-made code written
in MATLAB. The code was developed and benchmarked following the techniques and results
given by Bohren & Huffman in Appendix A [274]. In this work, the refractive index (RI) of
gold used was calculated by interpolating the data given by Johnson & Cristy [275]. The RI of
medium surrounding the GNPs was taken as 1.33 (i.e. of distil water). The developed code isgiven in the Appendix 1 of this thesis.

4.3 Results and discussion
4.3.1 Characterization of GNPs
The TEM image of synthesized GNPs is shown in the inset of Fig. 4.3(b). It can be seen for theimage that particles are approximately spherical. The size distribution of the GNPs in thecolloidal solution, obtained by DLS measurement is shown in Fig. 4.4(a). As seen from thefigure, the maximum and average diameter of the synthesized GNPs are 33.34 nm and 22.95
nm respectively with the standard deviation of 12.77 nm. The presence of symmetrical
nanoparticles was further corroborated by measuring the UV-VIS spectrum of the colloidal
solution, which shows only one LSPR peak at a wavelength of 524 nm, as illustrated in Fig.
4.4(b). For radius = 44 nm, the modelled spectrum of GNPs matches well with theexperimentally obtained UV-vis spectrum, as shown in the same figure. The slight mismatch
between the experimental and the modelled spectrum, especially at lower wavelength is due tothe assumption of uniform spherical GNPs of radius = 44 nm in the modelling. Due to the same

75

Chapter 4

assumption, the radius of GNPs obtained from the modelling is different from the average value

12

(a)

(b)

Percentage (%)

10
8
6
4
2
0

20

40
60
GNP size (nm)80

Normalized Absorbance (a.u.)

obtained from the DLS measurement.
1Modeling
Experimental

0.8
0.6
0.4
0.2

100

0
400

500

600

700

800

Wavelength(nm)Figure 4. 4: (a) DLS measurement of the GNPs (b) Experimental UV-VIS spectrum obtained, with superimposed
results of a model based on Mie scattering.

4.3.2 Refractive index response of GNPs-coated fibre probe
The success in creating the coating of GNPs layer was ensured by measuring its response tosolutions of known and varying RI. As seen in the Fig. 4.5(a), with varying RI from 1.33 to
1.42, the absorbance increases with simultaneous red wavelength shift of LSPR peak (peakaround 524 nm). The LSPR peak shows a linear variation (R2 = 0.92) with respect to RI, as
shown in Fig. 4.5(b). The sensitivity of the probe, (calculated from fitting) is ≈ 240 nm/RIU.
1.33
1.34
1.35
1.36
1.37
1.38
1.39
1.40
1.42

Absorbance (a.u.)

1.4
1.2
1
0.8
400

500

600
700
800
Wavelength (nm)

900

565

(b)
LSPR Wavelength (nm)(a)

Linear Fit
Experimental

555

545
Y = 239.65X + 219.47
R2 = 0.92535
1.32 1.34 1.36 1.38 1.4 1.42
Refractive Index (RIU)

Figure 4. 5: (a) Response of GNPs-coated fibre to increase in absorbance with increase in RI. The verticaldotted line at 545 nm is given as guidance for eyes. (b) Shift in LSPR wavelength in different refractive index
media.

76

Chapter 4

4.3.3 Heavy metal ion detection ability of GNPs-coated fibre
The heavy metal detection ability of the GNPs-only coated fibre was evaluated by measuring
its response in aqueous Lead Nitrate (LN) solutions of different concentrations (ranging from0.67 mM to 30 mM). In a way similar to the MUA-GNPs coated fibre (as discussed in next
subsection), the GNPs-coated probe was inserted into the solution and left undisturbed for 1
hour. After that hour was completed, the probe was taken out and dried using the air from the
hot air gun. Figure 4.6(a) shows the response of the fibre when it was in the solution. It can beseen from the figure that the absorbance of probe has increased in comparison with the response
in air (green dotted line), however, there is no change in response on varying LN solutions,which exactly matches the absorption spectrum obtained in Deionized (DI) water (i.e. where
there is no lead nitrate). As GNPs coated fibre is sensitive to external RI (discussed in preceding
subsection), the lack of response towards varying LN concentration shows that there is nochange in the reflective index of solution on varying LN concentration. This conclusion was
further corroborated by measuring the RIs of various concentrations of LN solution using an
Abbe refractometer. As expected, within the experimental error, all LN solutions showed the
RI of 1.33.
A similar result was observed when the fibre was dried, after taking it out from the LN solution.
As shown in Fig. 4.6(b), on drying the probe in air, its spectrum moves towards that of air andfinally overlaps with the response of air. No change in the absorption spectrum, even after
drying the fibre in air, shows that Pb2+ ions cannot be immobilized on the GNPs coated fibre,
thus highlighting the need of a linker to attach the “heavy metal” ions to the probe. Therefore,
the GNPs coated fibre was further functionalized with MUA and its responses are discussed in
the next subsection.

77

Chapter 4Absorbance (a.u.)(b)

DI water
0.67 mM solution
30 mM solution
air

1.2
1

Absorbance (a.u.)

(a)

0.8
0.6
0.4
0.2
400

500

600
700
800
Wavelength (nm)9000.67 mM solution
drying (0.5 sec)
drying (1 sec)
dried
air

1.2
1
0.8
0.6
0.4
0.2
400

500

600
700
800
Wavelength (nm)900

Figure 4. 6: Response of GNPs-coated fibre in (a) the Lead Nitrate (LN) solution (b) After removed from LN
solution, dried and monitored in air.

4.3.4 Lead ion detection using MUA-incorporated GNPs coated fibre
The comparison of the absorbance spectra of the MUA-GNPs-coated fibre with (only) the
GNPs-coated fibre is shown in Fig. 4.7(a). In the case of the MUA-GNPs fibre, there is a red
shift in the spectrum. This red shift in the spectrum indicates the successful immobilization of
the MUA on the fibre. The broadening of the absorbance spectrum after coating of MUA (canbe seen in the same figure), may be due to the presence of covalent bonding between the
carboxyl group of the MUA and the gold particles, where the carboxyl group acts as the‘anchor’ for the immobilization of a heavy metal ions (such as Pb2+), on the GNP surface. The
direct evident of the attachment of MUA to gold surface is obtained from the EDAX analysis.
The presence of high percentage of carbon and oxygen in the EDAX measurement carried out
on the portion (highlighted in Fig. 4.7(b)) of the GNPs-MUA coated fibre further confirms
successful coating of MUA.

78

Chapter 4

0.6

Absorbance (a.u.)

(a)

(b)

0.5
0.4
0.3
0.2
0.1
400

GNP coated OF
GNP+MUA coated OF

500

600

700

800

900

Wavelength (nm)Element

Wt(%)

O

31.5

Si

11.1

C

35.9

Pb

21.5

200 μmFigure 4. 7: (a) Absorbance spectrum of Au NP-coated fibre before and after coating with MUA. (b) SEM imageof GNPs-MUA-coated fibre after immobilization in Lead Nitrate (LN) solution. The table shows the EDAX
analysis of the highlighted section.

Figure 4.8(a) and 4.8(b) respectively shows the absorbance spectra of the MUA-GNPs-coatedfibre in different concentration of LN solution when probe is inside the solution and when it istaken out of solution, afterward dried completely. It can be seen from the Fig. 4.8(a) that the
LSPR absorbance peak remains almost unchanged during the incubation of the LSPR probe,
while it remains in a LN solution of different concentration. However, the change in positionof LSPR peak is quite evident when the probe is removed from the solution and afterwards
dried and monitored in air, as shown in Fig. 4.8(b). As can be seen from the results shown in
Fig. 4.8(c), an increase in the Pb2+ ion concentration (to 100 mM) results in the LSPR
wavelength being red shifted from 551.7 nm to 578.9 nm. The slope of the linear fitting of
LSPR red shift gives the Pb2+ ion sensitivity 0.28 nm/mM.

79

Chapter 4

Figure 4. 8: Response of MUA-coated fibre in (a) the Lead Nitrate (LN) solution (b) After removed from LN
solution, dried and monitored in air (c) Pb2+ concentration versus LSPR wavelength.

Previously it had been noted that the RI variation of the LN solution, due to the change in its
concentration, was relatively insignificant (the refractive index of the Pb2+ solution was noted
to vary slightly – by less than 0.006, creating a range from 1.330 to ~1.336 – due to the changeof the concentration from 0.67mM to 150mM). Such a refractive index change was within themeasurement error of the GNPs based sensor probe. Therefore, the recorded spectra from the
GNPs-MUA probe were similar, whether the LN solution or DI water were used. When the
GNPs-MUA coated probes were removed from the LN solution, it was very clear that some
Pb2+ ions had been immobilized by use of the MUA carboxyl group. Subsequently, when the
Pb2+ ion-immobilized probes were dried in air, an RI change due to Pb2+ contact was observed.
Therefore, the red wavelength shift seen from the LSPR spectra in air is a consequence of the
Pb2+ ion detection ability of the sensor, through the GNPs-MUA-incorporated LSPR opticalfibre probe developed.

80Chapter 4

In comparison to MUA, the EDTA has more affinity towards heavy metal ions [264].
Therefore, the lead ions bonded to MUA can be partially removed by dipping the optical fibreprobe into EDTA solution and after thoroughly washing with distil water, it can be reused.
However, as previously reported in literature [264,276], the response of chemical sensors
generally deteriorate after every round of reusage because it is not possible to remove all
bonded Pb2+ ions.
4.3.5 Performance comparison with prior work
In this work, a sensitivity 0.28 nm/mM and limit of detection of 800 μM (65 ppm) of Pb2+ ionswere obtained. In comparison to earlier reported limit of detection values of heavy metal ions,such as 0.36 μM for Pb2+ [262], 0.1μM for Hg2+ [263], 25μM Hg2+ + 79μM Cu2+ [270], thisreported value is slightly higher. However, the real strength of this sensor lies in its reusability,
portability, mechanical robustness, ease of fabrication and low-cost setup because it does notneed expensive and bulky source, detector, collimator, lenses, fusion splicer, etc.

4.4 Summary
In this collaborative proof of concept work, the design and application of a GNPs coated opticalfibre LSPR sensor has been demonstrated for detecting heavy metal ions present in aqueous
solution. This was achieved by functionalizing GNPs-coated OF with MUA to immobilize thelead ions. In calibrations carried out, the Pb2+ ion sensitivity recorded was 0.28 nm/mM. This
study establishes the principle of creating a heavy metal sensor of this type by using such a
coated optical fibre design.
Further work is to increase the sensitivity from the millimole range, through optimizing
parameters such as the gold nanoparticle size, the MUA drying temperature and the MUA
concentration.

81

Chapter 5

Chapter 5
Determination of aspect-ratio distribution ofgold nanorods in a colloidal solution using
UV-visible absorption spectroscopy
5.1 Introduction
Gold Nano Rods (GNRs), due to their asymmetric structure and unlike other symmetrical gold
nanoparticles such as spheres, shells, cages and cubes exhibit two plasmonic resonances, as
has been discussed in Chapter 2. As discussed previously in subsection 2.4.2, the plasmonicresonance corresponding to the shorter wavelength (around 520 nm), known as the T-LSPR,
arises due to the collective oscillation of free electrons in the presence of an external
electromagnetic field along the transverse dimension of the GNRs whereas, the resonance atthe longer wavelength, known as L-LSPR, is due to the oscillation of free electrons along thelongitudinal dimension. Due to the dependence of the position of the L-LSPR on their Aspect
Ratio (the length (L) divided by the width (W) and designated here by AR) and the external
refractive index, supported by well understood surface chemistry [277–280], GNRs have foundapplications in a wide variety of fields which are as diverse as biomedical sciences [281–284],
sensor development [285–288], imaging [289,290] and electronics-based applications such as
solar cells [291] development. For example, in photothermal cancer therapy (refer section
2.3.5. for the underlying principle), GNRs are preferred over GNPs because the position of LLSPR can be tuned in entire near infrared regime (NIR) by varying AR. Since, human tissues
are more transparent in NIR wavelength, tumours seated deep within tissue can be accessed
and treated with GNRs [292,293].
In one of the sensing applications, Yu and Irudayaraj used the AR sensitive L-LSPR resonanceto demonstrate multiplexed biosensor for detecting multiple target molecules [288]. For this,they synthesized GNRs with three different ARs (thus having three L-LSPR peaks),functionalised each with different antibodies and add them together to realise solution-phased
based multiplex biosensor. The addition of a target molecules the solution caused significant
red shift in the corresponding L-LSPR due to target specific binding and small shift in the other82

Chapter 5

two peaks due to non-specific bindings. Similarly, addition of two targets and three targets
resulted in red-shifts of corresponding two and three L-LSPR peaks respectively due to target
specific bindings. Mubeen et al. showed the usage of GNRs in photovoltaic by developing theplasmonic photovoltaic device, which consists of dense array of vertically oriented GNRs
coated with a 10 nm wide- band gap oxide (TiO2) and a low work function metal (Ti) [291].
Here, the majority of charges were derived from excitation of localised surface plasmon in
GNRs and short circuit photocurrent in the range 70-120 μAcm2 were obtained for simulated
one-sun AM1.5 illumination.
‘Bottom-up’ synthesis methods such as the seeded method [294], the electrochemical reduction
method [295] or photochemical reduction [296] of GNRs generally produce poly-dispersed
solutions with various ARs of the GNRs. Therefore, knowing the distribution of the ARs in thesynthesized colloidal solution is important as it reveals the quality of the solution and hence its
potential to be used in many possible applications. For example, it is important to have a narrowsize distribution in solution for uniform and long self-assemblies of GNRs [19]. In this regard,
TEM provides a very effective means for determining the actual size of the GNRs but obtaining
a statistically accurate size distribution of the colloidal solution is difficult because of thelimited numbers of GNRs spanning over a few selected images which are used to calculate theaverage AR. Further, GNRs tend to `self-sort' based on their sizes and shapes while drying on
the TEM grid and therefore the selection of the position for imaging become important [297].
The measurement of even hundreds of GNRs from TEM images is an onerous process andmost importantly, TEM devices are not readily accessible to all research groups. In recent
years, use of DLS techniques have been introduced to determine the size distribution of
nanoparticles but this approach is limited to spherical particles and it cannot be used foranisotropic particles, such as GNRs.
In previous work, Eustis & Sayed [298] have demonstrated that the Mie-Gans theory could be
used to determine the distribution of ARs in a given solution, by theoretically fitting theinhomogeneously-broadened LSPR absorption spectrum obtained using UV-Visible
spectrometer. However, the fitting technique used was manual and therefore very cumbersome.
Further, all the fittings employed were based on the assumption that the solvent used was puredeionized water and therefore the effect of contamination or impurities in the solvent wereignored. In this work, these important drawbacks are addressed by developing an algorithm
based on the Bellman Principle of Optimality, to automate the curve-fitting process. The effect83

Chapter 5of the external medium was considered by taking into account the dielectric constant, 𝜀𝑚 , ofthe solvent, while the fitting process was undertaken.

5.2 Background theory and algorithm formulation
According to the modified Gans’ Model [211], the absorption coefficient (𝛾) of the GNRs in
the colloidal solution considered is given by Eq. (5.1).

𝛾=322𝜋𝑁𝑉𝜀𝑚

3𝜆∑(1⁄𝑃𝐽2 )𝜀22
1 − 𝑃𝐽
]
𝜀
)
+ 𝜀22
𝑚
𝑃𝐽

(5.1)

𝐽=𝐴,𝐵,𝐶 (𝜀 + [1

where,𝑃𝐴 =1 − 𝑒2 1
1+𝑒[ 𝑙𝑛 () − 1]2𝑒2𝑒1−𝑒
1 − 𝑃𝐴𝑃𝐵 = 𝑃𝐶 =
,
2

(5.2)
(5.3)

and

𝑒 = √1 − (

𝑊 2
)
𝐿

(5.4)

In the above equations, 𝑃𝐴 , 𝑃𝐵 and 𝑃𝐶 are dependent on the shape of the GNRs as they also
depend on the variable, 𝑒, which in turn is an inverse function of the AR, i.e. the ratio of thelength (L) to width (W). N is number of GNRs per unit volume, V is the volume per particle,
𝜆 is the wavelength, εm is the dielectric constant of the surrounding medium and ε1 and ε2
represent respectively the real and imaginary parts of the permittivity for the gold used.
In this work, the permittivity of the gold used was calculated by interpolating the data given
by Johnson & Cristy [275]. Using an approach that is similar to that seen in the previous work,
as reported by Eustis & Sayed in [298], V is considered as a constant, as, the average volumeof the GNRs remains constant across the ARs in most of the seed synthesis methods. Figures
5.1(a) and (b) show the modelled dependence of the AR and εm respectively on the LSPR,
obtained by using Eq. (5.1) for arbitrary chosen value of εm and AR. In Fig. 5.1(a), while
studying the effect of AR, εm was kept constant at 1.77. Similarly, in Fig. 5.1(b), the effect ofεm was observed for a fixed value of AR = 2.5. It can be seen from both figures that, with theincrease in the AR and εm, L-LSPR shows a significant red wavelength shift.

84

Chapter 5

(a)

(b)

Increasing AR

Increasing εmFigure 5. 1: Self-normalized modelled absorption spectra showing the red shift in the Longitudinal Localised
Surface Plasmon Resonance due to an increase in (a) the Aspect Ratio (AR) and (b) the Permittivity of thesurrounding medium (εm).

The first step in automating the theoretical fitting to the experimentally obtained value of LLSPR is to rearrange and thus represent the absorption coefficient seen in Eq. (5.1), as the
product of two variables, as shown in Eq. (5.5). The first variable (𝐴𝜆𝐴𝑅 ), contains all the sizeand frequency dependent terms (as shown in Eq. (5.6)), whereas the second variable (𝑁 𝐴𝑅 ) is
the number of particles per unit volume of a given AR.
𝛾 = 𝐴𝜆𝐴𝑅 𝑁 𝐴𝑅 ,(5.5)

where,
3(1⁄𝑃𝐽2 )𝜀2

2
2𝜋𝜀𝑚
𝐴𝑅
𝐴𝜆 =
∑
3𝜆

2
1 − 𝑃𝐽
𝐽=𝐴,𝐵,𝐶 (𝜀 + [
]
𝜀
)
+ 𝜀22
1
𝑚
𝑃

,

(5.6)

𝐽

In the self-normalized absorption spectrum of a poly-disperse colloidal solution, the value of
𝑁 𝐴𝑅 varies from 0 and 1, thus indicating the contribution of GNRs of a particular AR in the
total absorption. The 𝑁 𝐴𝑅 equal to 0 shows that the solution is devoid of GNRs of a given AR,
whereas 𝑁 𝐴𝑅 equal to 1 indicates the mono-dispersed GNRs solution. Therefore, for a polydispersed colloidal solution having “n” varieties of ARs, the resultant absorption, at a given
wavelength, say (𝜆𝑥 ), is the cumulative effect of the contribution of the individual ARs.
Mathematically, this can be represented as shown by Eq. (5.7):
1

1

2

2

𝑛

𝑛

𝐴𝜆𝐴𝑅
𝑁 𝐴𝑅 + 𝐴𝜆𝐴𝑅
𝑁 𝐴𝑅 + ⋯ + 𝐴𝜆𝐴𝑅
𝑁 𝐴𝑅 = 𝐴𝑒𝑥𝑝
𝜆𝑥
𝑥
𝑥
𝑥

(5.7)

where,

85

Chapter 5
𝑛

𝑛

𝐴𝜆𝐴𝑅
is the absorption of the nth AR at 𝜆𝑥 , assuming 𝑁 𝐴𝑅 is 1, i.e. the absorption of a mono𝑥
dispersed GNRs solution with respect to the nth AR GNRs. This is calculated using Eq. (5.6),
𝑛for given 𝜆𝑥 at εm = 1.77. 𝑁 𝐴𝑅 is the actual contribution of a nth AR, and, unknown in thepresent case. 𝐴𝑒𝑥𝑝
𝜆𝑥 is the experimentally obtained value of the absorption at 𝜆𝑥 , obtained using
an analysis of UV-Vis spectrum of a chemically-synthesized colloidal solution.
Spanning 𝜆𝑥 over the entire LSPR wavelength range i.e. ≥ 615 nm, in “m” steps will constitutean over-determined set of linear equations (with n variables, m equations; where 𝑛 ≤ 𝑚). Thisset of over-determined equations in the matrix notation can then be expressed as:
𝐴𝜆𝐴𝑅
1

1

𝐴𝜆𝐴𝑅
1

1

𝐴𝜆𝐴𝑅
2
⋮
2
𝐴𝜆𝐴𝑅
𝑚

𝐴𝜆𝐴𝑅
2
⋮
1
𝐴𝜆𝐴𝑅
[⏟
𝑚

2
2

𝑨

⋯
⋱
⋯

𝑛

1
𝐴𝑒𝑥𝑝
𝜆1
𝑁 𝐴𝑅
𝑒𝑥𝑝
2
𝐴𝑅𝑛
𝐴𝜆2 × 𝑁 𝐴𝑅 = 𝐴𝜆2
⋮
⋮
⋮
𝑛
𝑒𝑥𝑝
𝐴𝑅
𝐴𝑅𝑛
[
]
⏟
𝐴
𝑁
𝐴𝜆𝑚 ]
[⏟𝜆𝑚 ]. . . 𝐴𝜆𝐴𝑅
1

𝑵

(5.8)

𝑨𝑒𝒙𝒑

Eq. (5.8), being over-determined in nature, cannot be solved to find the exact values of N.
Nevertheless, the value closest to the solution, represented by 𝑵∗ , can be found by using a
Least Squares Approximation (LSA), employing Eq. (5.9), where (𝑨′ ) and (𝑨−𝟏 ) represent
respectively the transpose and inverse of the matrix A [299] where𝑵∗ = ((𝑨′ 𝑨)−1 𝑨′ )𝑨𝑒𝑥𝑝(5.9)

However, the LSA may result in non-physical values of 𝑵∗ , such as negative values and/or
those greater than unity. Therefore their optimal physical values i.e. those lying between 0 and
1, are found using Bellman's dynamic programming Principle of Optimality (BPO) [300].
𝑥

Using the BPO approach, whatever the value of a given element of N, say 𝑁 𝐴𝑅 , is chosen, thecalculated values of the remaining elements of N will be optimal with respect to the chosen𝑥𝑥value of 𝑁 𝐴𝑅 . This ensures that each set of values (for every 𝑁 𝐴𝑅 ) is optimized and therefore,𝑥

out of all the chosen values of 𝑁 𝐴𝑅 , the value that yields the least fitting error will be the1

optimal value. Mathematically, to find the optimal value of 𝑁 𝐴𝑅 lying between 0 and 1, it is1varied between 0 to 1, using a step size of 0.001. For each step value, 𝑁 𝐴𝑅 is multiplied by(1)

the first row of A in Eq. (5.8) and shifted to the right-hand side, represented by 𝑨𝒓𝒆𝒅 in Eq.

86Chapter 5
(1)

(1)

(1)

(5.10). This operation modifies Eq. (5.8) to give Eq. (5.11), where 𝑨𝑻 , 𝑵𝑻 and 𝑨𝒓𝒆𝒅 are thetruncated versions of A, N and 𝑨𝒆𝒙𝒑 respectively.
𝐴𝜆𝐴𝑅
1
1
(1)
𝑨𝒓𝒆𝒅 = 𝑨𝒆𝒙𝒑 − 𝑁 𝐴𝑅

𝐴𝜆𝐴𝑅
1

2

2
𝐴𝜆𝐴𝑅
2

⋮
𝐴𝑅2
[𝐴𝜆𝑚
⏟

𝐴𝜆𝐴𝑅
1

...

1
1

𝐴𝜆𝐴𝑅
2
⋮
𝐴𝑅1
[𝐴𝜆𝑚 ](5.10)

𝑛
2

𝑁 𝐴𝑅
(1)
× [ ⋮ ] = 𝑨𝒓𝒆𝒅
𝑛
⋮
⏟𝑁 𝐴𝑅
𝐴𝑅𝑛
𝐴𝜆𝑚 ]
(1)
𝑵
𝑛
𝐴𝜆𝐴𝑅
2

⋯
⋱
⋯

(5.11)𝑻(1)

𝑨𝑻

In shorthand notation, the truncated matrices of Eq. (5.11) can be written as,
(1)

(1)

(5.12)(1)

𝑨𝑻 𝑵𝑻 = 𝑨𝒓𝒆𝒅

The closest unconstrained optimal values of 𝑵∗𝑻 using the LSA, the corresponding Error (𝑬𝒓)and Summed Square Error (SSE) are found using the following set of equations:′−1(1) ′ (1)(1)(1)∗
𝑵𝑻 = (((𝑨𝑻 ) 𝑨𝑻 ) (𝑨𝑻 ) ) 𝑨𝒓𝒆𝒅(1)

(5.13)

𝑬𝒓 = 𝑨𝒓𝒆𝒅 − 𝑨𝑻 𝑵∗𝑻(1)(5.14)

𝑆𝑆𝐸 = 𝑬𝒓′ 𝑬𝒓(5.15)
1

The SSE can be calculated for all the step values of 𝑁 𝐴𝑅 and among them, the one which gives
1

1

𝐴𝑅
the least SSE is taken as the optimized value of 𝑁 𝐴𝑅 , represented by 𝑁𝑜𝑝𝑡𝑖. Since, in
1

2

𝑛

𝐴𝑅
calculating 𝑁𝑜𝑝𝑡𝑖, all the unconstrained possibilities of 𝑁 𝐴𝑅 to 𝑁 𝐴𝑅 are considered, there is1

no need to recalculate the value of 𝑁 𝐴𝑅 while calculating their optimal values. For example,2

to calculate the optimal value of 𝑁 𝐴𝑅 , it is varied between 0 to 1 with a step size of 0.001.
1

2

𝐴𝑅
Since, 𝑁𝑜𝑝𝑡𝑖
has already been calculated in the previous step, for each step value of 𝑁 𝐴𝑅 , the1

2𝐴𝑅
first row of A (in Eq. (5.8)) is multiplied by 𝑁𝑜𝑝𝑡𝑖, the second row is multiplied by 𝑁 𝐴𝑅 andshifted to the right-hand side, i.e. subtracted from 𝑨𝒆𝒙𝒑, as shown in Eq. (5.16). This operation
(2)

(2)

(2)

will reduce the matrices A, N, 𝑨𝒆𝒙𝒑 in Eq. (5.8) to 𝑨𝑻 , 𝑵𝑻 , 𝑨𝒓𝒆𝒅 respectively, as shown in
Eq. (5.17).
87

Chapter 5

𝐴𝜆𝐴𝑅
1
(2)
𝐴𝑅1
𝑨𝒓𝒆𝒅 = 𝑨𝒆𝒙𝒑 − 𝑁𝑜𝑝𝑡𝑖

𝐴𝜆𝐴𝑅
1

3
3

𝐴𝜆𝐴𝑅
2
⋮
𝐴𝑅3
[𝐴𝜆𝑚
⏟

...
⋯
⋱
⋯

𝐴𝜆𝐴𝑅
1

1

𝐴𝜆𝐴𝑅
1

1

2
2

𝐴𝑅
2
𝐴𝜆𝐴𝑅
2
− 𝑁 𝐴𝑅 𝐴𝜆2
⋮
⋮
𝐴𝑅1
𝐴𝑅2
[𝐴𝜆𝑚 ][𝐴𝜆𝑚 ](5.16)

𝑛
3

𝑛
𝑁 𝐴𝑅
(2)
𝐴𝜆𝐴𝑅
2
× [ ⋮ ] = 𝑨𝒓𝒆𝒅
𝑛
⋮
⏟𝑁 𝐴𝑅
𝐴𝑅𝑛
𝐴𝜆𝑚 ]
(2)

(5.17)

𝑵𝑻

(2)

𝑨𝑻
(2)

The unconstrained value of 𝑵𝑻 using the LSA, Er and the SSE corresponding to each step isfound following the steps taken and shown in Eq. (5.13) to Eq. (5.15) and the resultant value
2

that then gives a minimum value of the SSE is selected as the optimal value of 𝑁 𝐴𝑅 . Similarly,
3

12

in calculating 𝑁 𝐴𝑅 , 𝑁 𝐴𝑅 and 𝑁 𝐴𝑅 are kept equal to the optimal values found from the1𝑛previous step. Likewise, after calculating all the values of N, i.e. 𝑁 𝐴𝑅 to 𝑁 𝐴𝑅 , the final
resultant (fitted) curve is obtained by post multiplying it by A, as per Eq. (5.8).
In order to determine the effect of the solvent on the process, the fitted curve for ε m taking
values from 1.77 to 2.3 with a step size of 0.05 is generated following the above procedure.
The error and SSE values determined from the experimental and the fitted curve (𝑬𝒓 = 𝑨𝒆𝒙𝒑 −𝑨𝒇𝒊𝒕𝒕𝒆𝒅 ; 𝑆𝑆𝐸 = 𝑬𝒓′ 𝑬𝒓) are calculated for all the step values of εm and among them, the valueof εm giving the minimum SSE is selected to generate the final fitted curve. The value of N
corresponding to the final fitted curve is taken as the contribution of the individual ARs.
The algorithm was coded in MATLAB [301] and the source-code is provided in the Appendix
2.

5.3 Methodology
5.3.1 Chemicals
The following chemicals used in the synthesis of GNRs were purchased from Aldrich:
Cetyltrimethylammonium

Bromide(CTAB;

C19H42NBr;

99%),

Chloroauricacid(HAuCl4.3H2O; 99.9%), Sodium borohydride (NaBH4, 99%), Silver nitride (AgNO3; 99+%),Ascorbic acid (C6H8O6, 99+%).

88

Chapter 5

5.3.2 Chemical synthesis
GNRs were synthesized by using the seed-mediated used previously at City, University of
London and reported by Jie Cao et al. [273]. In brief, the seed solution was prepared by
reducing a solution containing 5 mL of 0.2 M CTAB and 5 mL of 0.5 mM HAuCl4•3H2O with
600 μL of 0.01 M ice-cold NaBH4. After stirring the solution for an additional 2 minutes at 900
rpm, the seed solution was left undisturbed for 3 hours.
The growth solution was prepared by mixing a known amount of 20 mM AgNO 3 solution, 30
mL of 0.2 M CTAB solution and 30 mL of 1 mM HAuCl4•3H2O in the same sequence. To themixed solution, 420 μL of 0.0788 M ascorbic acid solution was added, while stirring at 350
rpm. This step will change the colour of solution from bright yellow to colourless. Further, 100
μL of seed solution was added to the growth solution and the resulting solution was left
undisturbed for 12 hours. Since CTAB is insoluble in deionized (DI) water at room
temperature, all the synthesis steps were performed in a water bath maintained at a constanttemperature of 301 K.
The excess of CTAB present in the GNR solution was removed by using two rounds ofcentrifugation at 3700g for 20 minutes for each round. After each round, the supernatant wasdecanted and the GNRs deposited at the bottom of the centrifuge tube were re-dispersed in thesame quantity of DI water. The role of different chemicals used in synthesis of GNRs is given
in Appendix 3.
5.3.3 Characterization
The absorption spectra of the GNRs solutions were measured by using a LAMBDA 35 UVVis spectrometer (Perkin Elmer Inc.) monitoring over the wavelength range from 400 nm to1000 nm, in steps of 1 nm. The TEM images were taken from JEOL at accelerating voltagesof 80kV and yielding 400k magnification. The dimensions of the GNRs from the TEM images
were measure using ImageJ, which is an open source image processing software inspired by
NIH image [302]. The DLS measurement was performed using a ZetaSizer Nano ZEN 3600
(Malvern Instruments).

89

Chapter 5

(a)

(b)

SSE = 0.0012(c)Figure 5. 2: (a) The UV-Vis absorption spectrum of the chemically synthesized sample (solid line) and thespectrum obtained by fitting the longitudinal resonance (dash line). Inset is shown a photograph of the GNRs
solution (b) AR distributions curve obtained through the measurement with the TEM images measurement (solidline) and fitting of the UV-Vis spectrum (dashed line). The legend shows the mean value for both graphs. (c) TEM
images taken at three different places on the TEM grid. The scale bar represents 50 nm.

5.4 Results and discussions
5.4.1 Comparison with TEM measurement
The experimental validation of the algorithm developed was performed by comparing the AR
distribution obtained from the use of the algorithm with that obtained by manually measuring
121 GNRs from TEM images captured at three different places on the TEM grid. Figure 5.2(a)shows an experimentally-obtained UV-Vis spectrum and the absorption spectrum obtained byfitting an experimental data points in the L-LSPR region. As it can be seen from the figure,both graphs match well (SSE = 0.0012) in the LSPR region. Further, a picture of the actual
synthesized colloidal solution is shown in the inset. The black color of the solution indicatesthe presence of a low number of GNPs. Figure 5.2(b) shows the distribution of the ARs
obtained by measuring GNRs from TEM images and those obtained from the use of algorithm
whereas, Fig. 5.2(c) shows the corresponding TEM images used for the ARs measurements. It
can be seen in Fig. 5.2(b) that, the algorithm used correctly predicted the most probable AR,

90

Chapter 5

the value of which is 3. However, the overall AR distribution obtained from the TEM images
is shifted towards lower ARs and consequently, the mean value of the distribution obtained by
the use of TEM is lower than that of the obtained from developed algorithm (𝜇 𝑇𝐸𝑀 = 2.9;
𝜇𝐹𝑖𝑡𝑡𝑒𝑑 = 3.3). This mismatch is due to the inability of the TEM to examine the macroscopic
volume in comparison to using L-LSPR region of UV-Vis spectrum, which is very muchsensitive to the macroscopic ARs distribution seen in the colloidal solution. To corroborate theabove claim, the UV-Vis spectrum was reconstructed by substituting the contribution obtained
from TEM measurement in Eq. (5.8), matching it with the experimentally obtained UV-Vis
spectrum. As shown in Fig. 5.3(a), UV-Vis spectrum retrieved using the TEM measurements
deviates significantly from the experimental UV-Vis spectrum SSETEM = 17.4839 is muchlarger than the value obtained from the algorithm SSEalgorithm = 0.0012). It is important to notethat due to the growth kinematics of seed-based synthesis, an AR cannot have a limitless
combination of length and width, because of the same average volume of GNRs for a given
colloidal solution. Therefore, any increase in the AR is caused by an increase in length and acorrelated decrease in the width, as can be seen from the TEM measurements of the GNRs
described in Fig. 5.3(b).

(a)

(b)

SSE = 17.4839

Figure 5. 3: (a) The UV-Vis absorption spectrum of the chemically synthesized sample (solid line) comparedwith spectrum retrieved from AR distribution obtained from TEM measurement (dashed line). (b) Dependenceof length and width of GNRs on AR obtained from TEM measurement.

91

Chapter 5

The inability to obtain a statistically accurate AR distribution from the TEM measurement wasalso reported by Eustis & Sayed [298] for 5 different samples, showing longitudinal resonancearound 630 nm, 700 nm, 850 nm, 900 nm & 1000 nm. In this work, these UV-Vis spectra havebeen reconstructed after extracting data using a Webplot digitizer [303], followed by the useof the algorithm developed to calculate the AR distribution. Figure 5.4 (a) shows thereconstructed UV-Vis spectra and Fig. 5.4(b)-(e) show the comparison of AR distribution
obtained from the developed algorithm and previously reported by Eustis & Sayed [298]. As it
can be seen from figure, there is good agreement between the present and previously obtained
AR distributions. This further validate the reliability of the developed algorithm.

(a)

(b)

(d)

(c)

(e)

Figure 5. 4: (a) The UV-visible spectra extracted from the work of Eustin & Sayed [298] . (b)-(e) Comparison of
AR distribution obtained from the algorithm developed in present work with the one reported in the same
publication.

5.4.2 Comparison with DLS measurement
The size distribution of the chemically synthesized sample obtained from DLS measurement
is shown in Fig. 5.5(a). It can be seen from the graph that the DLS measurement reports two
peaks centred around 2.544 nm and 69.94 nm. The first peak can be attributed to seed GNPs
which could not grow due to insufficient amount of gold in the growth solution, whereas second
peak accounts for fully developed GNRs and GNPs. Since DLS gives the size distribution withrespect to the hydrodynamic radius, i.e. the radius of an equivalent sphere having same
diffusion coefficient, it is difficult to obtain the AR distribution from the graph shown,

92

Chapter 5

especially when spherical and cubic gold impurities are present in the colloidal solution. For
example, few spherical GNPs impurities can be seen in right-hand TEM image, shown in Fig.
5.2(c). The inability of DLS to distinguish shape makes it unsuitable to measure the AR
distribution. In contrast to the DLS measurement, the algorithm developed here is unaffectedby the presence of large spherical GNPs impurities, because they do not exhibit a L-LSPR.
The algorithm developed was further benchmarked with the results of a numerical technique,as described in the next subsection, to circumvent the limitations discussed above andassociated with the TEM and DLS measurements.
(a)(b)
Size (d.nm)% Intensity

Std. Dev

Peak 1

2.544

40.5

0.7567

Peak 2

69.94

56.4

40.62

1

2

Figure 5. 5: (a) Size Distribution of chemically synthesized GNRs obtained by using the DLS technique (b)Quality of the fitting of the Absorption spectra generated by the test program, obtained by fitting the generated
curve with the bounded and the unbounded coefficients.

5.4.3 Theoretical Benchmarking of the algorithm
For the most effective theoretical benchmarking of the algorithm developed, the absorption
spectrum, resembling that of a chemically synthesized poly-dispersed colloidal solution, wasgenerated numerically from the combination of 11 GNRs samples having AR values ranging
between 3 and 4 (with a regular interval of 0.1), using Eq. (5.8). In Eq. (5.8), N was randomly
generated by the use of an in-built random function generator on MATLAB and A wasgenerated from Eq. (5.6) over the wavelength range from 400 to 900 nm, with a step size of 1
nm, at 𝜀𝑚 = 2.1.
The spectrum generated was input to the algorithm developed to retrieve the value of 𝜀𝑚 andthe corresponding (bounded) values of N. Further, to validate the point mentioned in theprevious section i.e. solving the over-determined set of linear equations without any constrain
may result in non-physical values, the LSA technique was used to obtain the unbounded values

93

Chapter 5of N. Both the unbounded and bounded values of N were cross compared with the known input(randomly generated) values of N to determine the accuracy of the methods used. Figure 5.5(b)shows the generated and retrieved absorption spectra. It can be seen from this that all three
spectra, i.e. the generated spectrum and the spectra obtained using the developed algorithm and
LSA match very closely at 𝜀𝑚 = 2.12. The value of 𝜀𝑚 = 2.12 was obtained by analyzing thevariation of the values of the SSE with respect to 𝜀𝑚 , as shown in Fig. 5.6(a). The minimum
SSE value was obtained at 𝜀𝑚 = 2.12 (and this is shown in the inset). It matches very well withthe value of 𝜀𝑚 = 2.1 used for generating the input spectrum.
(a)

(b)

ZoomedFigure 5. 6: (a) Fitted SSE as function of εm for the bounded coefficients. Inset shows the obtained minimum
SSE for εm = 2.12. (b) Left: the figure compares the generated (test) AR contribution with that generated by thealgorithm for the bounded and unbounded coefficients. Right: 'Zooming in' on the 3 ≤ AR ≤ 4 region from themain (Left) figure.

Figure 5.6(b) shows the input and retrieved values (i.e. the contribution), of N, represented asa percentage, for different values of AR. The blue solid spheres show the value of thecontribution obtained from the developed (bounded) algorithm. It can be seen from the figure
that, outside the input regime i.e. AR < 3 & AR > 4, the developed algorithm correctlypredicted the absence of any GNRs (i.e. a zero contribution) whereas for 3 ≤ AR ≤ 4, thevalues obtained from the algorithm are in good agreement with the input values (represented
by the red solid spheres), as shown in zoomed right-hand figure and in Table 5.1. However, if
the contributions obtained from the LSE is considered (shown by black stars in the main andthe zoomed figure), it gives a negatives contribution for some values of the AR, as indicatedby brown arrows in Fig. 5.6(b). Moreover, as given in Table 5.1, the SSE obtained from theFitted Bound is much lower than the SSE obtained from Fitted Unbound situation (𝑆𝑆𝐸𝑏𝑜𝑢𝑛𝑑 =1.83; 𝑆𝑆𝐸𝑢𝑛𝑏𝑜𝑢𝑛𝑑 = 7.59). This result shows that the algorithm which has been developed is94

Chapter 5

capable of correctly retrieving the contribution from the UV-Vis absorption spectrum of thepoly-dispersed colloidal solution.

Table 5. 1 AR and corresponding contribution obtained from Generated, Fitted Bound, & Fitted Unboundtechniques.

AR

Generated

Fitted Bound Error

Fitted Unbound

Error

3

17.17

18.39

0.06

16.8

-0.03

3.1

9.01

8.9

-0.01

10.14

0.13

3.2

18.41

17.6

-0.04

16.98

-0.08

3.3

0.68

0

-1

-1.14

-2.68

3.4

10.84

12.34

0.14

15.30

0.41

3.5

14.59

13.92

-0.05

11.11

-0.23

3.6

3.65

1.58

-0.57

3.92

0.07

3.7

6.85

8.47

0.24

6.85

-4.00E-04

3.8

3.82

2.18

-0.43

3.38

-0.117

3.9

6.55

9.02

0.38

8.28

0.26

4

8.22

5.59

-0.32

6.18

-0.25

SSE

1.83

7.59

5.4.4 Application on additional synthesized samples
After benchmarking, the bounded technique was used to determine the AR distributions in two
further chemically synthesized samples having different AR. These two chemicallysynthesized samples were obtained by varying the amount of AgNO3 added to growth solution
because the silver ions present in AgNO3 combine with Br2- to form AgBr in the presence of
CTAB and absorbs differentially to the facets of gold particles, thus promoting 1-D growth.
Figure 5.7(a) shows the L-LSPR fitting used in the case of a sample having well-separated LLSPR and T-LSPR peaks. As can be seen from the figure, in the L-LSPR regime i.e. where thewavelength is ≥ 615 nm, the fitted curve matches closely the experimentally obtained
absorption spectrum (SSE = 0.0086). Since, only the L-LSPR is used to obtain the contribution(as a percentage) of the individual ARs, extending the fitted spectrum to the T-LSPR spectral
region (which is less than the wavelength of 615 nm) will give the ideal spectrum, i.e. the95

Chapter 5
spectrum obtained in the absence of the GNPs (1 ≤ AR < 2). Therefore, the mismatch in the
T-LSPR regime between the fitted and the experimental curves can be used to visualize
quantitatively the magnitude of the GNPs present in the colloidal solution, as shown as thedotted region in Fig. 5.7(a). This can be described as, in the absence of any GNPs, theexperimental and the fitted curves would be matched closely around the T-LSPR as well. Fromthe mismatch at the T-LSPR in Fig. 5.7(a), it can be concluded that a significant number of
GNPs are present in the solution. Figure 5.7(b) shows the contribution (again as a percentage)of the AR present, where the calculated mean (μ) AR of the solution is 4, with a standard
deviation (𝜎) of 0.8.
(a)

(b)

SSE = 0.0086

Figure 5. 7: (a) The absorption spectra of chemically synthesized sample (solid line), juxtaposed with thespectra obtained by fitting the longitudinal resonance (dashed line). The dotted section highlights the mismatcharound transverse resonance. (b) AR distributions curve. The legend shows mean value and standard deviation.
For both graphs, εm = 1.92 was used.

Figure 5.8(a) shows the quality of the curve fitting in the case of a solution where the T-LSPR
and the L-LSPR cannot readily be distinguished. It can be seen that for a wavelength ≥ 615
nm, the theoretical curve fits well to the experimentally obtained spectrum. The mismatch
between the fitted and the experimental curves around the T-LSPR, as illustrated by the dotted
section on the graph, shows the presence of the GNPs. Figure 5.8(b) shows the AR
contributions and, as expected, by comparison to an analysis of the previous colloidal solution,
this solution has an abundance of less elongated GNRs (μ = 2.8; 𝜎 = 0.4) and the amount of
GNRs seen with an AR value greater than 4.2 is almost zero.

96Chapter 5

(a)

(b)

SSE = 0.0566

Figure 5. 8: (a) Measured (solid line) and fitted (dashed line) absorption spectra, for a low AR sample. Dotted
section qualitatively highlights the number of particles having AR ≤ 2. (b) Contribution of various AR values toobtain the fitted curve in (a). The SSE was a minimum for εm = 1.97.

5.5 Summary
The research carried out and reported in this Chapter has shown that the algorithm developedin this paper using Bellman's dynamic technique was an effective approach for the rapid
determination of the AR distribution of a synthesized GNRs colloidal solution by theoreticallyfitting the L-LSPR regime of the absorption spectrum. The developed algorithm, after
numerical and experimental benchmarking, was applied additionally to two in-house
synthesized solutions to determine the mean and standard deviations of the ARs. This technique
has been shown to give both a cost-effective and rapid way to determine the quality of thesynthesized solution as it avoids the need for more expensive TEM analysis of all of thesamples synthesized.

97

Chapter 6

Chapter 6
Summary and Future work
6.1 Summary of the work
The major objectives of the work, set out in Chapter 1, were achieved and several publications
in high impact international journals were produced as a result.
The achievements of the research project, with reference to the objectives set out in Chapter 1
can be summarized as:•

In the beginning, the review of nanoparticles, their synthesis processes and importantcharacterization techniques was conducted by analyzing data from several relevantpublished papers and book chapters. After the review, among the nanoparticles considered,rare-earth doped upconverting nanoparticles (UCNPs), due to their unique properties of
having thermally coupled radiative energy levels, were selected for further exploration as
the basis of the sensor head for luminescent temperature detection. However, the difficultyin modifying the UCNPs suitably for the development of heavy metals detection led to an
investigation of gold nanoparticles as an alternative. A detailed review of the underlying
principles of upconversion, the roles of dopants, the innovative ways to improve
fluorescence and selected interesting applications reported in last 10 years have beendelineated in Chapter 2. Moreover, in the last section of that chapter, the brief fundamentals
of Localized Surface Plasmon Resonance (LSPR) pertaining to nanoparticles synthesizedfrom gold have been considered.

•

After completing the literature review and finalizing the work on UCNPs for thedevelopment of portable optical fibre-based temperature sensors, the ~56 nm hexagonalphased UCNPs (NaYF4: (18%) Yb3+; (2%) Er3+) were synthesized using the solvothermal
method. Subsequently, the colloidal solution of the synthesized UCNPs was mixed with
PDMS in an appropriate ratio to obtain a UCNPs-PDMS composite and this was dip coatedon the tip of multimode optical fibre to realise a reflection based optical sensor. The ratioof the thermally coupled emission of the green bands (centred around 525 nm and 545 nm)
shows a linear response in useful range of 295 K to 473 K with, the sensitivity of (2.90 ±98

Chapter 60.40) ×10-3 K-1 and response time of ~ 5 seconds. The UNCPs powder-based sensor,
developed for cross-comparison, showed a higher sensitivity (4.91 ± 0.02) ×10-3 K-1 but
showed a lesser mechanical stability over time. The obtained sensitivity of the developed
powder and composite based sensors were of the same order as previously reported forseveral Er3+/Yb3+ doped glass-based sensors but the advantages of the developed sensors
lies in their portability and involved synthesis processes, which can be achieved with the
instruments found in the chemistry laboratory available to me.
•

For the development of the GNPs based heavy metal detection sensor, the colloidal solution
was synthesized and coated onto the optical fibre. The selectivity of the coated GNPs
towards heavy metal detection was achieved by modifying the surface with MUA andtested for various concentration of Pb2+ ions present in the aqueous solution. The LSPR
wavelength shifted from 551.7 nm to 578.9 nm on varying the concentration of Pb2+ from0 to 100 mM with a constant sensitivity of 0.28 nm/mM. This work has established theprinciple of creating a heavy metal sensor of this type by using such a coated optical fibre
design.

•Several colloidal solutions of GNRs were chemically synthesized and their quality wasdetermined by developing an algorithm to determine the AR distribution present by
theoretically fitting the normalized broadened L-LSPR region (𝜆 ≥ 615 nm) of the UV-Vis
spectrum. This fitting was carried out by first determining the individual L-LSPR spectrum
for given AR (for 2 ≤ AR ≤ 6), assuming uniform distribution using Gans’ Model andthen finding their amplitude (showing contribution) using the Bellman Principle of
Optimality. The developed algorithm was benchmark with previously published results andcross-verified with the results by DLS and TEM. The obtained results show that thedeveloped algorithm can be used as a cost-effective and rapid way to determine the qualityof the synthesized solution specifically needed for many potential applications for theadvanced sensor systems.

•

The positive research outcomes achieved in this work have been widely disseminated via
four peer reviewed journal publications and four international conference papers.

Thus, this provides the evidence, from the above points that the aims and objectives set out
in Chapter 1 have been addressed to a large extent.

99

Chapter 6

6.2 Proposal for future works
While working on the development of portable upconverting and gold nanoparticles based
optical fibre sensors and an algorithm to determine AR of GNRs, the following ideas have beendeveloped, which it is considered are worth pursuing in the future:• The developed UCNPs-PDMS composite coated optical fibre sensor can only measuretemperature at discrete points, however this work can be further extended to obtain asimultaneous thermal map of a large area. It can be achieved by first spin-coating the
UCNPs-PDMS composite to create a uniform layer over the large area and then using
colorimetric image detection technique instead of a more expensive spectrometer. This
colorimetric image detection is feasible because out of three bands of Er3+ visible emissions
i.e. those centred around 525 nm, 545 nm and 665 nm, where the only band around 545 nm
shows considerable change in the intensity, thus causing discernible colour change.
• The UCNPs-PDMS composite showed a linear response (a desired quality for any sensor)
in the temperature range of 295 K to 473 K. The linear response was attributed to an increasein non-radiative losses due to vibrational energy of the C-H stretching of PDMS and cannot
model using existing Boltzmann’s equation (ref. Eq. 3.1). Therefore, the development of asuitable model taking into account non-radiative losses which fits the experimental data very
well would give more details about underlying processes and other related parameters.
• The developed UCNPs-PDMS composite and powder-based temperature sensor shows
sensitivity comparable to several previously reported Yb3+/Er3+ doped glass-based
temperature sensors (ref. Table 3.2). It would thus be interesting to know the effect of PDMS
on the response and sensitivity of core-shell UCNPs, plasmon enhanced nanoparticles andratio of PDMS to UCNPs and this would be a fruitful area of exploration. Moreover, using
silver reflective paint at the tip of UCNPs-PDMS composite based optical fibre sensor
increased the upconversion intensity by ~23% (ref. Fig. 3.13(b)), which ideally could be
optimized to increase the amount of luminescence reflected back. This low increase may be
due to increase in scattering by the particle-based silver paint and hence reflection can befurther enhanced by using smooth thinner film. The use of Tollens’ regent for depositing
thin film of silver would be a good option to explore [304]. An improvement in the reflection
will enable use a cheaper, lower power laser source.
• The work has demonstrated the establishment of the principle of creating a portable heavy
metal sensor by MUA functionalized GNPs needs to be extended for optimization in thesynthesis processes such as the gold nanoparticle size and the MUA concentration to bring100

Chapter 6
its sensitivity further down from millimole range. Furthermore, investigation of thesensitivity of such sensors in different heavy metals is needed to determine the optimum
performance of the sensor.
• In the current work, MUA has been used as linker to attach heavy metal ions to GNP’s
surface. However, there are several other linkers reported in literate such as pyrazinium
thioacetate for detecting Pd2+ [305], chitosan for detecting Zn2+ and Cu2+ [306], Thioltagged DNA for all heavy metals [307], polyvinyl pyrrolidone for Hg2+ [263] and peptide
molecules for detecting Cd2+ [308]. It would be nice to explore these linkers as an alternative
to MUA along with the proper immobilization techniques to functionalize them on thesurface of GNPs.
• The developed MUA functionalized GNPs sensor shows no spectral change in LN solutions;hence, it has to take out of the solution and dry it to observe a noticeable LSPR shift. It
would be interesting to explore the exact reason behind this behaviour by studying the roleof various coating parameters such as thickness and coverage area of GNPs on the opticalfibre.
• The developed algorithm has shown to successfully to determine the AR in colloidal
solution, but it is limited only to asymmetrical GNRs i.e. 2 ≤ AR ≤ 6. However, in thebottom-up synthesis of GNRs, there is always a presence of symmetrical GNPs (AR< 2).
In the current algorithm, the amount of GNPs is determined qualitatively by visualizing themismatch in the T-LSPR regime between the fitted and the experimental curves because thequantitively determination of the variation of GNPs is challenging due to the dependence of
their absorbance on several parameters [309]. In this regard, other techniques like “Machinelearning” can be explored as an alternative solution. It will be valuable to have a single
algorithm which can perform complete quantitative analysis of a given colloidal solution.
The above suggested directions show that the exploration of UNCPs and gold nanoparticles asnovel sensor-heads will be a promising area of research for several years to come.

101

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132

Appendix 1

Appendix 1
close all; clc;clearvars;% Reading exp. value of RI from Johnson & Christy (1972) given at the end of program
experimental_refractive_index = data_john_christy();wavelength_john = experimental_refractive_index (:,1);n_exp = experimental_refractive_index (:,2);
k_exp = experimental_refractive_index (:,3);% reading experimental values
filename = 'gnp.Sample'; %%% UV_VIS spectrum file name (without header):filename = [filename '.csv']; %%%% UV-Vis file format (wavelength, Absorption (nm))
data_exp = load (filename);absorb_exp1 = data_exp (101:601,2);
absorb_exp1_norm = absorb_exp1./max(absorb_exp1);
lambda_exp = data_exp (101:601,1);
len = length(lambda_exp);%interpolation of experimental epsilon data over 300 to 900 at step of 1
ref_real_interpolated = interp1(wavelength_john, n_exp,lambda_exp,'spline');ref_imag_interpolated = interp1(wavelength_john, k_exp,lambda_exp,'spline');%calculating relative permittivity from ref. index data
epsilon_exp = (ref_real_interpolated+1i.*ref_imag_interpolated).^2;
epsilon_real_interpolated = real(epsilon_exp);
epsilon_imag_interpolated = imag(epsilon_exp);
ref_medium = 1.333;
radius = 44;
for i = 1:lenlambda = lambda_exp(i);ref_sphere_real = ref_real_interpolated(i);ref_sphere_img = ref_imag_interpolated(i);n_angle = 11;
S1 = zeros(1,(2*n_angle-1));
S2 = zeros(1,(2*n_angle-1));
tau = zeros(1,n_angle);
pi_n = zeros(1,(n_angle));pi_n_0 = zeros(1,(n_angle));pi_n_1 = ones(1,(n_angle));ref_relative = ref_sphere_real+1j*ref_sphere_img;
x = 2*pi*radius*ref_medium/lambda; % size parameterd_angle = 1.570796327/(n_angle-1);%%%%%%% program for calculating scatteringdx = x;133

Appendix 1
y = x*ref_relative;
x_stop = round(x + 4*x^(1/3)+2);
N_stop = round(max(x_stop,abs(y)))+15;
N_stop_2 = N_stop+2;
j = 1:n_angle;
theta = (j-1)*d_angle;
mu = cos(theta);%%%%%%% calculating D by backward recurrence
D = zeros(1,N_stop);
for n = N_stop:-1:2
D(n-1) = (n/y)-(1/(D(n)+(n/y)));end%%%%%%% upward recurrence
psi_n = zeros(1,N_stop_2);
chi = zeros(1,N_stop_2);
ksi_n = zeros(1,N_stop_2);
psi_n(1) = cos(dx);psi_n(2) = sin(dx);chi(1)= -sin(x);chi(2)= cos(x);ksi_n(1)= psi_n(1)-1j.*chi(1);ksi_n(2)= psi_n(2)-1j.*chi(2);Q_sca = 0;
for n = 1:N_stop
FN = (2*n+1)/(n*(n+1));
psi_n(n+2) = ((2*n-1)/dx)*psi_n(n+1)-psi_n(n);chi(n+2) = ((2*n-1)/dx)*chi(n+1)-chi(n);ksi_n(n+2) = psi_n(n+2) - 1j*chi(n+2);
a_num = (D(n)/ref_relative + n/x)*psi_n(n+2) -psi_n(n+1);
a_deno = (D(n)/ref_relative + n/x)*ksi_n(n+2) -ksi_n(n+1);
an = a_num/a_deno;
b_num = (ref_relative*D(n)+ n/x)*psi_n(n+2) -psi_n(n+1);
b_deno = (ref_relative*D(n) + n/x)*ksi_n(n+2) -ksi_n(n+1);
bn = b_num/b_deno;
Q_sca = Q_sca+(2*n+1)*((abs(an))^2+(abs(bn))^2);%%%%%%% for different polarization
for j = 1:n_angle
jj = 2*n_angle-j;pi_n(j)= pi_n_1(j);tau(j) = n*mu(j)*pi_n(j)-(n+1)*pi_n_0(j);S1(j) = S1(j)+FN*(an*pi_n(j)+bn*tau(j));S2(j) = S2(j)+FN*(bn*pi_n(j)+an*tau(j));
P = (-1)^(n-1);
T = (-1)^n;if(j ~= jj)
S1(jj) =S1(jj)+FN*(an*pi_n(j)*P+bn*tau(j)*T);
S2(jj) =S2(jj)+FN*(bn*pi_n(j)*P+an*tau(j)*T);
end
end
RN = n+1;
for j = 1:n_angle
pi_n_1(j) = ((2*RN-1)/(RN-1))*mu(j)*pi_n(j)-((RN/(RN-1))*pi_n_0(j));
pi_n_0(j)=pi_n(j);endend
Q_sca_array(i) = (2/(x^2))*Q_sca;134

Appendix 1
Q_ext_array(i) = (4/(x^2))*real(S1(1));
Q_back_array(i) = (4/(x^2))*abs(S1(2*n_angle-1))^2;
end
Absorb_calculated = pi*(radius)^2.*Q_ext_array./2.303;
Absorb_calculated_norm = Absorb_calculated./max(Absorb_calculated);
Q_ext_array_norm = Q_ext_array./max(Q_ext_array);figure();plot(lambda_exp,Q_ext_array_norm,lambda_exp,absorb_exp1./max(absorb_exp1),'Linewidth',6);set ( gca , 'FontSize' , 30 , 'fontweight' , 'b' , 'FontName' , 'Times New Roman') ;xlabel ( 'Wavelength(nm)' , 'FontSize' , 30 , 'fontweight' , 'b' ,'FontName' , 'Times New
Roman') ;ylabel ( 'Absorbance (a.u.)', 'FontSize' , 30 , 'fontweight' , 'b', 'FontName' , 'Times New
Roman' ) ;legend ('Modelling','Experimental');xlim([400,800]);%%%% GOld refractive index were taken from following reference% P.B. Johnson and R.W. Christy, “Optical constants of the noble metals,” Phys. Rev. B, vol.
6, pp. 4370, 1972.
% Data format [wavelength (nm), real (refractive index), img (refractive_index)]
function y = data_john_christy()y = [983.968254
0.22
6.350
891.942446 0.17
5.663
821.0596026
0.16
5.083
755.9756098
704.4318182
659.4680851
616.8159204
582.0657277
548.5840708
520.9243697

0.14
0.13
0.14
0.21
0.29
0.43
0.62

4.542
4.103
3.697
3.272
2.863
2.455
2.081

495.9200000 1.04
471.4068441
450.8363636
430.4861111
413.2666667
397.3717949
381.4769231

1.833
1.31
1.38
1.45
1.46
1.47
1.46

1.849
1.914
1.948
1.958
1.952
1.933

367.8931751
354.2285714
342.4861878

1.48
1.5
1.48

1.895
1.866
1.871

331.4973262
320.3617571
310.726817 1.53

1.48
1.54
1.893

1.883
1.898

300.9223301

1.53

1.889

292.4056604

1.49

1.878];

end135

Appendix 2

Appendix 2
close all; clc;clearvars;%%%% Reading exp. value of RI from Johnson & Christy (1972) given at the end of program
experimental_refractive_index = data_john_christy();wavelength_john = experimental_refractive_index (:,1);n_exp = experimental_refractive_index (:,2);
k_exp = experimental_refractive_index (:,3);%%%% reading experimental UV-Vis values from external file
filename = 'example.Sample'; %%% UV_VIS spectrum file name (without header):filename = [filename '.csv']; %%%%
UV_Vis_data_exp = load (filename);

UV-Vis file format (wavelength, Absorption (nm))% finding row number corresponding to wavelength 400 nm, 617 nm & 1000...wavelength_index is a subroutine, whose body is defined in the end
index_400 = wavelength_index(UV_Vis_data_exp (:,1),400);
index_618 = wavelength_index(UV_Vis_data_exp (:,1),618);
index_1000 = wavelength_index(UV_Vis_data_exp (:,1),1000);%extracting data from UV-VIS spectum file%LR stands for Longitudinal Resonanceabsorb_exp_LR = UV_Vis_data_exp (index_1000:index_618,2);
absorb_exp1_normalized = absorb_exp_LR./max(absorb_exp_LR);
absorb_exp_complete_spectrum_normalized = UV_Vis_data_exp(index_1000:index_400,2)./max(UV_Vis_data_exp (index_1000:index_400,2));
lambda_complete = UV_Vis_data_exp (index_1000:index_400,1); %% lambda = 400 nm to 1000 nm
lambda_LR = UV_Vis_data_exp (index_1000:index_618,1);
len_lamba = length(lambda_LR);%interpolation of experimental refractive index data over 300 to 900 at step of 1
ref_real_interpolated = interp1(wavelength_john, n_exp,lambda_LR,'spline');ref_imag_interpolated = interp1(wavelength_john, k_exp,lambda_LR,'spline');%calculating relative permittivity from interpolated refractive index data
epsilon_exp_complete = (ref_real_interpolated+1i.*ref_imag_interpolated).^2;
epsilon_real_interpolated = real(epsilon_exp_complete);
epsilon_imag_interpolated = imag(epsilon_exp_complete);%%%%%%%%%%%%%%%% Applying Gans theory %%%%%%%%%%%%%%AR = 2 : 0.2 : 6;
epsilon_medium = 1.77:0.05:2.1;
Absob_coff_transpose = zeros(length(AR),length(lambda_LR));
Absob_coff_transpose_normalized = zeros(length(AR),length(lambda_LR)); %% Normalized
Absorption Coefficient
N = 1; % Initial contribution
V = 1; %volume% Loop to find AR and Epsilon_medium having minimum Summed Square Error %%%%

136

Appendix 2% Refer main paper for algorithm
for k = 1:length(epsilon_medium)for i = 1:length(AR)elong = sqrt (1-(1/(AR(i)^2)));
PA = ((1-elong^2)/elong^2)*(1./(2*elong)* log ((1+elong)/(1-elong))-1);
PB = (1-PA)/2;
PC = PB;
coff_A = ((1/PA^2).*epsilon_imag_interpolated)./((epsilon_real_interpolated + ((1PA)/PA)*epsilon_medium(k)).^2 + epsilon_imag_interpolated.^2);
coff_B = ((1/PB^2).*epsilon_imag_interpolated)./((epsilon_real_interpolated + ((1PB)/PB)*epsilon_medium(k)).^2 + epsilon_imag_interpolated.^2);
coff_C = coff_B;
Absob_coff_transpose (i,:) = (2*pi*N*V*(epsilon_medium(k))^(3/2))./(3.*lambda_LR).*(coff_A + coff_B + coff_C);
Absob_coff_transpose_normalized (i,:) = Absob_coff_transpose (i,:) ./max(Absob_coff_transpose (i,:));
end
Absob_coff_norm = transpose(Absob_coff_transpose_normalized);factor = 0:0.001:1;
absorb_exp1_norm_new = absorb_exp1_normalized;
for i = 1:(length(AR))
if (i<length(AR))
trun_coff = Absob_coff_norm(:,i+1:length(AR));else
trun_coff = Absob_coff_norm(:,length(AR));end
trun_coff_tran = transpose (trun_coff);
factor_1 = factor .* Absob_coff_norm(:,i);for j = 1:length(factor)
absorb_exp1_norm_new_1 = absorb_exp1_norm_new-factor_1(:,j);if (i<length(AR))
P1 =(trun_coff_tran*trun_coff)\trun_coff_tran;
error_value_1 = P1*absorb_exp1_norm_new_1;
error_value = trun_coff*error_value_1;
else
absorb_exp1_norm_new_1 = absorb_exp1_norm_new;error_value = factor_1(:,j);end
SSE(i,j) = transpose(absorb_exp1_norm_new_1-error_value)*(absorb_exp1_norm_new_1error_value);end[min_SSE,min_index] = min(SSE(i,:));
freq(k,i,1)= factor(min_index);absorb_exp1_norm_new = absorb_exp1_norm_new-factor_1(:,min_index);
end
fitted_curve= Absob_coff_norm * transpose(freq(k,:));
error_final = absorb_exp1_normalized-fitted_curve;
SSE_final(k) = transpose(error_final)*(error_final);
end[min_SSE_eps,min_index_eps] = min(SSE_final);
epsilon_minimum = epsilon_medium(min_index_eps);%%%% for plotting complete curve i.e lambda = 400 nm to 1000 nm%interpolation of experimental epsilon data over 300 to 900 at step of 1
ref_real_interpolated = interp1(wavelength_john, n_exp,lambda_complete,'spline');137

Appendix 2
ref_imag_interpolated = interp1(wavelength_john, k_exp,lambda_complete,'spline');%calculating relative permittivity from ref. index data
epsilon_exp_complete = (ref_real_interpolated+1i.*ref_imag_interpolated).^2;
epsilon_real_interpolated = real(epsilon_exp_complete);
epsilon_imag_interpolated = imag(epsilon_exp_complete);% intialization corresponding to complete lambda
Absob_coff_transpose = zeros(length(AR),length(lambda_complete));Absob_coff_transpose_normalized = zeros(length(AR),length(lambda_complete));% Calculating complete UV-Vis form fitted contribution
for i = 1:length(AR)elong = sqrt (1-(1/(AR(i)^2)));
PA = ((1-elong^2)/elong^2)*(1./(2*elong)* log ((1+elong)/(1-elong))-1);
PB = (1-PA)/2;
PC = PB;
coff_A = ((1/PA^2).*epsilon_imag_interpolated)./((epsilon_real_interpolated + ((1PA)/PA)*epsilon_medium(min_index_eps)).^2 + epsilon_imag_interpolated.^2);
coff_B = ((1/PB^2).*epsilon_imag_interpolated)./((epsilon_real_interpolated + ((1PB)/PB)*epsilon_medium(min_index_eps)).^2 + epsilon_imag_interpolated.^2);
coff_C = coff_B;
Absob_coff_transpose (i,:) =(2*pi*N*V*(epsilon_medium(min_index_eps))^(3/2))./(3.*lambda_complete) .*(coff_A + coff_B +coff_C);
Absob_coff_transpose_normalized (i,:) = Absob_coff_transpose (i,:) ./max(Absob_coff_transpose (i,:));
end
Absob_coff_norm = transpose(Absob_coff_transpose_normalized);
fitted_curve_1= Absob_coff_norm * transpose(freq(min_index_eps,:));% calculating mean & standard deviation
mean = round(sum(AR.*freq(min_index_eps,:))/sum(freq(min_index_eps,:)),1);
variance_sum = (freq(min_index_eps,:).*(AR-mean).^2);
std_deviation = round(sqrt(sum(variance_sum)/sum(freq(min_index_eps,:))),1);%%%%% plotting figures %%%%%%%%%%%%%%% plotting uv-vis spectrum
figure ();p = plot (lambda_complete,absorb_exp_complete_spectrum_normalized,lambda_complete,fitted_curve_1,'Linewidth',6);p(1).LineStyle = '-';
p(1).LineWidth = 6;
p(1).Color ='[0,0,1]';p(2).LineStyle = '--';
p(2).LineWidth = 6;
p(2).Color ='[1,0,0]';set ( gca , 'FontSize' , 30 , 'fontweight' , 'b' , 'FontName' , 'Times New Roman') ;xlabel ( 'Wavelength (nm)' , 'FontSize' , 30 , 'fontweight' , 'b' ,'FontName' , 'Times New
Roman') ;ylabel ( 'Absorption (a.u.)', 'FontSize' , 30 , 'fontweight' , 'b', 'FontName' , 'Times New
Roman' ) ;legend ( 'Experimental' ,'Fitted Curve') ;xlim([400,1000]);138

Appendix 2
dimension = [0.2 0.5 0.3 0.3];
str = {'SSE:', num2str(min_SSE_eps)};annotation('textbox',dimension,'String',str,'FitBoxToText','on','FontSize' , 20 ,'fontweight' , 'b' ,'FontName' , 'Times New Roman');% plotting contribution
figure();p = plot (AR,(freq(min_index_eps,:)./sum(freq(min_index_eps,:)))*100);p(1).LineStyle = '--';
p(1).LineWidth = 2;
p(1).Color ='[0,0,1]';p(1).Marker = 'o';p(1).MarkerSize = 10;
p(1).MarkerEdgeColor = '[0,0,1]';p(1).MarkerFaceColor = '[0,0,1]';
set ( gca , 'FontSize' , 30 , 'fontweight' , 'b' , 'FontName' , 'Times New Roman') ;xlabel ( 'Aspect Ratio' , 'FontSize' , 30 , 'fontweight' , 'b' ,'FontName' , 'Times New
Roman') ;ylabel ( 'Contribution (%)', 'FontSize' , 30 , 'fontweight' , 'b', 'FontName' , 'Times New
Roman' ) ;dimension = [0.2 0.5 0.3 0.3];
str = {'\mu / \sigma:', num2str(mean) num2str(std_deviation)};annotation('textbox',dimension,'String',str,'FitBoxToText','on','FontSize' , 20 ,'fontweight' , 'b' ,'FontName' , 'Times New Roman');%%%% GOld refractive index were taken from following reference% P.B. Johnson and R.W. Christy, “Optical constants of the noble metals,” Phys. Rev. B, vol.
6, pp. 4370, 1972.
% Data format [wavelength (nm), real (refractive index), img (refractive_index)]
function y = data_john_christy()y = [983.968254
0.22
6.350
891.942446 0.17
5.663
821.0596026
0.16
5.083
755.9756098
0.14
4.542
704.4318182
0.13
4.103
659.4680851
616.8159204
582.0657277

0.14
0.21
0.29

3.697
3.272
2.863

548.5840708
520.9243697
495.9200000 1.04

0.43
0.62
1.833

2.455
2.081

471.4068441

1.31

1.849

450.8363636
430.4861111
413.2666667
397.3717949
381.4769231
367.8931751
354.2285714

1.38
1.45
1.46
1.47
1.46
1.48
1.5

1.914
1.948
1.958
1.952
1.933
1.895
1.866

342.4861878

1.48

1.871

331.4973262
320.3617571
310.726817 1.53

1.48
1.54
1.893

1.883
1.898

139

Appendix 2
300.9223301
292.4056604

1.53
1.49

1.889
1.878];

end% wavelength subroutine Body
function y = wavelength_index(wavelen, wave)[~, index_400] = min (abs(wavelen(:,1)-wave));y = index_400;
end

140

Appendix 3

Appendix 3
Chemicals used of Gold Nanorods Preparation
1) Cetrltrimethylammoniumbromide (CTAB)•

Chemical Formula: C19H42NBr; Molecular Weight: 364.45 g/mol•

It is surface capping agent which promotes one-dimensional growth of Nanorods by forming a bilayer on them. It also controls the approach rates of gold
ions and ascorbic acid to the seed particles. Therefore, lowering of the CTAB
concentration leads to nonrod-shaped particles.

2) Chloroauric acid:•

Chemical Formula: HAuCl4; Molecular Weight: 393.833 g/mol (trihydrate)•

It is source of the seed particles (come from seed solution) and gold (Au3+) ions(come from growth solutions). Increasing its content in seed solution will
decrease nano-rods length and eventually lead to spherical shaped particles.
This is due to less availability of Au3+ions in growth solution per seed particle.
Due to same reason, decreasing of Au3+ will also results in rounded particles.

3) Sodium borohydride:•

Chemical Formula: NaBH4; Molecular Weight: 37.83 g/mol•

It acts as reducing agent which help in in-situ formation of seed particles.

4) Silver Nitrate:•

Chemical Formula: AgNO3; Molecular Weight: 169.87 g/mol•

It may form AgBr in the presence of CTAB, which (AgBr) absorbs
differentially to the facets of Gold particles, thus promoting 1-D growth.

•

Increasing and decreasing amount of AgNO3 results in formation of nonrodshaped particles.

5) Ascorbic Acid:•

Chemical Formula: C6H8O6; Molecular Weight: 176.12 g/mol

141

Appendix 3•

It provides necessary pH needed for reduction of Au 3+ ions to Au0 acts as
reducing agent.

•

Increasing the concentration of Ascorbic acid will decrease the aspect ratio.

142

List of Publications

List of Publications
Journal Papers
1. R. Kumar, L. Binetti, H. Nguyen, L. Alwis, A. Agrawal, T. Sun and K. Grattan,“Optical fibre thermometry using ratiometric green emission of an upconverting
nanoparticle-polydimethylsiloxane composite.” Sensors & Actuators A: Physical, 312,
(2020), 112083.
2. R. Kumar, L. Binetti, H. Nguyen, L. Alwis, A. Agrawal, T. Sun and K. Grattan,“Determination of aspect-ratio distribution of gold nanorods in a colloidal solution
using Bellman Principle of Optimality” Scientific Reports, 9, (2019), 1-10
3. P. Dhara*, R. Kumar*, L. Binetti, H. Nguyen, L. Alwis, T. Sun and K. Grattan,“Optical fiber-based heavy metal detection using the Localized Surface Plasmon
Resonance technique” IEEE sensors Journal, 19, (2019), 8720-8726.

*EqualContribution
4. K. P. W. Dissanayak, P. Dhara, R. Kumar, S. Ghosh, H. Nguyen, T. Sun and
K.Grattan, “Fibre optic chemical sensors for environmental monitoring using sensitive
nano-material coatings” Asian Journal of Physics, 28, (2019), 567-576. Invited

Conference Papers
1. R. Kumar, S. Ghosh, H. Nguyen, T. Sun, K.T.V Grattan, “Portable optical fibre
temperature sensor based on green fluorescence emission from NaYF4: (18%) Yb3+,(2%) Er3+ nanoparticle PDMS composite”, Nanophotonics Conference 2019, Munich,Germany, 4-6 September 2019
2. R. Kumar, P. Dhara, H. Nguyen, T. Sun, K.T.V Grattan, “Optical fiber based
upconversion thermometry”, Photonics2018, Delhi, India, 12-15 December 2018.
3. R. Kumar, H. Nguyen, A. Agrawal, T. Sun and Grattan, K. T., “Estimation of the
aspect-ratio distribution in chemically synthesized gold nanorods solution using UVvisible absorption spectroscopy”, Journal of Physics: Conference Series, 1065, August
2018.
4. K. P. W. Dissanayake, R. Kumar, H. Nguyen, W. Wu, T. Sun and Grattan, K. T.,“Stability of Graphene Oxide encapsulated Gold Nanorods for optical sensing
purposes”, Journal of Physics: Conference Series, 1065, August 2018.

143