Surface Modification of Multimaterial Multifunctional Fibers Enabling

Biosensing Applications

Ana Lopez Marcano

Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in

partial fulfillment of the requirements for the degree of

Master of Science

In

Electrical Engineering

Xiaoting Jia, Chair

Wei Zhou, Co-Chair

Yunhui Zhu

May 2nd 2018

Blacksburg, Virginia

Keywords: Surface Modification, Plasmonics, Multifunctional Fibers, Soft Lithography,

Refractive Index, Raman Spectroscopy

Copyright © 2018 by Ana Lopez Marcano. All rights reserved.

Surface Modification of Multimaterial Multifunctional Fibers Enabling

Biosensing Applications

Ana Lopez Marcano

Abstract

During the last decades, the continuing need for faster and smaller sensors has indeed

triggered the rapid growth of more sophisticated technologies. This has led to the development of

new optical-based sensors, able to detect and measure different phenomena using light.

Furthermore, material processing technologies and micro fabrication methods have exponentially

advanced, allowing engineers and scientists to develop new and more complex sensors on optical

fibers platforms; specifically attractive for life science and biomedical research. All these

substantial developments have brought biosensors to a point where multifunctionality is needed,

this has led to envision the “Lab-on-Fiber” concept. Which promotes the integration of different

sensing components into a single platform, an optical fiber.

In this work, an integrated system with non-conventional polymer optical fibers and their

further surface modification has been developed. With these different approaches, electrodes,

hollow channels and plasmonic nanostructures can be incorporated into a single optical fiber-based

sensor, allowing for both electrical and optical sensing with the capabilities of tuning and signal

enhancement thanks to the metallic nanostructures. Different fiber substrates can be designed and

modified in order to satisfy multiple requirements for a wide variety of applications.

Surface Modification of Multimaterial Multifunctional Fibers Enabling

Biosensing Applications

Ana Lopez Marcano

General Audience Abstract

Silica optical fibers have been used since the 1960’s to guide optical signals, such as light,

with low losses through long distances; making them an attractive platform to use in large

communication systems. However, over the past couple of decades researchers have been trying

to implement these low-loss platforms in sensing devices for many different fields, such as

environmental and structural monitoring, and chemical and biomedical research. Unfortunately,

their high brittleness has prompted researchers to introduce different materials in the same

technology, leveraging the development of multimaterial non-conventional fibers. Where different

polymers and even metals have replaced silica as the structural material, making these fibers more

cost-affordable, flexible, and allow for multi-sensing capabilities of both electrical and optical

signals.

Although these multimaterial fibers are able to transmit light, they need to be

functionalized or modified in order for them to be able to sense different phenomena occurring in

their surrounding media. This can be achieved by integrating small particles or structures onto the

fibers end-faces, these small structures are known as plasmonic nanostructures. When light

(electromagnetic radiation) travels through a fiber and interacts with the free (conduction)

electrons of a metallic nanostructure, it leads to a coupling that results in collective oscillations,

which produce strong enhancement of the local electromagnetic fields surrounding the

nanostructures. The latter can be easily detected with the help of an optical spectrum analyzer that

iv

stores the transmitted light as a function of the transmitted wavelength. Noble metals like gold and

silver produce unprecedented electromagnetic field enhancements and are also biocompatible,

making them very attractive in biosensing applications.

In this research metallic plasmonic nanostructures were deposited on the end face of

multimaterial polymer fibers to enhance the optical properties and potentially the electrical

properties as well, creating new sensing devices. The enhancement produced by these structures

was studied with both experimental measurements and theoretical simulations. The results

demonstrate that the nanostructures investigated in this work can indeed enhance the optical

properties of the used polymer fibers, enabling them to work as sensing probes for a many different

applications, especially biosensing research.

v

Acknowledgements

First and foremost, I would like to thank God for making me a curious person who loves

to investigate His creations. “Trust in the Lord with all your heart, and lean not on your own

understanding, in all your ways acknowledge Him, and He shall direct your paths.” Proverbs 3:5-6

I would especially like to express my gratitude to my research advisors, Dr. Jia and Dr.

Zhou. Your constant support and mentorship gave me strength to complete my research and make

relevant contributions in this fascinating field. Thank you for giving me the opportunity to conduct

research in both groups, and for helping me complete the work presented in this thesis. I would

also like to thank Dr. Zhu for being part of my thesis committee and the college of engineering for

their financial support.

There have been many people who have walked alongside me during my college career.

They have guided me and revealed to me new doors with endless opportunities. I would like to

thank each one of them for being in my life, our experiences together have shaped me, especially

all the people who have been in my graduate school journey. My labmates, Kruthika, Romain,

Shan, Junyeob, Kelly, Ali, Maryam, Nam, Yujing, Chuan, Kemaya, and Aditya, who made my

time in the lab more enjoyable. Junyeob, who has been my mentor throughout this work deserves

especial recognition, as well as Ali and Shan. Without your help this would have been impossible.

I would also like to thank my family and extended family for always supporting me through

my journey. I am who I am because of the people who came before me. Finally, I would like to

thank my husband, Spencer, for all his patience, and his unlimited love and support, I would not

have done this without you.

vi

Table of Contents

Abstract .......................................................................................................................................... ii

General Audience Abstract ......................................................................................................... iii

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

Table of Contents ......................................................................................................................... vi

List of Figures ............................................................................................................................. viii

List of Tables ............................................................................................................................... xii

1. Introduction .................................................................................................................... 1

1.1 Surface Plasmon Resonance-Based Sensing ................................................................ 1

1.2 Micro/Nano Fabrication Approaches ........................................................................... 3

1.3 Optical Fiber Drawing Techniques ............................................................................... 4

1.4 Scope of Work .............................................................................................................. 7

2. Optical Fiber Sensors ..................................................................................................... 9

2.1 Optical waveguide principles ....................................................................................... 9

2.2 Lab-on-Fiber ............................................................................................................... 11

2.3 Optical Fiber Sensing ................................................................................................. 13

2.3.1 Refractive Index Sensors ..................................................................................... 14

2.3.2 Surface Enhanced Raman Scattering Sensors ..................................................... 15

2.3.3 Surface Plasmon Resonance Sensors .................................................................. 16

3. Fundamentals of Plasmonics ....................................................................................... 17

3.1 Surface Plasmon Resonance Theory .......................................................................... 17

3.2 Surface Plasmon Polaritons ........................................................................................ 20

3.3 Localized Surface Plasmon Resonance ...................................................................... 23

3.4 Surface Plasmon Excitation by Light ......................................................................... 25

3.5 Excitation of Surface Plasmon Resonances on an Optical Fiber ................................ 25

4. Numerical Modeling Techniques ................................................................................ 29

4.1 Finite-Difference Time-Domain (FDTD) ................................................................... 29

4.1.1 Lumerical FDTD Solutions.................................................................................... 33

4.2 Finite Element Method ............................................................................................... 34

vii

4.2.1 Comsol Multiphysics ........................................................................................... 35

4.3 Lumerical FDTD Solutions versus Comsol Multiphysics .......................................... 35

5. Fabrication and Experimental Techniques................................................................ 37

5.1 Introduction ................................................................................................................ 38

5.2 Experimental Procedures ............................................................................................ 40

5.2.1 Thermal Drawing of Multimaterial Fibers ........................................................... 41

5.2.2 Plasmonic Nanohole Array Fabrication Process ................................................. 43

5.2.3 Fiber Bundle Fabrication ..................................................................................... 45

5.2.4 Plasmonic Nanohole Array Transfer ................................................................... 47

5.2.5 Metallization ....................................................................................................... 49

5.3 Optical Characterization of Multifunctional Fibers ................................................... 51

5.3.1 Spectral Attenuation in Transmission Fibers ...................................................... 51

5.3.2 Refractive Index Sensing ..................................................................................... 55

5.3.3 Surface Enhanced Raman Spectroscopy ............................................................. 61

5.4 Electrical Characterization of Multifunctional Fibers ................................................ 67

6. Results and Discussion ................................................................................................. 69

6.1 Introduction ................................................................................................................ 69

6.2 Optical Properties ....................................................................................................... 70

6.3 Optimization of the Plasmonic Nanostructure ............................................................ 74

7. Conclusions and Future Outlook ................................................................................ 79

7.1 Summary and Conclusions ......................................................................................... 79

7.2 Significance and Contributions .................................................................................. 82

7.3 Future Outlooks .......................................................................................................... 83

References .................................................................................................................................... 84

viii

List of Figures

Figure 1.1 Stretched multimaterial preform dropped during fiber drawing .................................. 6

Figure 1.2 Illustration of an array of metallic nanostructures on the fiber end-face. ..................... 8

Figure 2.1 Illustration of the propagation of light through an optical fiber. .................................. 9

Figure 2.2 Schematics of light rays traveling in an optical fiber waveguide. (a) Leaky or refractive

rays. (b) Bound or guided rays. ..................................................................................................... 10

Figure 2.3 Illustration of the resulting evanescent wave formed as light undergoes total internal

reflection at the core/cladding interface. The evanescent wave decays exponentially away from the

interface......................................................................................................................................... 11

Figure 2.4 Direct-writing technique. (a) Schematic (not in scale) of the main technological steps

involved in the fabrication path. (b) Schematic of the modified spin coater chuck. Consales, M. et

al. Lab-on-fiber technology: Toward multifunctional optical nanoprobes. ACS Nano (2012). Used

under fair use, 2018....................................................................................................................... 12

Figure 2.5 Nano-transferring technique. Summary of the procedure used to fabricate and transfer

arrays of metallic nanostructures to the facets of optical fibers. Lipomi, D. J. et al. Patterning the

tips of optical fibers with metallic nanostructures using nanoskiving. Nano Lett. 11, 632–636

(2011). Used under fair use, 2018. ................................................................................................ 13

Figure 3.1 Geometry of a single interface between a metal and a dielectric for surface plasmon

propagation. Raether, H. in Surface plasmons on smooth and rough surfaces and on gratings 4–39

(Springer, 1988). Used under fair use, 2018. ................................................................................ 20

ix

Figure 3.2 Dispersion relation of SPs at interface between the dielectric εd and metal εm. Raether,

H. in Surface plasmons on smooth and rough surfaces and on gratings 4–39 (Springer, 1988). Used

under fair use, 2018....................................................................................................................... 22

Figure 3.3 LSPR based sensing techniques. (a) LSPR measurements using nanoparticles dispersed

in a solution. (b) LSPR measurements using nanoparticles attached to a planar substrate. (c) LSPR

measurements using a single nanoparticle on a substrate. ............................................................ 24

Figure 3.4 An optical fiber based SPR sensor with Ag–Au alloy nanoparticle metallic film.

Sharma, A. K. & Gupta, B. D. Fibre-optic sensor based on surface plasmon resonance with Ag-

Au alloy nanoparticle films. Nanotechnology 17, 124–131 (2006). Used under fair use, 2018. . 27

Figure 4.1 Geometrical meaning of the differential of a function f(x). Calculus - Differentiation

the Rate of Change. Available at: http://www.splung.com/content/sid/1/page/differentiation.

(Accessed: 3rd April 2018). Used under fair use, 2018. ................................................................ 30

Figure 4.2 Positions of the electric and magnetic field vector components on a cubic unit cell of

the Yee space lattice. Gao, H., Ouyang, M., Zhou, J. & Liu, D. Vector analysis of polarization

properties of rectangle phase grating. Opt. Commun. 271, 24–29 (2007). Used under fair use, 2018.

....................................................................................................................................................... 32

Figure 5.1 Multimaterial optical fiber processing and fabrication. (a) A schematic showing the

fabrication steps of the preform for multimaterial fiber probes. (b) Consolidation of the previously

assembled preform. (c) An illustration of the fiber drawing tower. The final dimensions of the

resulting fiber are determined by the ratio of capstan and downward speed. (d) Cross-sections of

some multi-material non-conventional optical fibers. .................................................................. 42

Figure 5.2 Fabrication process to create metallic film nanohole arrays. ..................................... 44

Figure 5.3 Fiber bundle fabrication process................................................................................. 47

x

Figure 5.4 Nanohole array transfer procedure ............................................................................. 48

Figure 5.5 Schematic illustration of the bundle metallization. (a) Schematics of the nanopillar

array, periodicity and multilayer multimaterial configuration. (b) Diagram of the evaporation

process in a high vacuum chamber. (c) Mechanical exfoliation to remove gold nanohole array film.

....................................................................................................................................................... 50

Figure 5.6 SEM photo of a modified fiber cross-section. (a) Multifunctional fiber cross section

(b)

....................................................................................................................................................... 51

Figure 5.7 Illustration of the attenuation measurement test set up by the cutback technique. .... 52

Figure 5.8 Calculated total attenuation for high loss polymer optical fibers. .............................. 54

Figure 5.9 Schematic of the measurement set up utilized to record the transmission spectra at

normal incidence, to obtain refractive index change data. ............................................................ 55

Figure 5.10 Transmission spectra (normalized) obtained through experiments from a

multifunctional fiber with plasmonic nanostructures on its tip. ................................................... 57

Figure 5.11 Gaussian-fitted transmission intensity spectra. ........................................................ 58

Figure 5.12 Refractive index sensitivity measurements of the fabricated nano-plasmonic sensors.

....................................................................................................................................................... 60

Figure 5.13 Schematics of a confocal Raman microscope (WITec Alpha 300 SR) system. ....... 62

Figure 5.14 SERS spectra of an unmodified fiber and a modified fiber incubated in 10-3 BZT. 63

Figure 5.15 Enhancement factor calculation. (a) Quarter section of the focused illuminated area.

(b) Side view of the deposited plasmonic nanostructures. The surface area of interest is highlighted

in orange........................................................................................................................................ 66

xi

Figure 6.1 Screen shot of the Lumerical solutions user interface. A periodic nanopillars array is in

the four individual frames. ............................................................................................................ 70

Figure 6.2 Transmission spectra, refractive index vs. wavelength. (a) Color plot of the

experimental transmission spectra through the multimaterial fiber. (b) Color plot of the simulated

transmission spectra obtained through FDTD. ............................................................................. 72

Figure 6.3 Graph of the transmission spectra of different substrate thicknesses. ........................ 73

Figure 6.4 Box plot of the refractive index measurements of the optimized nano-plasmonic fiber

sensors. .......................................................................................................................................... 75

Figure 6.5 Refractive index vs. wavelength, color plot of the simulated transmission spectra of the

etched devices obtained through FDTD. ...................................................................................... 76

xii

List of Tables Table 5-1 Total attenuation measurements set up and equipment ............................................... 53

Table 5-2 Center wavelengths and peak intensities of absorption band found in polymer optical

fibers. ............................................................................................................................................ 54

Table 5-3 Measured and calculated refractive index sensing slopes ........................................... 60

Table 6-1 Lumerical FDTD simulation parameters ..................................................................... 71

Table 6-2 Summary of average sensitivities of experimental and simulation results. ................. 76

Table 6-3 Enhancement factor distribution of tested fibers at maximum peak wavelength of 1090

nm. ................................................................................................................................................ 77

1

1. Introduction

This chapter introduces the basic concepts of surface plasmon resonance-based sensing and

the many different applications of plasmonic sensors. The advanced optical fiber drawing

techniques, well-known microfabrication methods used in planar substrates, and unconventional

fabrication methods are also described. Based on the achievements of current plasmonic-based

sensors, the objectives and motivations of this work are then defined.

1.1 Surface Plasmon Resonance-Based Sensing

Surface plasmon resonance (SPR) is the excitation of all the surface plasmons (SPs) within

the conduction band, at the interface between a metal (e.g. gold) and dielectric (e.g. air) 1,2. This

interaction occurs at the metal/dielectric interface and leads to substantial field enhancement. SPs

are very sensitive to the dielectric properties near metal surfaces. And the refractive index of the

dielectric substrate can modulate the high-concentrated electromagnetic fields generated by SPR.

This in turn, allows to monitor any dielectric refractive index changes in the surrounding media.

Typical biosensing SPR-based probes rely on the highly sensitive surface/media interface.

As a direct consequence, SPR sensors allow for real-time monitoring at the sensor tip. These highly

sensible structures can be further functionalized by previously immobilizing a receptor on the

metallic surfaces, which will then bind with an specific target analyte 3. This characteristic allows

for label-free sensing as well, an attractive feature of plasmonic sensors in biosensing applications.

The advances in SPR biomolecular sensing technologies have expanded the scope of

plasmonic utilization. With this method, propagating SPs are produced by illuminating thin metal

films through a prism in a Kretschmann configuration based on attenuated total reflection 4. When

an analyte (e.g. antibodies, viruses, bacterial toxins, cells, etc.) binds with the immobilized

2

molecules on the sensor’s surface, changes in the refractive index of the dielectric environment

surrounding the surface of the metallic structures alter the magnitude and position of the recorded

SPR spectra 5. This SPR shift can then be functionalized to work at certain frequencies. Combined

with well-established techniques such as surface chemistry and microfluidics, SPR sensing enables

real-time detection and measurement of analyte binding, providing quantitative information such

as affinity, concentration, and reaction kinetics 5,6. Consequently playing an important role in life

science and biomedical research, promoting the materialization of waveguide SPR sensors and

optical fiber sensors 7–9.

In contrast to propagating SPR sensors where special illumination configurations are

required, nano-plasmonic sensors on fiber platforms can function under simpler and less involved

conditions, by utilizing ordinary white light at normal incidence. Therefore, making the

instruments more compact and portable 10. Research efforts in the nano-plasmonic sensors field

are being geared toward the development of metallic nanostructures and defining new

methodologies to fabricate them on both planar and unconventional substrates. The nanostructures

characteristics, such as their material, shape, size, and patterns dramatically affect the optical

enhancement11. Therefore, the configuration of the overall nanostructure array configuration is of

utmost importance to the performance and optimization of a plasmonic device.

Gold and silver are the most commonly used materials due to their excellent properties as

well as their compatibility with organic elements. In addition, there is an endless variety of

structures, sizes and arrays that have been previously demonstrated in earlier plasmonic sensors.

From simple shapes such as nanoparticles and nanoholes, to more complex shapes such as bow

ties and spirals. Fundamentally, it is possible to engineer and fabricate plasmonic nanostructures

3

that possess desired optical properties for a specific applications utilizing well-known micro and

nanofabrication techniques.

1.2 Micro/Nano Fabrication Approaches

Advanced microfabrication techniques have been promoting the rapid growth of

plasmonics, electronics, and nano-photonics research. Particularly, the growth of nano-plasmonics

depends on the capabilities to reliably fabricate sub-100 nm structures. These structures are usually

fabricated using conventional top-down techniques. However, several other unconventional

methods have been also explored 12. Top-down approaches involve using advanced and well-

developed techniques, such as electron-beam lithography and focused-ion beam milling to create

a pattern directly onto the substrates. In contrast, unconventional fabrication techniques, such as

soft lithography and nanoimprint lithography, enable high-resolution patterning at low costs,

allowing more researchers to have the opportunity to access nano-plasmonic fabrication.

Electron-beam lithography (EBL) utilizes a beam of highly focused electrons to pattern

arbitrary shapes onto a planar substrate. The electron exposure enables selective removal of either

the exposed or non-exposed areas by immersing the photoresist in a solvent. The patterned resist

can be further used as a sacrificial layer to generate nanostructures with defined geometries after

metal deposition processes. However, the major drawback of EBL is the involved lift-off process

after metallization, it restricts the variety of substrates that can be utilized due to poor selectivity

between certain solvents and substrates.

Focused-ion beam (FIB) milling is a fabrication technique that impinges a focused beam

of ions onto the substrate to directly write patterns. As a maskless and high-resolution approach,

FIB milling is extensively used for direct patterning of nanostructures onto previously metallized

substrates. However, there are some limitations. Structures are patterned one by one, making the

4

process extra time-consuming and very expensive. Additionally, Gallium ions are implanted into

the substrate’s surface, contaminating the substrate and possibly reducing the performance of the

plasmonic sensor.

Current microfabrication materials include planar substrates such as silicon and glass, and

a wide variety of materials used during the deposition steps, both metals and dielectrics. Because

of the low cost and high processing flexibility that polymers generally have, expanding the use of

polymers in microfabrication can benefit the nano-plasmonics community 13. Soft lithography is a

rapidly emerging technique, in which soft elastic stamps are used to replicate features by molding

master patterns, usually fabricated with conventional methods 14. This means that from a single

nanofabricated structures array, multiple stamps can be made at a much lower cost. Although soft

lithography techniques can create patterns over larger areas and at a much lower cost, the resolution

and aspect ratio of the created structures is very limited.

Another unconventional fabrication technique that has been increasingly being utilized is

nanoimprint lithography (NIL). It accomplishes nano-pattern transfer by imprinting a hard stamp

with nanostructures into a resist cast on a substrate at a controlled temperature and pressure 15. NIL

compared to photon- or electron-beam lithography, relies on mechanical deformation. Thus the

resolution of the nanostructures is not limited by light diffraction or beam scattering. NIL has

shown a high-throughput and low-cost, and it is therefore suitable for large-scale patterning of

plasmonic nanostructures.

1.3 Optical Fiber Drawing Techniques

The technological effectiveness of light is remarkably broad. During the last decades, the

increasing need for faster and improved means of communication and sensing, has encouraged the

rapid growth of the fiber optics field. In 1956, for the first time a structured fiber made of two

5

different materials was thermally-drawn at the University of Michigan 16. This new optical fiber

enabled optical signals to travel with much lower loss than single-material glass optical fibers,

making them an attractive platform for a many different research fields.

Over the past decade, advances in the fiber drawing technologies and materials processing

have prompted the curiosity of researchers to introduce multi-material nonconventional optical

fiber devices 17. By combining a variety of materials into a prescribed fiber structure, optical fibers

were no longer considered passive elements, but they were able to actively sense and communicate

with composite systems. The integration of functional fibers with other sensing technologies is a

paradigm shift, from the common notion of optical fibers as communication elements, to the new

conception of complex and highly functional sensors.

The thermal drawing process starts with the fabrication of a multimaterial macroscopic

preform. The preform is in fact identical in its geometry and composition to the final fiber, but

with a much larger cross sectional area and shorter in length. A preform usually consists of a

cladding material and other functional materials that compose the cladding and any other elements

in a well-chosen fiber architecture. The cladding material can either be chosen for its exceptional

optical properties or mostly, to serve as a mechanical support for the stresses arising in the fiber

drawing process. In polymer preforms, cladding and active materials are assembled by either film

rolling of stacking, followed by a consolidation step to fuse the different materials together in a

solid structure.

After assembly and consolidation, the preform is then transferred to the drawing tower,

which consists of a vertical preheated furnace, a laser sensor, and a capstan that adds tension at the

end of the fiber. During the preheating of the preform, the hot zone temperature is set to around

100 °C to 120 °C above the cladding material’s glass transition temperature. The aim of this

6

preheating step is to locally soften the preform to a point where it necks down and starts falling

under the effect of gravity without rupturing as shown in Error! Reference source not found..

ollowing, the bottom part of the preform is cut and disposed, then the actual fiber drawing starts.

The end of the fiber is fed into the capstan which pulls on the fiber at a constant controllable speed

vcapstan, while the top of the preform is being fed into the furnace at a vdownward speed. Conservation

of volume dictates that the drawdown ratio u, relating to the preform cross-section dimensions to

that of the final fiber is achieved by the processing speed shown by:

𝜐 = 𝐿𝑝𝑟𝑒𝑓𝑜𝑟𝑚

𝐿𝑓𝑖𝑏𝑒𝑟= √

𝑣𝑐𝑎𝑝𝑠𝑡𝑎𝑛

𝑣𝑑𝑜𝑤𝑛𝑤𝑎𝑟𝑑

A laser sensor below the bottom iris, measures the cross-sectional dimensions of the drawn

fiber, while a tensiometer measures the tension pulling the fiber. By monitoring the process with

a LabVIEW program and properly controlling the different process parameters, such as the capstan

speed and the furnace temperature, a fiber can be drawn with the desired diameter and length. And

provided that the different materials in the preform have compatible drawing temperatures, the

geometry and composition of the preform can be maintained but scaled down by a factor of u.

Figure 1.1 Stretched multimaterial preform dropped during fiber drawing

7

The fiber thermal drawing process offers numerous advantages. This method allows the

incorporation of multiple materials into fibers, and this results in the production of fibers devices

with submicron features that have the same architecture as their preform. Materials such as metals

and semiconductors have been successfully incorporated into fiber structures, permitting the

realization of multifunctional optical fiber-based devices 18. This method, however, imposes some

constraints on the materials that can be utilized. The materials that compose the preform should be

able to co-flow. In other words, they should have similar glass-transition temperatures in order to

allow for a controlled draw with a uniform fiber structure along its entire length.

1.4 Scope of Work

Many plasmonic sensors have been demonstrated in the field of biochemical sensing and

spectroscopy thanks to the numerous advances in fabrications technologies, and their effectiveness

highly depend on the quality of the patterned nanostructures. Thus, an effective and high-quality

fabrication technique is demanded in order to successfully create plasmonic nanostructures.

Meanwhile, practical applications of plasmonic sensors require that these systems not only

showcase robustness but also flexibility and portability to be able to be implemented in different

scenarios.

The pairing of some unconventional lithography techniques with different multimaterial

polymer fibers would allow for both electrical and optical sensing with the capabilities of tuning

and signal enhancement thanks to the metallic nanostructures. This idea is depicted in Error!

eference source not found., where metallic nanostructures were placed on the end-facet of a

multimaterial non-conventional fiber. Different fiber substrates can be designed with structural

materials that can serve as ends to carry out electrical measurements, microfluidics, etc. and they

8

can be further modified with metallic nanostructures in order to satisfy multiple requirements and

to enhance both optical and electrical measurements for a wide variety of applications.

Figure 1.2 Illustration of an array of metallic nanostructures on the fiber end-face.

9

2. Optical Fiber Sensors

This chapter will cover the basic structure of optical fibers and waveguide principles. Next,

light propagation phenomena inside the fibers based on the interaction between the core and

cladding interface will be explained as a preface to introduce the lab-on-fiber technology. Finally,

a brief review of different types of optical fiber-based sensors will conclude this chapter.

2.1 Optical waveguide principles

An optical fiber is a cylindrical dielectric waveguide that transports energy at wavelengths

in the visible and infrared portions of the electromagnetic spectrum, which takes advantage of the

total internal reflection phenomenon occurring at the interface between two media with different

refractive indices. The central core in which light travels, is embedded inside an outer cladding

layer, which has a slightly lower refractive index than the core material. To promote guided rays

inside the fiber, the light should be incident on the core surface inside the acceptance cone at an

𝜃𝑎 angle, such that upon refraction into the core light can make an angle smaller than 𝜃𝑐, with the

fiber axis as shown in Error! Reference source not found. 19. When incident light strikes the

iber outside of the acceptance cone, it then starts losing power to the cladding after each reflection

and is not guided anymore, becoming a “leaky” ray or mode as shown in Figure 2.2(a).

Figure 2.1 Illustration of the propagation of light through an optical fiber.

10

Light rays that are entirely confined within the core, thanks to total internal refraction, are

defined as bound or guided rays, as shown in Figure 2.2(b). Since bound rays are completely

contained within the core, they can travel and propagate indefinitely without losses coming from

rays escaping the core but with absorption and scattering losses in the core. Both bound and leaky

rays can be categorized by their 𝜃𝑧 value as shown below:

Bound or guided rays: 0 ≤ 𝜃𝑧 ≤ 𝜃𝑐

Leaky or refractive rays: 𝜃𝑐 ≤ 𝜃𝑧 ≤ 𝜋 2⁄

According to Maxwell’s equations, when light undergoes total internal reflection, the

electromagnetic field cannot be discontinuous at the boundary between two optical media.

Therefore, a stationary wave is formed and it extends into the cladding normal to the interface 20.

This phenomenon is known as the evanescent wave, and as shown in Figure 2.3 the electric field

decays exponentially away from the boundary. The penetration depth of the evanescent field is

given by:

𝑑𝑝 = 𝜆𝑜

2𝜋 √(𝑛𝑐𝑜𝑟𝑒2 𝑠𝑖𝑛2𝜃 − 𝑛𝑐𝑙𝑎𝑑𝑑𝑖𝑛𝑔

2 )

Figure 2.2 Schematics of light rays traveling in an optical fiber waveguide. (a) Leaky or refractive rays.

(b) Bound or guided rays.

11

Where 𝜆𝑜 is the wavelength of light in free space, is the angle of incidence and 𝑛𝑐𝑜𝑟𝑒 and

𝑛𝑐𝑙𝑎𝑑𝑑𝑖𝑛𝑔 are the core and cladding refractive indices respectively. The evanescent field is part of

the guided light that travels through a region that extends outward, about 100 nanometers into the

cladding surrounding the core of the waveguide. Changes in the optical properties, such as the

refractive index of the surrounding media, can affect the phase velocity of the guided wave. This

is induced by the evanescent field

2.2 Lab-on-Fiber

One of the highlights of the work presented in this thesis is the development of unique

hybrid fiber-based sensors by combining multimaterial multifunctional fibers together with

nanostructures for the improvement of both optical and electrical measurements. This all-in-fiber

sensing platform is also known as lab-on-fiber, and it represents a technological revolution that

will enable miniaturization, light weight, relatively low cost, and highly desirable mechanical and

chemical properties that would allow them to be utilized as multifunctional laboratories for many

different applications 21. However, drawing multimaterial optical fibers can be difficult and could

require several attempts. This can be achieved by selecting materials with the desired optical and

electrical properties, which also have compatible thermomechanical properties 22.

Figure 2.3 Illustration of the resulting evanescent wave formed as light undergoes total internal reflection

at the core/cladding interface. The evanescent wave decays exponentially away from the interface.

12

The creation of highly integrated lab-on-fiber sensors can be very advantageous, since their

enhancement properties can be easily tuned to satisfy certain applications by changing the size of

the nanostructures, periodicity or materials employed. However, this is not an easy task to achieve

since a reliable and repeatable fabrication process is needed in order to integrate metallic

nanostructures onto optical fiber tips while preserving the integrity of the fibers as well. In this

context, the integration of functional materials onto optical fiber-based sensing platforms has been

explored in recent years, resulting in many successful demonstrations of promising fabrication

routes and uses of these devices 21,23,24.

Lab-on-fiber fabrication approaches can be divided into two groups, nano-transferring and

direct-writing 23. Nano-transferring relies on the preliminary fabrication of nanostructures onto

planar substrates by means of common micro/nanofabrication techniques, and their subsequent

transfer on optical fiber tips 25,26. In more recent years, however, direct-writing approaches (both

top-down and bottom-up) have been investigated and demonstrated for integrating nanostructures

on the optical fiber tip 21,23. Nonetheless, direct-writing methods rely on highly customized micro-

fabrication techniques to achieve the desired structures on the fiber tip. This imposes limitations

in terms of both elevated fabrication costs and the possible inability to utilize non-conventional

polymer fibers due to their poor compatibility with some solvents utilized during such processes.

Figure 2.4 Direct-writing technique. (a) Schematic (not in scale) of the main technological steps involved

in the fabrication path. (b) Schematic of the modified spin coater chuck. Consales, M. et al. Lab-on-fiber

technology: Toward multifunctional optical nanoprobes. ACS Nano (2012). Used under fair use, 2018.

13

Contrary to direct-writing techniques, nano-transferring techniques can potentially

introduce defects during the process. Such defects can be associated with the brittleness of the

evaporated materials combined with mechanical stresses introduced by the pattern transfer. Which

could potentially result in the fracture of individual structures on the substrate 27. Another, more

common, type of defect is the folding of the patterned film 25.

2.3 Optical Fiber Sensing

In today’s society, there is an increasing need to monitor different parameters with possibly

the same sensor, from temperature and stresses to the presence and concentration of chemical or

biological species in a sample. Along with other sensing technologies, optical fiber sensors have

become a very attractive sensing platform due to many different advantages that range from their

low cost and flexibility to their precision and sensitivity in various environments.

Figure 2.5 Nano-transferring technique. Summary of the procedure used to fabricate and transfer arrays of

metallic nanostructures to the facets of optical fibers. Lipomi, D. J. et al. Patterning the tips of optical fibers

with metallic nanostructures using nanoskiving. Nano Lett. 11, 632–636 (2011). Used under fair use, 2018.

14

Optical fiber sensors showcase high sensitivity and precision due to the dielectric nature of

glass and polymers. They offer high immunity to electromagnetic and radio frequency interference

that could potentially affect the measurements accuracy and precision in most electrical sensors.

Another great advantage is that they can operate in hazardous environments, such as high pressure

and corrosive or toxic environments 28,29.

Furthermore, optical fibers are intrinsically small, due to their reduced cross-section

making them very compact and flexible, as well as lightweight. Thus, they have become very

attractive for remote sensing applications, as they are resilient and useful when building a compact

measurement and acquisition system.

With these advantages in mind, optical fibers have been implemented to replace several

sensing platforms, especially chemical and biological sensors. Their use as chemical analytes

concentration sensors has been reported as early as the 1960’s. In general, the most popular

applications for optical fiber-based sensors have been reported to be chemical 30,31, biochemical 32,

and biomedical or environmental 33 applications. Overall, there are many different advantages and

applications to these optical fiber-based sensors. Continuing, some of the more common sensed

parameters will be explained in the remaining of this chapter

2.3.1 Refractive Index Sensors

Various physical, chemical, and biological phenomena can be detected and characterized

through refractive index measurements 34. In this perspective, optical fiber-based refractive index

sensors have found applications in in-situ monitoring of chemically active environments. Different

refractive index related parameters and techniques such as interferometry 35 and fiber gratings 36,

have been proposed and investigated as design elements for optical fiber-based refractive index

sensors.

15

An interferometer-based refractive index sensor is considered a highly robust sensing

system, it consists of two light beams, one beam is exposed to the sample media while the other

beam is used as a reference 35. When these two beams are combined to generate an interference

pattern, a change in the media refractive index alters the optical path length of the sensing beam,

causing a shift in the interference pattern that can be normalized to find the change in the refractive

index of the sensed media. On the other hand, fiber gratings measure refractive index changes from

the shifts of the transmission or reflection spectra, due to the influence of the external refractive

index on the coupling conditions of the gratings 36.

2.3.2 Surface Enhanced Raman Scattering Sensors

Surface enhanced Raman scattering (SERS) is a form of Raman spectroscopy which

involves the study of samples that interact with the metal structures on the substrate. In the case of

conventional Raman scattering, no metal structures are present on the surface, and the target

analyte interacts directly with the incident electromagnetic field. In surface enhanced Raman

scattering however, the substrate is coated with metallic nanostructures and the chemical to be

examined is on the metal surface. These metallic nanostructures involve the generation of surface

plasmons on the substrate’s surface, which in turn, transfer energy through and electric field to the

target molecules, allowing inaccessible vibrational structures to be determined.

The effect of SERS has been explored on optical fiber platforms for chemical sensing 37.

In general, sensors consist of a single optical fiber that serves as a waveguide of the exciting laser

beam, with its end-face coated with nanoparticles, resulting in a high quality SERS signal. A

variety of techniques for the creation of the nanostructures on the fiber’s cross-section have also

been demonstrated in the past, creating different geometries, structures and arrays; attracting many

researchers due to the possibility of tuning and customization 21,23,24,25,26.

16

2.3.3 Surface Plasmon Resonance Sensors

In recent years, many fiber-based SPR sensors have been studied. For instance, SPR

sensors based on either a multimode or a single mode platform patterned with metallic

nanostructures have been previously proposed and validated 38,39. In a SPR based sensor, light

waves interact with the collective oscillation of free electrons on the surface of metallic films or

nanostructures, located on the fiber tip. The unique properties of SPR have fascinated research

communities, moving towards optical biosensing research technologies. For example, when

analyte molecules bind to an immobilized target or to a metallic surface, the local refractive index

changes, this change can be monitored in real-time by detecting changes in the intensity of the

reflected light at the other end of the optical fiber.

17

3. Fundamentals of Plasmonics

Between 1902 and 1912 R. M. Wood at Johns Hopkins University noticed dark bands in

the spectrum of the refracted light 40. Although he ventured about how the light, gratings and metal

surfaces interacted, a clear answer to this phenomenon was not found. The first theoretical

treatment of these inconsistencies was by Lord Rayleigh in 1907 41. He found that the scattered

field was singular at wavelengths for which one of the spectral orders emerged from the grating.

He then observed that these wavelengths, which have come to be called the Rayleigh wavelengths

λR, correspond to the Wood anomalies. It was the work of Otto 42, Kretschmann and Raether 43 in

the late 1960s that brought understanding and showed the versatility of the SPR technique.

In recent years, SPR has shifted from a merely theoretical physical phenomenon to an

optical tool, which is in fact used extensively in chemical, physical, and biological fields. The main

reason for SPR sensors to become a powerful tool for the characterization of biomolecules

interaction is their capability for real-time monitoring and label-free sensing with high detection

sensitivity 44,45. The objective of this chapter is to provide an introduction to the SPR effect and

available SPR technologies, including SPR theory and properties of metals, properties of surface

plasmon polaritons (SPPs) and localized surface plasmons (LSPs), and their excitation on an

optical fiber platform.

3.1 Surface Plasmon Resonance Theory

The surface plasmon resonance (SPR) is the excitation of all the surface plasmons (SPs)

within the conduction band, at the interface between a metal (e.g. gold) and dielectric (e.g. air) 1,2.

A plasmon is a group of electrons that collectively oscillate in a conductive material. When

electrons are displaced, the positive charges exert an attractive force on the electrons and try to

18

move them back to their original locations. Plasmons oscillate once they are excited, and the

oscillation frequency of collective electrons in a volume metal is called plasma frequency and it

can be defined as:

𝜔𝑝 = √𝑁 𝑒2

𝜀0 𝑚

Where N is the conduction electron density, e is the charge electron, m is the electron mass,

and 0 is the permittivity of free-space 46.The surface plasmons are confined to the surface and

strongly interact with the incident light, making the surface plasmon field intensity at a

metal/dielectric interface very high. This is why SPR based sensing technologies are very sensitive

and very powerful tools for various different types of fields of study.

As mentioned before, unlike bulk or volume plasmons, surface plasmons can be only

excited along the interface between a metal and a dielectric, which makes them dependent upon

the response of the metal interacting with the incident light.

Over a wide range of frequencies, the dielectric properties of metals can be described by

the model proposed by Drude in 1900 46, which assumes the metal is a free electron gas as shown

by:

𝜀(𝜔) = 1 − 𝜔𝑝

2

𝜔2 + 𝑖 Γ𝑝𝜔

Where p is the collision frequency and plasma frequencies p are usually frequencies

within the visible spectra (between 400 to 790 THz). In the Drude model, interactions between

electrons are not taken into account. The electrons oscillating in response to the applied

electromagnetic field are damped via collisions with nuclei at a collision frequency p = 1/τ, where

19

τ is known as the average collision time of free electrons. The real and imaginary parts of ε ()

can be expressed as:

𝜀𝑟 = 1 − 𝜔𝑝

2

(𝜔2 + Γ𝑝2)

𝜀𝑖 = 𝜔𝑝

2 Γ𝑝

[𝜔 (𝜔2 + Γ𝑝2)]

The imaginary part εi of the dielectric function determines the amount of absorption inside

the medium and the real part εr determines the amount of polarization 47. For metals to maintain

their metallic characteristics, frequencies need to be limited to ω<p. In turn, for higher frequencies

for example p, which corresponds to optical frequencies, damping can be ignored and εr can

be approximated as 1 − 𝜔𝑝2 𝜔2⁄ , making εr negative. Thus, the equivalent permittivity in which

plasmonic behavior is exhibited requires that the permittivity becomes negative below resonance

and positive above resonance. Which is the interface between a surface with positive real dielectric

constant and a surface which real part of dielectric constant is negative.

In order to fully account for the interband transition in real metals, permittivity values are

preferred 48. In 1972, Johnson and Christy obtained such data from reflection and transmission

measurements on vacuum evaporated thin films. The authors obtained the refractive index n and

the optical absorption constant K of noble metals commonly used in plasmonics research such as

gold, silver and copper for the visible and near-infrared portions of the electromagnetic spectrum.

The complex refractive index of a metal can be defined as

𝑛 = √𝜀 = 𝑛𝑟 + 𝑖𝑛𝑖

20

And from the definitions of complex refractive index and permittivity, they can be expressed as:

𝑛 (𝜔) = 𝑛 + 𝑖𝐾

𝜀 (𝜔) = 𝜀′(𝜔) + 𝑖𝜀′′(𝜔) = 𝑛2

3.2 Surface Plasmon Polaritons

The simplest geometry capable of sustaining a Surface Plasmon Polaritons (SPP) is an

interface between a surface with positive real dielectric constant and a surface which real part of

dielectric constant εr is negative. Hence they are capable of exhibiting plasmonic behavior when

the wavelength of the incident electromagnetic radiation is greater than the size of the metallic

nanostructure 49. Figure 3.1 shows a planar geometry that sustains surface plasmons in a single,

smooth interface between two half regions 1 and 2, which are a dielectric, non-absorbing half

region (z > 0) with a positive real dielectric constant εd (ω) and an adjacent conducting half region

(z < 0) described with the dielectric function εm (ω), which can be described by the Drude model.

Figure 3.1 Geometry of a single interface between a metal and a dielectric for surface plasmon propagation.

Raether, H. in Surface plasmons on smooth and rough surfaces and on gratings 4–39 (Springer, 1988).

Used under fair use, 2018.

21

When an incident electromagnetic wave travels from the dielectric region to the metallic

region, the electric field with a component normal to the interface is the primary condition of

surface plasmon excitation, which induces a surface charge density. As a result, surface plasmons

have p-polarized (parallel to the plane of incidence) wave characteristics on the flat interface and

only a transverse magnetic TM polarized wave can be excited 49. No surface modes exist for the

transverse electric (TE) polarization. Considering a TM wave incident from a dielectric region to

a metal region, the fields in the two media must satisfy Maxwell’s equations:

∇ × �⃗⃗� = 𝜀

𝑐 𝜕

𝜕𝑡 �⃗�

∇ × �⃗� = −1

𝑐 𝜕

𝜕𝑡 �⃗⃗�

∇ ∙ 𝜀�⃗� = 0

∇ ∙ �⃗⃗� = 0

Where c is the speed of light in vacuum; and together with the continuity relations,

𝐸𝑥1 = 𝐸𝑥2

𝐻𝑦1 = 𝐻𝑦2

𝜀𝑑 𝐸𝑧1 = 𝜀𝑚 𝐸𝑧2

𝑘𝑥1 = 𝑘𝑥2 = 𝑘𝑥

Enable the dispersion relation of SPPs, in the system to be obtained:

𝑘𝑧1

𝜀𝑑+

𝑘𝑧2

𝜀𝑚= 0

22

This dispersion equation indicates that surface plasmons can only be excited when the

dielectric constants of the two media of the interface are of opposite sign. The properties of surface

plasmons with an electric field propagating along the x-direction, parallel to the surface, and

decaying along the z-direction, perpendicular to the surface, determine the complex value of kx.

As a result, the conditions εd > 0, εm < 0, and εd < | εm | should be satisfied for SPP propagation.

Figure 3.2 shows the dispersion relation of surface plasmons along the interface between

the dielectric surface εd and the metallic one εm 49. When 𝜔 < 𝜔𝑝 √1 + 𝜀𝑑⁄ , the propagation of

surface plasmons is bound to the interface, corresponding to non-radiative evanescent surface

waves. When 𝜔 > 𝜔𝑝, both kx and kz transform to real values, with surface plasmons radiating out

of the surface, these are called radiative surface plasmons. In the visible spectra, surface plasmons

exhibit large field confinement to the interface and a small propagation length; whereas at high

frequencies, surface plasmon fields extend deeper into the dielectric region, with small localization

and larger propagation length.

Figure 3.2 Dispersion relation of SPs at interface between the dielectric εd and metal εm. Raether, H. in

Surface plasmons on smooth and rough surfaces and on gratings 4–39 (Springer, 1988). Used under fair

use, 2018.

23

3.3 Localized Surface Plasmon Resonance

A localized surface plasmon (LSP) is the result of the confinement of a surface plasmon in

a metallic nanoparticle (usually gold or silver) of size comparable or smaller than the wavelengths

in the visible range of light, used to excite the plasmon 50. LSPs have two very important features

or characteristics. First, electric fields near the nanostructures’ surfaces are greatly enhanced. This

field enhancement can greatly decrease if the distance between the structures is increased. Second,

a particle’s optical absorption has a maximum at the plasmon resonant frequency. For noble metal

nanoparticles, this occurs within the range of visible wavelengths. For semiconductor

nanoparticles, however, the maximum optical absorption occurs in the near-infrared or mid-

infrared region.

When the frequency of incident photons matches the collective oscillations of the

conduction band electrons of the noble metal nanoparticles, localized surface plasmon resonance

(LSPR) occurs 51,52. This results in a strong absorption band or multiple bands in the visible region

for metals such as gold and silver. The intensity and wavelength of the LSPR band depends on

several factors, including the composition, size, and shape of the nanoparticles as well as the

dielectric properties of the environment surrounding the metal and their periodicity with respect to

neighboring nanoparticles 51.

Metal nanostructures can be used in sensing technologies according to their visible optical

properties in various ways. One of the most common approaches, which is the focus of this thesis,

involves monitoring the shift of the LSPR band for metal nanoparticles based on changes in the

local dielectric environment upon binding of analyte to the nanoparticle surface. This is known as

LSPR spectroscopy 53. LSPR based sensing devices can consist of nanoparticles dissolved in

solution 54, thin evaporated metal films 55, or chemically-synthesized metal nanostructures

24

immobilized on a surface 56. Their properties are then monitored through light transmission or

scattering/reflection on a collection of nanostructures or just an individual nanostructure, Figure

3.3 shows different ways to perform LSPR based sensing. The latter has been performed by

detecting changes in the wavelength (Δ𝜆) or intensity of the LSPR band of the nanoparticles.

However, in most cases, the LSPR response exhibits a red shift and increases intensity upon

analyte binding due to dielectric changes in the environment 52. Another, less common way to

utilize LSPR is by using nanoparticles as optical tags similar to other bio-labels in an immunoassay

or for cell imaging. In the presence of a cell or biomolecule of interest, a metallic nanoparticle

binds to the surface of a cell and produces a signal that can be measured with a detector or directly

imaged with the help of a microscope.

Figure 3.3 LSPR based sensing techniques. (a) LSPR measurements using nanoparticles dispersed in a

solution. (b) LSPR measurements using nanoparticles attached to a planar substrate. (c) LSPR

measurements using a single nanoparticle on a substrate.

25

3.4 Surface Plasmon Excitation by Light

In order to excite SPR with incident light, a phase matching condition needs to be satisfied,

which states that the excitation of SPR is possible only if the propagation constant of the light

vector matches the propagation constant of the surface plasmon 57. For any wavelength, surface

plasmons have a longer wave vector than light waves of the same frequency propagating at the

surface. This condition makes it impossible to excite surface plasmons directly by shining incident

light onto a smooth metal surface. The wave vector of light can be adjusted to match the wave

vector of the surface plasmon by launching it through a medium with a refractive index higher

than that where the fiber is going to be excited. Standard ways to excite a SPR are to couple light

through a prism 58, gratings 59, or through a waveguide 60. However, in recent years, there has been

an interest to excite SPR on the surface of optical fibers. This will be discussed in the subsequent

section.

3.5 Excitation of Surface Plasmon Resonances on an Optical Fiber

Despite the fact that sensors based on the Kretschmann configuration are very reliable and

can be relatively small, there has been an enormous interest to fabricate SPR based sensors using

optical fibers platforms, to produce a more compact and flexible device with remote sensing

capabilities. As explained previously in chapter 2, light propagates through the cladding and core

of an optical fiber in the form of modes and it experiences total internal reflection at the

cladding/core interface . These modes hit the cladding/core interface at different angles and finally

exponentially decay through the cladding. This is very similar to the total internal reflection in a

prism-based configuration.

Recently, remarkable progress has been made to develop SPR sensors on optical fibers

platforms and have attracted growing attention in the research community. Most of the already

26

designed and realized fiber-based SPR sensors work in the transmission regime, where light from

a broadband source is launched into one end of the fiber and is detected at the other end. With the

advantage of having SPR fiber-based sensors able to work in both the reflection and transmission

regime, allows these sensors to be more compact, portable, and practical for in-situ measurements

in small spatial volumes. Such qualities are highly desirable for many different applications. Even

though these sensors work in different modes, have different configurations and geometries, and

are suited for many different applications, they all have similar sensing mechanisms. The SPR

sensing mechanism is the most important element of the sensor design and its configuration

determines crucial sensing parameters such as sensitivity, compactness, and robustness.

In standard silica or polymer fibers, the coupling mechanism is not strong enough to excite

SPR. In fact, the strength of the resulting evanescent field resulting from the total internal reflection

at the core/cladding interface is too weak to cross the cladding and interact with any features on

the outer surface of a standard fiber. Therefore, current SPR sensors based on optical fibers depend

highly on deformations or modifications of the fiber’s morphology. Existing approaches are based

on the excitation of SPR by means of enhancing the evanescent field can be divided in two groups.

In the first approach, optical fibers are deformed in such a way that a metallic layer is

deposited in the proximity to the core and core/cladding interface. The evanescent field resulting

from the core reflection can excite SPR if it is strong enough to reach the metal layer, which can

be located in the proximity of the core/cladding interface by partially or completely removing the

cladding. This is typically achieved by creating a deep cut in the cladding or by bending the fiber

and polishing one of the fiber’s side. The metal coating can be a simple metallic layer, but it has

also been replaced with nanoparticle layers, which have been reported to improve the performance

of SPR fiber-based sensors 61. This new approach is shown in Figure 3.4, where a small portion of

27

the cladding was removed and then the exposed core was coated with a Silver-Gold alloy

nanoparticle metal film, surrounded by the sensing layer.

One of the disadvantages of the previously mentioned sensors is the fact that SPR is being

excited in both multimode and single-mode based fibers by uncontrolled fields. As a result,

experimental results show broad SPR resonances in the spectra that decrease the overall sensor

performance. From a structural perspective, these sensors are based on modified, non-standard

fibers that may result in a highly fragile sensor with possibly higher costs compared to sensors

made with standard silica fibers.

The second approach is relatively new. Fiber gratings are being used to couple incoming

light to a specific mode that generates an evanescent field at the metallic interface strong enough

to excite SPR 62. Although this proposed approach shows a promising level of sensitivity and

novelty, it has a few drawbacks. First, SPR excitation occurs because of coupling of only one

certain mode to the surface plasmons. The use of only one mode limits the operating range of the

Figure 3.4 An optical fiber based SPR sensor with Ag–Au alloy nanoparticle metallic film. Sharma, A. K.

& Gupta, B. D. Fibre-optic sensor based on surface plasmon resonance with Ag-Au alloy nanoparticle

films. Nanotechnology 17, 124–131 (2006). Used under fair use, 2018.

28

sensor. However, this can be mitigated by the use of multiple writings of the gratings with different

periods, which in turn makes the design more complicated. Second, the sensor design is noticeably

more complicated and has a more involved configuration, this makes the sensor not as compact

and hard to implement in different implementations.

There has been an increasing interest for nanophotonic devices applications and the

understanding of the underlying physical mechanisms to explain them. Various types of SPR based

sensors have been proposed, from tapered fibers and metallization to the introduction of

nanostructures attached to fiber’s end-face for refractive index sensing. However, difficulties

occurring during the manufacturing of sensors may result in changes to the SPR phase matching

condition. The work reported in this thesis investigates the current state-of-the-art in the field of

SPR based sensing together with new fabrication approaches that can be used to integrate nano-

plasmonic structures onto the end-faces of non-conventional optical fibers. This will produce more

robust and diverse sensing devices.

29

4. Numerical Modeling Techniques

In order to fully understand and to easily explain and investigate the physics of the

extraordinary optical and electrical properties of metallic nanostructures and how they could be

incorporated onto the end-face of optical fibers, a systematic modelling study was investigated.

These models require several parameters that can vary from model to model, including the type of

metal and its properties, and the size, shape, and periodicity of the metallic nanostructures. In

reality, it is not feasible to explore all these possible configurations experimentally. However, with

the help of computational methods and modelling tools, it is possible for researchers to make

significant contributions to this extraordinary field of study.

Numerical modelling is a fast and cost-effective method widely used in different fields

such as fluid dynamics, electromagnetics, and structural physics. It was utilized in this work as a

design tool, to investigate plasmonic nanostructures and their optical performance. There are

various numerical approaches that help researchers investigate optical transmission and reflection

from the metallic plasmonic nanostructures, each with unique advantages and disadvantages. This

chapter briefly describes and compares two commercially available software that were used in this

thesis, finite-domain time-difference (Lumerical FDTD) and finite element method FEM

(COMSOL Multiphysics).

4.1 Finite-Difference Time-Domain (FDTD)

The FDTD method solves Maxwell’s time-dependent equations by initially converting

them into finite-difference equations, which are then solved in a time-matching sequence by

alternately calculating the electric and magnetic fields in a spatial grid. The FDTD method was

first proposed in 1966 by Kane Yee for the analysis of the scattering of an electromagnetic pulse

30

by a perfectly conducting cylinder 63. It has since then become a useful tool used to study

electromagnetic waves and interference, radiation, and surface plasmon modelling and analysis 64.

Recently there has been a growing interest in applications of this technique to analyze the different

phenomena occurring in dielectric optical devices 65.

There are many advantages of using FDTD over other modelling tools, making it of high

interest so solve Maxwell’s equations 66. First, it is accurate and robust, the sources of error in

FDTS calculations are well understood, and allows the use of boundary conditions to enable

accurate modelling for a large variety of electromagnetic wave interaction problems. Second, due

to the time domain nature of this technique, FDTD calculates the nonlinear response of an

electromagnetic system. Finally, FDTD is a systematic approach and when a new structure is

defined and ready to be modelled, it is simply reduced to a problem of mesh generation rather than

the potentially complex reformulation of a series of differential equations.

Figure 4.1 Geometrical meaning of the differential of a function f(x). Calculus - Differentiation

the Rate of Change. Available at: http://www.splung.com/content/sid/1/page/differentiation.

(Accessed: 3rd April 2018). Used under fair use, 2018.

31

The FDTD method is based on approximating the spatial and temporal derivatives by finite

differences. As seen in Figure 4.1 the derivative of a function 𝑓(𝑥) at a point 𝑥0 can be

approximated in different ways 67, for example:

𝑑𝑓(𝑥0)

𝑑𝑥= 𝑓′(𝑥0) ≈

𝑓(𝑥0 + Δ𝑥) − 𝑓(𝑥0)

Δ𝑥

𝑑𝑓(𝑥0)

𝑑𝑥= 𝑓′(𝑥0) ≈

𝑓(𝑥0) − 𝑓(𝑥0 − Δ𝑥)

Δ𝑥

The above equations are the forward difference method and the backward difference

method respectively. From calculus, they were used to approximate the derivative of a

function𝑓(𝑥). A more accurate approximation is obtained by reducing possible errors coming from

these simple functions. The order of the error for each of these approximations is easily seen from

formal expansions as Taylor series about the value 𝑥, for the forward and backward difference

method this is shown below:

𝑓(𝑥 + Δ𝑥) = 𝑓(𝑥) + Δ𝑥𝑓′(𝑥) + (Δ𝑥)2

2 𝑓′′(𝑥) +

(Δ𝑥)3

6 𝑓′′′(𝑥) + …

And

𝑓(𝑥 − Δ𝑥) = 𝑓(𝑥) − Δ𝑥𝑓′(𝑥) + (Δ𝑥)2

2 𝑓′′(𝑥) −

(Δ𝑥)3

6 𝑓′′′(𝑥) + …

By taking the difference of the above equations, and by dividing the final result by 2Δ𝑥 the

following approximation is obtained:

𝑓′(𝑥) = 𝑓(𝑥 + Δ𝑥) − 𝑓(𝑥 − Δ𝑥)

2 Δ𝑥−

Δ𝑥2

6 𝑓′′′(𝑥) + …

32

The term on the left side of the above equation is the central difference approximation to

𝑓′(𝑥) and the following terms are the resulting error between the approximation and the exact

value of the derivative of 𝑓(𝑥). The error is proportional to the square of the finite difference Δ𝑥,

therefore, this method is considered second order accurate. And while it is possible to obtain and

use more accurate methods, the second order accurate central difference method is sufficiently

accurate to use in most of the practical modelling applications.

In any FDTD modelling software, the first step carried out by the algorithm is the

discretization of the computational space into cells, and the location of the electric and magnetic

field vectors on each cell 68. In 1966, Kane Yee developed an algorithm in which the electric and

magnetic field vectors were staggered as shown in Figure 4.2. In each cell, three electric field

vectors and three magnetic field vectors are defined, the magnetic fields are located normal to the

faces and the electric fields are located along the edges. This is a perfect depiction of Faraday’s

Law and Ampere’s Law. It can be seen in Figure 4.2 that the electric field vectors are forming

loops around the magnetic field vectors and vice versa.

Figure 4.2 Positions of the electric and magnetic field vector components on a cubic unit cell of the Yee

space lattice. Gao, H., Ouyang, M., Zhou, J. & Liu, D. Vector analysis of polarization properties of rectangle

phase grating. Opt. Commun. 271, 24–29 (2007). Used under fair use, 2018.

33

The algorithm used in FDTD software is based on the iterative computation of the electric

and magnetic field values at every cell in the previously defined computational space. After every

iteration, six new values of field vectors are calculated for every cell. In the Yee algorithm, the

electric and magnetic fields are separated by both space and time, this is why the Yee algorithm is

a so-called leapfrog algorithm. For example, if the electric fields are calculated at a time instant

2Δ𝑡 then the magnetic fields will be calculated at a time instant (𝑙 + 0.5)Δ𝑡, where 𝑙 is the time

step index and Δ𝑡 is the duration of a time step. The iteration process fits to the equations when

the second order central difference method is used to discretize the time and space derivatives in

Maxwell’s curl equations.

FDTD has been used in the modelling and solution of various different phenomena and

several research publications are based on the results obtained through this method. Computer

memory and visualization technologies have evolved exponentially, this is of particular advantage

to numerical techniques. For example, it allows FDTD software, which generates time-matched

arrays of field quantities, to illustrate the field dynamics in color videos and plots.

4.1.1 Lumerical FDTD Solutions

Lumerical FDTD Solutions TM is a commercially available software package that provides

state-of-the-art methods for solving Maxwell’s equations I complex geometries. It is a fully

vectorial method that gives both time-domain and frequency-domain feedback to the user, offering

unique insight into all types of problems and applications in electromagnetics and photonics. In

Lumerical FDTD Solutions TM the electromagnetic fields and structural materials of interest are

described on a discrete mesh. Maxwell’s equations are solved discretely in time, where the time

step used is related to the mesh size.

34

The modelled structures have a wide variety of electromagnetic material properties.

Lumerical FDTD Solutions TM is used to calculate how electromagnetic fields propagate from the

source through the structures of interest. Subsequent iterations provide the electromagnetic field

propagating in time. And the simulations continue to run until there are essentially no

electromagnetic fields left in the simulation region.

4.2 Finite Element Method

The finite element method (FEM) or finite element analysis (FEA) is a fundamentally a

method utilized to obtain a numeric approximation corresponding to a governing differential

equation, subject to the previously defined boundary conditions, over a prescribed geometric

domain. This domain is divided into a finite number of smaller non-overlapping regions, also

referred as elements. When all the elements are gathered together they completely cover the

domain of interest like the pieces of a puzzle. Historically, the discretization of single elements

has been used to solve problems in elasticity and heat transfer 66. Since then, finite element methods

have continue to evolve, driven by incredibly powerful computers, and the advantage to use this

technique to solve a wide variety of problems in science and engineering.

In these models, each discrete element contains a defined number of points, usually referred

as nodes, and the amount of nodes per element depends on the geometry used to discretize the

region of interest. For instance, a 2-dimensional problem may use triangular elements, and each

element, or triangle, would have at least three points, corresponding to the vertex points of the

triangle. Together, the nodes and elements are referred as the mesh. The dependent variable of the

governing differential equation is approximated over each element through polynomial

interpolation. The number of nodes in each element must be equal to the number of parameters

35

that needs to be determined in the interpolating function, in some cases, more nodes need to be

added to satisfy this requirement.

4.2.1 Comsol Multiphysics

Comsol Multiphysics TM is also a commercially available software package, which evolved

from other finite element analysis tools. It provides a computer aided design (CAD) interface to

define the geometry in 1-D, 2-D, or 3-D. It also contains a very sophisticated mesh generation

capability, where the element size and configuration can be evaluated depending on the physics to

be studied. Finally, it has a wide variety of numeric solver and post-processing tools.

In addition to its partial differential equation solver capabilities, Comsol Multiphysics TM

offers application specific modules, each tailored to solving specific types of physics and

engineering problems, including mass and energy transport 69, elasticity 70, and electromagnetics,

just to name a few disciplines. The modules in turn contain application modes, which help the user

define the governing partial differential equation to be solved, and allow the user to specify

essential parameters such as coefficients, boundary conditions, and initial conditions.

4.3 Lumerical FDTD Solutions versus Comsol Multiphysics

Computational methods are very powerful tools used in science and engineering research.

However, there are some drawbacks from using these approximation techniques compared to real,

physical tests. For example, in all time-domain computational methods, one of the most important

issues one of the most challenging issues is developing highly accurate approximations to the

physics-defined differential equations. This is because mathematically speaking, better

approximations often end up degrading the physical solution.

36

Theoretically speaking, if any computational method is sufficiently converged, they should

all arrive to the same solution. However, a deciding factor might be geometry to be studied. In this

context, if the geometry is very block-like, FDTD may be a better approach. But if there are several

sharp corners and asymmetric shapes, then FEM may converge faster. For the purpose of this

thesis, there are several advantages that Lumerical FDTD Solutions TM has to offer. First, it has a

simple, and straightforward formulation. Perhaps the biggest advantage is its applicability to a

wide range of problems; any structure can be modeled by simply specifying ε (permittivity) and μ

(permeability) over a computational domain which is periodic or non-periodic, and arbitrary

incident fields can be easily inserted into the simulations. Because of these advantages, FDTD was

the preferred modelling tool, and therefore has been used to investigate the optical properties of

optical fibers with metallic nanostructures on their end-face.

37

5. Fabrication and Experimental Techniques

Surface plasmon resonance (SPR) on metallic nanostructures offers a promising route for

manipulation and enhancement of light and its properties. However, the utility of SPR structures

is largely limited by currently implemented nanofabrication methods and the relatively

sophisticated optical components required to exploit their properties. In this chapter, plasmonic

optical fiber sensors are constructed by transferring periodic metallic nanohole arrays onto the end-

faces of optical fibers and depositing noble metals that will turn into the active plasmonic

structures. This metallic structures can consist of one or multiple metals and layers, by changing

these parameters, the properties of the optical sensor can be tuned to specific applications.

In this chapter, an extensive fabrication procedure is described. First, a simple and robust

polymer optical fiber drawing is explained, followed by the fabrication of nanohole arrays on

gold/chrome films. Continuing, a new technique used to transfer nanohole array films onto optical

fibers is outlined. This technique significantly simplifies the process of sensor fabrication and

potentially decreases the cost of the device. The optical properties of the designed plasmonic fiber

are then evaluated, first, as a refractive index sensor and then as a surface enhanced Raman

spectroscopy sensor.

Plasmonic polymer optical fibers take advantage of the consistent responses of the

waveguide substrate, excellent flexibility and mechanical properties, and the opportunity to

incorporate both electrical and optical sensing capabilities on the same platform. The electrical

properties were studied by measuring the bio impedance of the sensors and creating a circuit model

of the sensor that represents the intrinsic characteristics of the modified fiber. These features enable

these plasmonic fibers to open up an alternative avenue for biosensing and nano-plasmonics.

38

5.1 Introduction

Surface plasmon resonance is a collective electron oscillation resulting from the coupling

of electromagnetic waves with free electrons at metal/dielectric interfaces, as previously explained

in chapter 3. These interactions in metallic nanostructures lead to significant field enhancement

phenomena. Since electromagnetic fields are concentrated and channeled, SPR can be used to

detect light-matter interactions and produce special spectra in an extremely reduced area. This

phenomenal aspect gave rise to the increase interest in plasmonic research and its applications for

label-free sensing 71, chemical imaging, and surface enhanced spectroscopy 12. However,

functional plasmonic devices are usually confined to planar substrates or rely on bulky complex

optical configurations such as lasers, or prisms in order to operate, making it hard or impossible to

utilize these sensors in confined spaces or for remote sensing applications. For instance, analytes

have to be collected and transferred from their in-situ environment to specialized laboratory

settings in order to perform tests. As a result, removing analytes of interest from their original

environment can and probably induce large deviations from the real values of interest, especially

for biosensing applications. Therefore, a miniaturized, portable, and accessible plasmonic platform

is highly desirable for practical applications 72.

Polymer optical fibers serve as versatile sensing platforms due to their lightweight, small

size, relatively reduced cost, flexibility, and robustness. The implementation of active plasmonic

nanostructures onto optical fibers can thus significantly improve currently used optical sensing

technologies, making nano-plasmonic sensors versatile and greatly attractive to researchers and

scientists. This, would allow researchers to perform remote and in-vivo biological sensing, without

affecting the target living organisms. Consequently, this platform could extend the scope of

plasmonics utilization to many other fields, where this characteristics are highly desired.

39

However, the small dimension and large aspect ratio of optical fibers makes it challenging

to fabricate metallic nanostructures on their end-face. Generally two different strategies have been

utilized to create plasmonic nanostructures on fiber tips. One technique involves direct-writing or

in situ patterning onto the end-face. Some common nanofabrication approaches that have been

reported are electron-beam lithography (EBL) and focused ion beam (FIB). However, there are

some drawbacks of using this type of patterning techniques on unconventional substrates such as

optical fibers. First, EBL requires the implementation of special or modified apparatuses to be able

to host the optical fiber, and still the fibers are susceptible to suffer from fabrication defects due to

the small perimeter of their end-faces 21. FIB milling on the other side, poses a potential substrate

contamination by ions and thus a probable low yield 73.

The other technique used to create nanostructures on fiber tips separates pattern fabrication

from optical fibers and then transfers the previously prepared metallic nanostructures on planar

substrates onto fiber tips. This two-step process avoids the many challenges encountered when

directly patterning nanostructures on unconventional substrates. For instance, the polymer fibers

presented in this thesis work are incompatible with conventional fabrication techniques. In the

past, optical fibers were patterned with various periodic metal nanostructures on the fiber tip via

nano-skiving, where a microtome is used to section thin metal nanostructures embedded in epoxy

and then the patterned substrate is transferred to the optical fiber facets 25. However, this skiving

technique is not suitable for producing large areas of structured films due to the high level of

cutting force needed for the microtome to cut a very thin layer of the composite structure. In

addition, defects could occur due to the high mechanical stresses exerted onto the epoxy/metal

block. Finally, the transferred metallic nanostructures can suffer from folding and other defects

occurring during the transfer, as well as poor bonding to the fiber substrate.

40

In this chapter, a method to pattern polymer optical fibers with periodic metal

nanostructures on the tip by template transfer and further metallization was developed. This

approach allows for the fabrications of plasmonic nanostructures on large areas in two simple

steps: nanohole array pattern transfer and metal deposition. Distinct probe properties can be

achieved by drawing a specific polymer fiber, changing the periodicity of the patterned film, or by

varying the metallic materials deposited. Using this method, a refractive index sensing probe was

demonstrated in transmission mode. Furthermore, its SERS properties and electrical enhancement

were studied as well. The realization of this plasmonic polymer optical fiber will open the doors

for a new series of biosensing platforms, capable of incorporating both optical and electrical

sensing.

5.2 Experimental Procedures

The fabrication of the plasmonic optical fiber-based sensor is thoroughly described in this

chapter. First, the fabrication of polymer optical fibers will be discussed, from preform making to

thermal drawing. Next, nanohole arrays need to be pre-patterned on silicon wafers, onto which

gold and copper are deposited by electron-beam evaporation. The coupling of the nanohole arrays

and the polymer fibers, as well as the metallization will culminate the fabrication procedures.

To study the performance of the fabricated optical fibers, they were characterized optically

and electrically. They were first utilized as refractive index sensors and then, surface enhanced

Raman spectroscopy tests were carried out to determine the enhancement factor of the signal. Due

to the unique configuration of the nanostructures on the fiber tips, a further etching step was taken

to further enhance the refractive index sensitivity and SERS signal. Finally, the modified fibers

were electrically characterized by measuring their impedance in brain-like media.

41

5.2.1 Thermal Drawing of Multimaterial Fibers

Optical fibers have been an excellent platform for optical research. Especially in the fields

of optical networks and communication systems, this due to the minimal loss windows of silica

fibers at different wavelengths. Other potential research areas such as medicine, remote sensing,

could benefit from the attractive mechanical and optical properties of these waveguides.

Traditionally, optical fibers consist of doped silica cores surrounded by pure silica claddings. From

the manufacturing perspective there has been an increasing interest in the integration of non-

conventional materials into optical fibers. Being able to integrate multiple sensing capabilities into

a long, flexible and thin substrate could be the beginning of innovative sensing and even wearable

devices. This is actually the essence of lab-on-fiber. The growing interest in such new application

areas has, therefore, triggered the development and improvement in fiber drawing technologies 17.

This added to innovative post-processing techniques has resulted in the development of

multifunctional fibers 74.

Thermal fiber drawing is a well-established fabrication method used for the production of

functional microstructured fibers and it is shown in Figure 5.1. This simple and robust technique

enables the drawing of very intricate configurations while maintaining their well-defined material

geometries along the length of the fiber. In this thesis work, fiber drawing was utilized to fabricate

both simple waveguides and more complex, multifunctional fibers with embedded electrodes.

High throughput of the fiber is of this fiber drawing technique is due to the ability to

fabricate the macroscopic fiber preform, with the desired structure 75. Initially cleaned and kept in

vacuum, a polycarbonate (PC) film (Mcmaster-Carr, Tg 147 °C) film was tightly rolled around a

cyclic olefin copolymer (COC) rod (TOPAS, Tg 158 °C), shown in Figure 5.1(a). The rolled

Pc/COC preform was then placed into a furnace under vacuum above its glass transition

42

temperature (Tg), to fuse (consolidate) the PC film thermally, as shown in Figure 5.1(b). After

obtaining the desired macroscopic preform, it was then feed into the vertical furnace of a drawing

tower set up to approximately 203 °C. Then, a load was attached to the end of the preform, to

induce mechanical stresses and start the drawing process. As the preform was being softened due

to the high temperature and an extra pulling force was being exerted on the preform, its lower part

dropped without rupturing.

Figure 5.1 Multimaterial optical fiber processing and fabrication. (a) A schematic showing the fabrication

steps of the preform for multimaterial fiber probes. (b) Consolidation of the previously assembled preform.

(c) An illustration of the fiber drawing tower. The final dimensions of the resulting fiber are determined by

the ratio of capstan and downward speed. (d) Cross-sections of some multi-material non-conventional

optical fibers.

43

Consequently, a fiber with a much more reduced diameter compared to that of the initial

preform can be drawn by adjusting the stress level applied by the capstan at the lower region, the

feed velocity at the top region, and the temperature at the heat zone. Precise control over these

parameters enables drawing fibers with high accuracy. As shown in Figure 5.1(c), the diameter of

the drawn fiber can be monitored with a laser-measuring device incorporated into the drawing

tower.

5.2.2 Plasmonic Nanohole Array Fabrication Process

A major challenge in plasmonic sensors nanofabrication is to effectively pattern

unconventional substrates, such as optical fibers, that cannot be processed using traditional

fabrications techniques previously explained in chapter 1.2. Some of the more common challenges

encountered when direct writing onto these substrates are incompatibility with optical lithography

tools or wet chemical steps, where the substrate can be severely damaged or expensive tool

configurations are needed in order to enable fabrication onto unconventional substrates. In this

work an alternative patterned film-transfer method is presented.

Nanohole array based surface plasmon resonance sensors provide a promising platform for

label-free biosensing. For their extensive use, an efficient and robust fabrication method is

necessary in order to create nanoscale features on metallic films. To generate such metallic films,

a fabrication known as soft interference lithography (SIL) was utilized. SIL combines nanoscale

patterns obtained by interference lithography with the versatility of soft lithography 76,77. Unlike

costly and time consuming techniques such as adapted conventional deposition and nanopatterning

techniques previously reported in literature 21, SIL can create high-resolution nanostructures over

wafer scale areas with the possibility to incorporate these features on unconventional substrates.

44

Figure 5.2 shows the fabrication to create a SIL photomask. A Si master with an array of

nanopillars (height = 400 nm, diameter = 100 nm, ao = 400 nm) was initially made using

interference lithography. The polydimethylsiloxane (PDMS) masks were composite masks made

with two layers. First, a stiffer PDMS layer was molded against the master and cured. Then, a thin

layer of liquid PDMS was poured on top of the stiff PDMS, cured, and carefully removed to create

the SIL photomask.

This PDMS mask was then used in phase-shifting lithography, placing the PDMS in conformal

contact with a thin layer of positive photoresist (Shipley 1805, diluted 1:3 with 1-methoxy-2-

Figure 5.2 Fabrication process to create metallic film nanohole arrays.

45

propyl acetate) that had been previously spun on a Si (100) wafer and then exposed to broadband

UV light. The photoresist areas under taller elastomer features on the SIL photomask were exposed

to lower amounts of UV light, making them soluble in the developer. The mask was then removed

and the photoresist was developed in a dilute solution of Microposit 351 (1:5 in water) to create

an array of photoresist nanopillars. A 10 nm layer of Cr was electron-beam deposited and the

photoresist lifted off by sonicating the wafer in acetone, creating a chrome nanohole array.

Following, cylindrical pits were created beneath the exposed Si holes, with reactive ion etching.

Finally, a 50 nm layer of Au was electron-beam deposited, generating a Cr/Au nanohole array film

on to the Si surface and Au nanorods in the Si pits.

5.2.3 Fiber Bundle Fabrication

Highly efficient micro sensing systems are in demand because of their low cost and their

low invasiveness during launch. As useful tools for measurement and analysis, optical fiber-based

biosensors find themselves being very attractive for healthcare, environmental monitoring and

homeland security applications. And their use and further development have remarkably increased

in the past few years. To apply fiber optic technology as a sensing platform, numerous challenging

issues must be addressed, including surface modification.

In the past, great efforts have been devoted to the development of optical biosensors for

the determination of various media properties, and have been based on absorbance, reflectance,

fluorescence, or refractive index measurements. A considerable number of these studies have been

performed for the development of optical fibers based on LSPR modified by gold nanoparticles on

the fiber surface. Different surface modification methods have been outlined and demonstrated,

and in principle, they consisted on the treatment of one fiber facet at a time. In this thesis work

46

however, a multi-fiber modification technique has been outlined, where several fibers are bundled

together and embedded in a polymer matrix before surface modification.

The experimental surface modification of multifunctional optical fibers was performed

starting from individual fibers to create a final fiber bundle as shown in Figure 5.3. First,

multifunctional fibers were cut to about 50 cm in length using a fresh razor blade, they were then

placed inside a piece of nonporous alumina ceramic hollow rod (McMaster-Carr OD 1/8’’- ID

0.063’’) and aligned, while leaving about 5 mm protruding the rod. The fiber sections were placed

inside the ceramic rod until they were tightly packed together (between 5 and 10 fibers depending

on the cladding diameter) and then fixed together with phenyl salicylate (ReagentPlus® Sigma-

Aldrich, 99%) placed on both ends. After encapsulating the fibers in the ceramic rod, the fiber

cluster was then polished to obtain sub-micrometer roughness, using optical fiber polishing pucks

(6 um, 3 um, 1 um, and 0.5 um) and deionized water as the cooling fluid.

The previous three steps were repeated at least two times, to obtain a minimum of three

fiber clusters, needed for stability. As seen in Figure 5.3, the three clusters were then attached to a

rod using heat resistant tape. It was important then, to align the three fiber clusters with respect to

each other using a straight edge. Next, the fiber clusters were embedded into a polymer, to ease

future fabrication steps. Polydimethylsiloxane (PDMS) was selected as the structural material to

be molded around the clusters. The PDMS bundle was fabricated by preparing a mixture of Sylgard

184 silicone elastomer and Sylgard 184 curing agent (Dow Corning, Midland, MI) in a 10:1 ratio

by weight respectively. After mixing vigorously for 2 minutes, the mixture was then placed under

high vacuum to remove excess air bubbles. The viscous mixture was then poured into a Petri dish

which housed the fiber clusters and degassed under vacuum one more time before curing for 12

hours on a hot plate set to 50 °C. The PDMS bundle was carefully demolded and polished one

47

more time using polishing pucks (6 um, 3 um, 1 um, and 0.5 um), to remove any excess PDMS

covering the fibers’ end faces and to eliminate any scratches that may have be inflicted on the

fibers.

5.2.4 Plasmonic Nanohole Array Transfer

As previously mentioned, the fiber modification technique outlined in this thesis permits

the treatment of several fibers at the time. Accordingly, the fiber clusters were embedded in a

PDMS matrix. Here, the patterning of optical fibers with various metallic nanostructures by a

template transfer method is explained. This facile approach allows for realizing high-quality and

large-area general plasmonic structures from pre-fabricated nanohole arrays to nanopillars on

optical fibers by two extremely simple and widely utilized steps: transfer and deposition. The

fabrication of the final plasmonic nanostructures depends on the patterns of the used templates.

Figure 5.3 Fiber bundle fabrication process

48

Besides, different nanostructures can be achieved with the same template by controlling the type

of metals deposited and the number of layers of such metals.

The nanohole array transfer procedure is summarized in Figure 5.4. Before transferring the

nanohole film, the fiber bundle needs to be cleaned with oxygen plasma at a low power, 40 watts

of power being applied to the RF induction source. Oxygen gas flowed at 50 SCCM and the

cleaning takes process in 30 seconds. The next step was to section the nanohole array to the desired

size using a scribing tool and place it in a Petri dish with chrome etchant. After a couple of hours,

the sacrificial chrome layer must have been etched and the gold nanohole array is then carefully

placed in a Petri dish with deionized water. After 5 minutes have passed, the gold film is then

placed in a second water bath.

Figure 5.4 Nanohole array transfer procedure

49

Continuing with the transfer process, a glass slide and a pipette were utilized to successfully

transfer the gold nanohole array onto the bundle facet. First, the glass slide was immersed in the

beaker with deionized water in order to retrieve the gold nanohole array. Then, with the help of

more deionized water and a pipette, a “bridge” of water was created in order to transfer the gold

film from the glass slide to the bundle surface as seen in Figure 5.4. After the nanohole array is at

the desired location, the water “bridge” was gently wiped off and any excess water was evaporated.

5.2.5 Metallization

There has been evidence from literature that direct metallization onto fiber end-faces was

performed correctly in order to create metallic plasmonic nanostructures 23,73. To create the

metallic nanostructures on the fiber bundles, they were first covered with aluminum foil in order

to protect the surfaces that do not need to be modified. Next, the bundles were attached to the

mounting stage utilized in the metal evaporation as seen in Error! Reference source not found..

After attaching the fiber bundles onto the substrate holder, the metallization process started

with a 2 nm adhesive layer by using a PVD250 electron beam evaporator (Kurt J. Lesker). As seen

in Error! Reference source not found.(a), during the evaporation process the fiber bundles faced

he metal vapor source, where the plume of evaporated metal particles (evaporant) radiating from

the crucible to ensure that the bundles end faces were completely covered with the desired

materials. The deposition rate was kept constant at 0.1 nm/s at a chamber pressure of 2 × 10−5

Torr.

After the metal deposition was completed, the bundles were removed from the substrate

holder before carrying out the mechanical exfoliation shown in Error! Reference source not

ound.(b). To separate the gold nanohole array from the fiber bundle, Scotch tape was utilized. The

tape was gently pressed onto the bundle surface of the target area (over the nanohole array), and

50

as the tape is peeled off, the nanohole array along with the newly deposited metallic layers stick

to it, leaving behind an array of metallic nanopillars that can see in the SEM photos shown in

Figure 5.6. The nanohole arrays utilized in this thesis work, produced pillars of 120 nm in diameter,

periodically arranged 400 nm apart from each other, as shown in Figure 5.6(b).

Figure 5.5 Schematic illustration of the bundle metallization. (a) Schematics of the nanopillar array,

periodicity and multilayer multimaterial configuration. (b) Diagram of the evaporation process in a high

vacuum chamber. (c) Mechanical exfoliation to remove gold nanohole array film.

51

5.3 Optical Characterization of Multifunctional Fibers

Among numerous optical sensing platforms, multifunctional optical fibers serve as a

versatile platform due to their advantages of lightweight, small size, cost effectiveness, flexibility

and robustness. However, in most cases, these multifunctional, multi-material optical fibers are

polymer-based devices which do not have the extraordinary optical transmission properties of

silica. Polymer fibers have larger core diameter, larger attenuation and limited bandwidth

compared to conventional silica fibers 78. In this section, a comprehensive study of the optical

properties of multifunctional fibers will be explained. From fiber attenuation to sensing

characteristics of surface modified fibers such as refractive index sensing and surface enhanced

Raman spectroscopy.

5.3.1 Spectral Attenuation in Transmission Fibers

It has been observed that some polymer fibers have a better performance in the visible

wavelength spectra ( < 1300 nm), whereas silica fibers show the lowest attenuation in the infrared

( = 1500 nm). In order to better understand how the fabricated multifunctional fibers perform, in

Figure 5.6 SEM photo of a modified fiber cross-section. (a) Multifunctional fiber cross section photo

(100 m scale bar). (b) Zoomed in photo of the same fiber cross section (0.5 m scale bar).

52

this section, the spectral attenuation will be measured and analyzed, with special emphasis on the

absorption peaks. Attenuation, or transmission loss, is one of the most important performance

indicators of optical fibers 79. Attenuation is the main determinant of the maximum transmission

distance and maximum output power from the light source to the receiver. It is mainly caused by

absorption, scattering, and radiation of optical power throughout the length of the fiber due to

intrinsic or extrinsic contributors. Attenuation can be defined as the ratio of the input power to the

output power. The output power decreases exponentially with distance, as light travels along the

fiber. Therefore, attenuation has units of decibels per distance (usually kilometers), and can be

calculated using the following equation:

𝛼 = − 10

𝐿 𝑙𝑜𝑔10 (

𝑃𝑜𝑢𝑡

𝑃𝑖𝑛)

Where is the total attenuation, Pin is the input optical power into the fiber, Pout is the

output optical power from the fiber, and L is the fiber length.

The measurement of the spectral attenuation of optical fibers by the cutback method has

been previously described 80. It is the most widely used, but destructive, method of measuring

attenuation, because it is fairly easy and accurate. Figure 5.7 schematically illustrates an

Figure 5.7 Illustration of the attenuation measurement test set up by the cutback technique.

53

experimental set up for measuring the attenuation by the cutback method. The optical power is

first measured at the end of the long fiber, then the fiber is cut off a few centimeters from the output

end, and the output power is again measured at the end of the shorter fiber. This step is repeated

several times in order to improve the measurements accuracy.

The measurement includes two types of multifunctional fibers, a simple polymer

waveguide and a more complex fiber with embedded electrodes. For each fiber twelve

measurements have been made for the entire visible spectra region in order to check the

reproducibility of the measurements. The different equipment utilized and fiber lengths are

summarized both in Table 5-1.

Table 5-1 Total attenuation measurements set up and equipment

Fiber Type Wavelength

Range Light Source Detector Fiber Length

Waveguide 300 nm - 1700 nm Ando aq-4303b Ando aq-6315A 100 cm – 25 cm

Multifunctional 300 nm - 1700 nm Ando aq-4303b Ando aq-6315A 100 cm – 25 cm

The fibers were connected on one end to the Ando white light source and on the other end

to the Ando optical spectrum analyzer. The spectral data was then retrieved using a Matlab code.

By using the same ferrules over all the measurements, the coupling losses associated with them

can be neglected from the attenuation calculations. Using the attenuation formula mentioned

earlier, the attenuation of both the simple waveguide and the polymer multifunctional fiber with

electrodes were calculated and are shown below in Figure 5.8

Rayleigh scattering losses dominate at shorter wavelengths whereas infrared vibrational

absorptions and waveguide dependent losses such as micro and macro bend losses, dominate at

higher wavelengths. As seen in Figure 5.8, the absorption peaks of these two fibers occur at similar

54

wavelengths, first at around 425 nm, then at 1200 nm, and finally at around 1450 nm. Since the

testing set up was the same for both fibers at all lengths, bending losses associated with the high

absorption peaks should not be considered. Therefore, all these absorption suggest high attenuation

due to absorptions caused by material contamination during the consolidation process. Table 5-2

shown below, lists the parameters describing the absorption bands found in the two studied fibers,

in the wavelength range from 300 nm to 1600 nm.

Table 5-2 Center wavelengths and peak intensities of absorption band found in polymer optical fibers.

Fiber

425 nm 1200 nm 1450 nm

Wavelength

(nm)

Loss

(db/cm)

Wavelength

(nm)

Loss

(db/cm)

Wavelength

(nm)

Loss

(db/cm)

1 434.85 5.45 1188.85 3.22 1457.10 5.63

2 406.50 3.63 1191.70 3.26 1428.30 5.10

200 400 600 800 1000 1200 1400 1600

-1

0

1

2

3

4

5

6

Loss (

db/c

m)

Wavelength (nm)

Waveguide

Multifunctional

Polymer Fibers Attenuation Plots

Figure 5.8 Calculated total attenuation for high loss polymer optical fibers.

55

5.3.2 Refractive Index Sensing

Refractive index is a material property that describes the linear response of a medium to an

applied electromagnetic field, typically in the form of an optical wave 81. It is the ratio of the phase

velocity of light in vacuum to that in the medium. The refractive index of a medium is dependent

on the materials, temperature, pressure, and stress. This allows for an easy translation of a change

in refractive index into one of these properties. Therefore, by measuring the change in refractive

index, a change in one of these properties can be measured as long as the remaining properties are

kept constant. Consequently, a device that measures the refractive index is called a refractive index

sensor. This thesis work focuses on integrating plasmonic nanostructures onto a non-conventional

fibers end-faces. And being able to sense refractive index changes in the media surrounding the

fiber tip, is a way to prove the effectiveness of these devices.

Figure 5.9 Schematic of the measurement set up utilized to record the transmission spectra at normal

incidence, to obtain refractive index change data.

56

Figure 5.9 shows the schematic of the test set up for transmission measurement at normal

incidence. A halogen light source was utilized to illuminate the nano-plasmonic fiber tip through

a microscope objective (20X, NA = 0.42) using the inverted microscope configuration of an

existing microscope (Alpha300 SR, WITec Raman Imaging system).

The transmitted light was collected under normal excitation at the end of the fiber sensor

with a fiber-coupled spectrometer (Flame, Ocean Optics). To examine the sensitivity of the

plasmonic nanostructures deposited onto the fiber tips to changes in refractive indices, optical

transmission spectra were measured as the sensor tip was immersed in different refractive index

matching oils (Cargille), ranging from 1.30 to 1.38.

Refractive index sensing measurements were repeated several times per fiber, and both

modified polymer fibers were tested. A comprehensive review of the results will be explained next.

To verify the repeatability of the sensor response to external refractive index change,

transmission-mode measurements were performed using 10 different fiber samples. The order that

the matching refractive index oils were utilized was arbitrary, and ethanol was used to rinse the

sensor tip and Petri dish; these steps were repeated until all measurements were completed. Figure

5.10 shows the normalized experimental transmission spectra of a periodic nanostructure array on

a multifunctional polymer fiber exposed to different refractive index matching oils.

57

When utilizing optical fibers as sensing platforms, there can be losses and other optical

phenomena introduced by the fiber itself, and not by the designed sensor. To be able to normalize

the transmission data, the previously mentioned experiments were carried out with the modified

optical fibers and with an unmodified optical fiber as well. The following equation was used to

normalize the transmission spectra

𝐼′(𝜆) = 𝐼2(𝜆)

𝐼1(𝜆)

Were 𝐼′(𝜆) is the normalized intensity, 𝐼1(𝜆) is the intensity of the bare fiber, and 𝐼2(𝜆) is

the intensity of the modified fiber.

Figure 5.10 Transmission spectra (normalized) obtained through experiments from a multifunctional

fiber with plasmonic nanostructures on its tip.

58

Different peak tracking methods such as direct methods and fitting methods have been

previously explored to characterize refractive index sensors 82,83. Direct methods perform peak

detection on the spectrum by means of direct analysis of the spectrum 84. Whereas fitting methods

perform an interpolation of the spectrum with an analytical function (polynomial, Gaussian,

spline), which is then further processed to obtain the peak position. These methods can be applied

to any measured spectrum in case of low-wavelength resolution. In order to obtain smoother

spectra and to better resolve the peak location, the curve, Gaussian-fitting method was

implemented in this work. More specifically, the curve-fitting toolbox was utilized (OriginLab

Corporation). A fitted curve can be seen in Figure 5.11.

The sensing principle of plasmonic sensing devices depends on the SPR sensitivity to the

refractive index change surrounding the sensor’s tip. Figure 5.11 shows the optical transmission

spectra to the polymer non-conventional fiber. Each curve was obtained by recording the

transmission spectra one time and then fitted to a Gaussian curve. From the plot it can be observed

Figure 5.11 Gaussian-fitted transmission intensity spectra.

59

that as the refractive index increases, the peak location red shifts. These spectral shifts arise from

the surface plasmons at the interface between the nano-pillar array and the surrounding media.

To better understand the sensing performance, the sensor sensitivity and resolution will be

introduced in this section, and different definitions of figures of merit will be discussed. A

refractive index sensor is based on measuring the change of an output quantity (wavelength), which

is induced by an input quantity of interest, in this case the refractive index of the media. The

sensitivity of a refractive index sensor can then be defined as the slope of the sensor calibration

curve:

𝑆𝜆 = 𝜕𝜆

𝜕𝑛

Where 𝑆𝜆 is the sensor’s sensitivity, 𝜕𝜆 is the wavelength shift, and 𝜕𝑛 is the change in the

refractive index of the surrounding media. Accordingly, the average sensitivity of the characterized

sensors was measured and it is shown in Figure 5.12. On the other hand, the resolution of a sensor

in terms of 𝑛 is defined as the smallest detectable change of the measured quantity. Expressing this

resolution in terms of the output quantity , which is detected with an uncertainty 𝜎𝜆, the limit of

detection can be expressed as:

𝜎𝑛 = 𝜎𝜆

𝑆𝜆

Thus, the resolution is highly dependent on the noise properties of the wavelength.

60

In order to calculate the uncertainty of the sensor, the uncertainty of the wavelength must

be first found. An easy but reliable method to achieve so, is by calculating the uncertainty in the

slope of a graph. For this, the maximum and minimum slopes of the data need to be found. Table

5-3 shows the slopes measured using different sensors, and based on the results, the minimum and

maximum slopes are 67.5 and 85.7 nm/RIU respectively. After plugging in these values into the

resolution formula, the resolution was found to be 0.12 nm/RIU.

Table 5-3 Measured and calculated refractive index sensing slopes

Device Slope

Fiber 1 81.3

Fiber 2 72.0

Fiber 3 73.3

Fiber4 68.7

Fiber 5 67.5

Fiber 6 85.7

Fiber 7 82.6

Figure 5.12 Refractive index sensitivity measurements of the fabricated nano-plasmonic sensors.

61

5.3.3 Surface Enhanced Raman Spectroscopy

The surface enhanced Raman spectroscopy (SERS) effect was first discovered in 1974 by

Fleischmann, Hendra and Mcquillan.85. This group of researchers discovered an anomalously large

enhancement of the Raman signal of pyridine in the presence of a roughened silver electrode. Since

then, SERS has been extended to other metals such as gold, copper, and platinum; promoting

advances in plasmonic research as well. However, while SERS has become a large and extremely

active field of enquiry, there still remain basic questions as to the exact details of its mechanism

and its magnitude. In general, two broad classes of enhancement mechanisms have been proposed,

electromagnetic and chemical, with the electromagnetic enhancement playing a more important

role than the chemical counterpart.

The electromagnetic enhancement can basically be viewed as a redistribution of the

electromagnetic field around the SERS substrate, resulting in strongly localized regions (hot spots)

of high field intensity. This effect is mediated through resonance of the light with the surface

plasmons of the metal, with the enhancement exponentially decreasing away from the substrate.

For practical applications of SERS substrates, the sensitivity of planar substrates is considered to

be modest, due to the limited concentration of hot spots available within the laser-activated

footprint 86,87. In contrast, 3D substrates show a great potential for increasing the level of

enhancement for SERS detection. By extending the sensing device into a third dimension, a much

greater are for particle coverage is achieved, compare to two-dimensional substrates, providing

more opportunities for the hot-spots to interact with the light beams. As a result, 3D plasmonic

nanostructures were fabricated on the tips of the fiber-based sensors presented in this thesis.

In order to provide a better understanding of the performance of the plasmonic

nanostructures fabricated on fiber tips described in this work, it is important that common, standard

62

Raman analytes are used for initial verification of the sensor function. These molecules are usually

fluorescent dyes or strongly binding small molecules. Researchers often use benzenethiol (BZT)

as an alternative because it has a distinct Raman spectrum, has no innate chemical resonance, and

can strongly bind to metallic nanostructure surfaces, thanks to the thiol-metal interaction 88. This

Raman analyte provides a foundation for the description of a substrate’s enhancement properties

that can be universally understood and compared across the field of SERS and nano-plasmonics

research, and are therefore the basis for these tests.

Confocal Raman microscopy was utilized to study the plasmonic enhancement behavior of

the plasmonic nanostructures described in this work. Raman microscopy relies on vibrational

spectroscopy, which can provide chemical composition, structure of the material by monitoring

the frequency shifts between excitation laser and scattered light. It has therefore the potential to be

Figure 5.13 Schematics of a confocal Raman microscope (WITec Alpha 300 SR) system.

63

one of the most important tools for characterizing and sensing biological, environmental, and

chemical targets, primarily due to its non-destructive working principle. As seen in Error!

eference source not found. a WITec (Alpha 300 SR) confocal Raman microscope equipped with

a laser diode (785 nm) was employed for spectrospic analysis of the various multifunctional fibers,

as well as bulk analyte reference spectra. Focusing of the confocal microscope was performed with

a 20X objective lens.

To evaluate the SERS activity of the multifunctional fiber sensors, 10-3 M ethanolic

solution of BZT was incubated on each substrate for 24 hours. As mentioned before, and excitation

wavelength of 785 nm was employed during Raman measurements. Figure 5.14 shows the SERS

spectra of BZT adsorbed on the fiber tips hosting the plasmonic nanostructures. As it can be

Figure 5.14 SERS spectra of an unmodified fiber and a modified fiber incubated in 10-3 BZT.

64

observed, the SERS activity of the unmodified substrate is negligible, hence, showing the

dependence on the nanostructures.

When analyte molecules interact with light, they vibrate and produce inellastically-

scattered photons with spectra uniquely determined by the composition and structure of the

molecules. Raman scattering from these molecules is weak, and signals are undetectable from bare

polymer fibers. And as seen in Figure 5.14, SERS plasmonic nanostructures act as antennas and

utilize surface plasmons to significantly enhance the weak signals several orders of magnitude

generated by the analytes on the surface. The use of the uniform and repeating pattern of these

nanostructures, act as Raman enhancing sites, enabling the calculation of SERS enhancement

factor calculation 89.

The geometry of these plasmonic nanostructures can be designed to oscillate resonantly

when illuminated with particular frequencies of light. Localized surface plasmon resonances

(LSPR) can result in a surface charge distribution across the nanostructures that are similar to an

oscillating dipole. When two of these nanostructures are placed near one another and are then

illuminated, they can act as a pair of coupled dipoles. This field enhancement between the

plasmonic nanostructures increases relative to the single dipole case, resulting in enhancement

sites or hot spots.

The level of enhancement, or enhancement factor, varies with many factors, including the

shape and size of the nanostructures, the periodicity of such plasmonic structures, the type of

Raman analyte, and the properties of the incident light 90. Raman enhancement factor was

estimated for the BZT-incubated sensors explored in this work, following usual procedures

reported earlier 89–91. The average SERS enhancement factor of the deposited nano-plasmonic

array illuminated externally was calculated using the following equation:

65

𝐸𝐹 = (𝐼𝑆𝐸𝑅𝑆

𝑁𝑆𝐸𝑅𝑆) (

𝑁𝑅𝑎𝑚𝑎𝑛

𝐼𝑅𝑎𝑚𝑎𝑛)

Where 𝐼𝑆𝐸𝑅𝑆 is the height of the SERS peak measured after the substrate is was incubated

with BZT, 𝐼𝑅𝑎𝑚𝑎𝑛 is the height of the same Raman peak measured with a sample of liquid BZT

𝑁𝑆𝐸𝑅𝑆 is the number of BZT molecules contributing to the SERS signal of the array, and 𝑁𝑅𝑎𝑚𝑎𝑛 is

the number of molecules contributing to the BZT signal.

As mentioned before, 𝐼𝑆𝐸𝑅𝑆 and, 𝐼𝑅𝑎𝑚𝑎𝑛 are the heights of Raman bands of BZT from

spectra taken over a 5-second integration time over a 10 by 10 pixels scanned area that covered 25

um, while 1 mW of power focused onto the sample. The heights of the Raman peaks were

measured from the non-zero baseline of collected spectra, and five different areas per substrate

were examined to more accurately determine the overall enhancement factor. 𝑁𝑆𝐸𝑅𝑆 and

𝑁𝑅𝑎𝑚𝑎𝑛were calculated employing previously outlined methodology 91, in which 𝑁𝑆𝐸𝑅𝑆 is defined

as:

𝑁𝑆𝐸𝑅𝑆 = 𝑆𝐴 × 𝜌𝑠𝑢𝑟𝑓𝑎𝑐𝑒

Where SA is the fraction of illuminated surface area containing BZT molecules that

contribute to the Raman signal, and 𝜌𝑠𝑢𝑟𝑓𝑎𝑐𝑒 is the packing density of absorbed BZT molecules.

The value used for 𝜌𝑠𝑢𝑟𝑓𝑎𝑐𝑒 was 6.8 x 1014 molecules/cm2. As explained on the Smythe et al. paper,

this is the largest reported packing density of BZT. Therefore, this would produce the smallest

calculated value of enhancement factor. To determine SA, the number of structures in the

illuminated area was first determined. The lens focused to a spot about 10 um in diameter. This

circumference was then divided up into quarters and the approximated number of nanostructures

was calculated with the following equation:

66

𝑁 = 4 × {∑[√𝑅2 − (𝑝𝑖𝑡𝑐ℎ × 𝑖)2 − 𝑟

𝑝𝑖𝑡𝑐ℎ]

𝑎

𝑖=1

} + (4 × 𝑎) + 1

In this equation, R is the radius of the focused illuminated spot, the pitch is the periodicity

of the nanostructures, 400 nm, and r is the radius of the nanostructures, in this case, the diameter

of the nanopillars was 120 nm. These dimensions can be seen in Figure 5.15. In the above equation,

𝑎 is the number of nanopillars from the center to the edge of the illuminated area, and it can be

obtained with the following equation:𝑎 = (𝑅 𝑝𝑖𝑡𝑐ℎ⁄ ) − 1.

Using the above equations, the number of nanostructures covered by the illuminated area

can be approximated to be 49250. It is important to disclose that this is an approximation, where

it was assumed that the center of the lens was coincident with the center of one of the nanopillars

and only fully covered nanopillars were considered in this approximation. In other words, any

partially covered nanopillars were considered as nonexistent.

Continuing with the calculations of SA, the surface area containing Raman active

molecules can be obtained with the following equation:

Figure 5.15 Enhancement factor calculation. (a) Quarter section of the focused illuminated area. (b) Side

view of the deposited plasmonic nanostructures. The surface area of interest is highlighted in orange.

67

𝑆𝐴 = 𝑁 × (2𝜋𝑟ℎ + 𝜋𝑟2)

Where h is the height of the nanopillars, 150 nm as seen in Figure 5.15. This was used to

determine 𝑁𝑆𝐸𝑅𝑆 = 2.27 x 1010.

On the other hand, 𝑁𝑅𝑎𝑚𝑎𝑛 is given by:

𝑁𝑅𝑎𝑚𝑎𝑛 = 𝐴 × 𝑑 × 𝜌𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛

Where A is the area of the focused illuminated beam, in this case with radius r = 50 um, d

is the effective depth of resolution containing molecules contributing to the Raman signal, and

𝜌𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛 is the density of the Raman active molecule solution. The effective depth of solution

refers to the depth of effective cylindrical focal volume in solution containing molecules that

contribute to the Raman signal and it was calculated to be 23.11 um 91. The density of BZT was

𝜌𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛 = 5.9 x 1021 molecules/cm3 (Sigma Aldrich). The number of BZT molecules contributing

to the Raman signal was found to be 𝑁𝑅𝑎𝑚𝑎𝑛 = 1.07 𝑥 1015. The enhancement factor of the

devices was calculated at 1090 cm-1 and it was approximately 8.30 x 10 5. This number represents

the magnitude of enhancement factor calculated over five different areas on each device, rather

than a single spot.

5.4 Electrical Characterization of Multifunctional Fibers

The use of nanomaterials in biosensors has been increasingly attractive in recent years.

Nanomaterials can improve the detection limit and selectivity of biosensors. Metallic

nanostructures and nanoparticles, graphene, and self-assembled monolayers have been explored

for this purpose and reported in literature 92,93. Enzymes, as well as other common sensing elements

for biosensors, show increased resistance against elevated temperature and pH when they are

68

immobilized on nanomaterials. And commonly, these nanostructures are used as sensing elements,

or incorporated with receptors in electrochemical or optical sensors 94. Among various

electrochemical techniques utilized to characterize such sensors, electrochemical impedance

spectroscopy (EIS) is a well-known powerful tool, and it was utilized in this work for sensor

characterization.

Electrochemical impedance spectroscopy (EIS) is a technique that has been used for

electrochemical characterization of various surfaces and functionalized electrodes. The excitation

signal in EIS is a sinewave voltage with a variable frequency, and the response to the excitation

signal is a sinewave current with a phase angle. Impedance at each frequency is calculated from

the voltage and current data

To explore the possibility of this surface modification method to enhance the electrical

properties of embedded electrodes in multifunctional fibers, their electrochemical characteristics

were evaluated via EIS (Interface 1000E, Gamry Instruments). Measurements taken, adopted the

schemes of a two electrode set-up, which consisted of a 2 cm long fiber with plasmonic

nanoparticles surface modification or unmodified fiber, and a platinum wire as a counter electrode.

A 1X phosphate buffered saline (PBS) solution (Fisher BP661-10) was used as the electrolyte. EIS

measurements were performed in a frequency range of 1 -100,000 Hz with an alternating current

(ac) voltage of 10 mV.

69

6. Results and Discussion

6.1 Introduction

Surface plasmon-based sensing is historically one of the first major application of nano-

plasmonics 95. The wavevector and wavelength at which surface plasmon resonance occurs, are

strongly dependent on the permittivity of the dielectric half-space. Thus, precise measurements of

the previous quantities can be used for detecting small changes of the refractive index of the

dielectric. Historically, most plasmonic nanostructures have been used for refractive index sensing,

but more recently, these sensing devices have been incorporated as sensing platforms. And when

incorporated onto an optical fiber platform, a very powerful device can be created.

In the work presented in this thesis, the optical and electrical behavior of multimaterial

multifunctional fibers coupled with plasmonic nanostructures deposited on their tips. In previous

chapters, the essential theory behind light propagating inside an optical fiber and nano-plasmonics

was thoroughly explained, as well as the reliability of using FDTD method to model and predict

the behavior of various plasmonic nanostructures. By combing these nanostructures with optical

fibers, the light propagating through the fiber core interacts with any liquid or material surrounding

the fiber tip. This sensing platform showed a characteristic change in spectral output as a

consequence of different refractive indices. This property could be potentially used for analyte

detection and several other biomedical applications.

This chapter summarizes the results obtained in Chapter 5 and compares them to results

obtained through FDTD simulations to establish the validity of the fabricated sensors. Moreover,

a technique to improve the overall performance and sensitivity of the fabricated devices was also

explored. The results obtained are also and compared to the previously measured devices.

70

6.2 Optical Properties

The transmission measurements performed and demonstrated in Chapter 5 show a redshift

in the spectra due to an increase in the refractive index of the media surrounding the sensors’ tips.

Additionally, with the results obtained in these tests two figures of merit were calculated in order

to better compare the performance of the sensors developed in this work with that of similar

devices that have been previously reported. The key observation from these measurements is

shown in Figure 5.12 and it is the average sensitivity of the devices, calculated to be 75.9 mm/RIU.

While the experiments reveal interesting phenomena of the transmitted light, they only

allow to capture the transmitted spectra after travelling through a high loss polymer fiber. To

confirm the experimental results, several simulations were performed in order to capture the results

obtained in chapter 5. The FDTD simulations were performed in Lumerical (FDTD Solutions TM).

Figure 6.1 Screen shot of the Lumerical solutions user interface. A periodic nanopillars array is in the

four individual frames.

71

This software allows users to define key parameters such as mesh, source, and boundary conditions

which the software then uses to solve Maxwell’s equations throughout the mesh.

The simulation set up was very similar to the experimental set up. The incident light was a

plane wave propagating along the z-direction. Periodic boundary conditions were implemented on

the sides and perfectly matched layers were used to eliminate reflections at the upper and lower

surfaces. A single, periodic nanostructure was created for this simulation and a screenshot of the

user interface is shown in Figure 6.1. In this model, the refractive index of the surrounding media

was swept from 1.33 to 1.43 in increments of 0.2; very similar to the experimental results. Built in

properties of for gold and silver (Palik) were used. For the substrate material, polycarbonate, the

attenuation data obtained in Chapter 5 was utilized to obtain the imaginary part of the refractive

index dependent on wavelength, and 1.56 was used for the real part of the refractive index. Below,

Table 6-1 summarizes the key parameters needed to create this simulation in Lumerical FDTD

software:

Table 6-1 Lumerical FDTD simulation parameters

Parameter in Lumerical FDTD Parameter Value/Description

Source: Wavelength Plane wave, 350 nm to 2500 nm

Source: Geometry Incident at 0°, located at z = 400 nm

Mesh Size 2 nm in all x, y , and z directions

Media Refractive Index 1.33 to 1.43 (Depending on simulation)

Boundary Conditions Periodic, PML at z-min and z-max

Monitors 3 monitors located at z1 = 34 nm, z2 = 73 nm, z3 = 114 nm

Nanostructure: Materials Au: Palik for the nanopillars, Ag: Palik for the gap material

Substrate: Material Polycarbonate [Re]Index: 1.56 96, [Im]Index: experimental

Substrate: Geometry Thickness: 50 nm

72

The simulation performed aimed to replicate the experimental transmission measurements.

Using the parameters outlined in Table 6-1 the transmission spectra was obtained and compared

to the experimental results to compare the consistency between the experimental and the simulated

data. Figure 6.2 shows how the transmission spectra undergo a red shift as the refractive index of

the surrounding media increases in both the experimental and simulated results. However, it can

also be observed that the shift is more dramatic in Figure 6.2(b), corresponding to the simulation

results. The sensitivity of the simulated device was calculated to be 242 nm/RIU, which is three

times larger than that of the experimental results.

This decrease in performance could be caused by two different properties of the fabricated

devices that cannot be taken into account on the simulations. First, the coverage and integrity of

the plasmonic nanostructures is not flawless as modelled in the simulations. With this in mind,

micro- and nano-folds can arise during the transfer of the nanohole array onto the fiber bundle,

creating an array that is not evenly spaced or where single nano-pillars are missing. In addition,

Figure 6.2 Transmission spectra, refractive index vs. wavelength. (a) Color plot of the experimental

transmission spectra through the multimaterial fiber. (b) Color plot of the simulated transmission spectra

obtained through FDTD.

73

shadowing effect arises during the metallic deposition 97, making the nano-pillars look more like

nano-cones.

Another difference between the simulation set up and the actual measurements, is the

thickness of the substrate. As described in Chapter 5, the attenuation of the fiber substrate is very

high, and it can decrease and distort the transmission signal acquired at the detector. Due to

limitations in the FDTD software, the height of the simulated substrate is very small compared to

the length of the multimaterial optical fiber. In order to test the validity of the previous statement,

three simulations were performed where the only parameter changed was the thickness of the

substrate. The refractive index of the media was set to be 1 (air), and the thickness of the substrate

was increased from 50 nm, to 100 nm, and to 150 nm. The results are shown in Figure 6.3, where

the discrepancies between each spectra are very obvious, even though the difference in the

substrate thickness is either 50 nm or 100 nm. It is expected that the spectra from a 50 cm substrate

would be dramatically altered, supporting the experimental results.

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

0.0

0.2

0.4

0.6

0.8

1.0

Tra

nsm

issio

n

Wavelength (nm)

50 nm

100 nm

150 nm

Figure 6.3 Graph of the transmission spectra of different substrate thicknesses.

74

6.3 Optimization of the Plasmonic Nanostructure

One of the key issues in the field of SPR-based sensing is to find different ways to improve

the sensitivity and limit of detection while maintaining the resonance properties of the sensor. As

mentioned in previous chapters, the optical properties of SPPs, such as resonance wavelength and

enhancement factor of electric field are highly dependent on geometric parameters of the metallic

and dielectric materials. In particular, among the various designs of plasmonic nanostructures

consisting of metallic/insulator configurations, adjacent nanoscale gaps have shown strong field

confinement and enhancement in the gap regions due to the in-plane near-field coupling across the

gaps 98,99.

Recently, new nano-plasmonic configurations known as metal-insulator-metal (MIM)

structures have been studied for nano-antenna applications 100. The out-of-plane near-field

coupling between metallic films separated by a dielectric spacer, confines light in the form of SPPs

along the metallic surfaces, enhancing the near-field intensity 101.

In order to achieve similar properties to MIM configurations, structural optimization of the

current nano-pillar arrays was employed with the intention of further enhancing the concentrated

field. This was performed by etching the silver layers with chrome etchant 1020 (Fisher Scientific).

Silver has been found to be incompatible with this etchant. However, its etch-rate is still unknown.

With this in mind, in order to perform the etching following a conservative approach, the chrome

etchant 1020 was diluted with deionized water (100:1). Then, the fiber tips were submerged in the

diluted etchant solution for 20 seconds and rinsed with more deionized water. Both refractive index

measurements and SERS experiments were performed using these fibers as previously performed

on modified fibers and described in chapter 5.

75

First, refractive index measurements were performed using the modified and then etched

fibers, following the procedure previously outlined. The average sensitivity or the slope of the

wavelength/refractive index change curve is shown in Figure 6.4. The average sensitivity of the

etched devices was calculated to be 121.8 nm/RIU, improving their sensitivity by 60% compared

to the devices described in chapter 5. In the same way, the resolution of the newly etched devices

was calculated as 0.09 nm/RIU.

In the same way, FDTD simulations were performed to confirm the experimental results.

The same procedures previously explained in this chapter were followed to obtain such results.

However, the etching depth of the silver layers was arbitrarily selected, since the devices had not

been characterized through SEM images, the color plot is shown in Figure 6.5. As expected, the

experimental and simulation results obtained for both etched and un-etched devices, show the same

Figure 6.4 Box plot of the refractive index measurements of the optimized nano-plasmonic fiber sensors.

76

red-shift trend. To quantitatively compare the trends of the modified devices and the optimized

devices, the modeled and experimental sensitivities were calculated and are shown in Table 6-2.

Table 6-2 Summary of average sensitivities of experimental and simulation results.

Experimental Simulation

Modified Fiber 75.9 nm/RIU 242.5 nm/RIU

Etched Fiber 121.8 nm RIU 322.5 nm/RIU

These results show an overall improvement of the sensors’ performance after etching.

Therefore, it can be hypothesized that the SERS results would improve as well. To evaluate the

performance of the etched devices, the same methodology followed in chapter 5 was implemented

one more time. The fibers were incubated in 10-3 M ethanolic solution of BZT for 24 hours and

then Raman measurements were performed with a 785 nm laser light source. The enhancement

factor was also calculated in order to quantify the results obtained with the new fibers and the

Figure 6.5 Refractive index vs. wavelength, color plot of the simulated transmission spectra of the etched

devices obtained through FDTD.

77

compare them to the un-etched fibers. The average enhancement factor of the etched fibers was

calculated to be 1.12x 106, this is a 36% improvement compared to the un-etched fibers. The

statistical analysis of the SERS enhancement factor results of the modified fibers, both etched and

un-etched is shown below in Table 6-3.

Table 6-3 Enhancement factor distribution of tested fibers at maximum peak wavelength of 1090 nm.

Modified Fibers Modified Etched Fibers

Enhancement

Factor

Standard

Deviation

Enhancement

Factor

Standard

Deviation

Fiber 1A 8.62E+05 3.06E+05

Fiber 1B 1.49E+06 3.58E+05

Fiber 2A 1.49E+06 3.58E+05

Fiber 2B 6.29E+05 2.82E+05

Fiber 3A 5.68E+05 1.19E+05

Fiber 3B 1.62E+06 2.39E+05

Fiber 4A 6.62E+05 1.27E+05

Fiber 4B 1.06E+06 3.02E+05

Fiber 5A 5.65E+05 1.46E+05

Fiber 5B 8.16E+05 1.85E+05

In this section, optimization of the optical fiber devices sensitivity was achieved by etching

part of the silver layers with chrome etchant in order to create air gaps between the gold layers.

His observation indicates that, despite the fact that the etch depth or gap values were not known,

all the optical measurements were consistent showing an improvement in both the refractive index

sensitivity and SERS enhancement factor with the presence of the gap between the gold layers. As

a result, this new configuration brings the opportunity to find the optimal etching time and etchant

dilution to ultimately improve the optical capabilities of the fiber based plasmonic nanostructures

sensors.

78

The interactions and couplings of plasmonic nanostructures and light have been discussed

in previous chapters. As a group of these nanostructures are brought close enough, a remarkable

and highly interesting feature occurs where a region of extremely large electric field, previously

referred as hot spot, is generated. Only when the out-of-plane near-field coupling between metallic

films, separated by a dielectric gaps, confines light in the form of SPPs an extremely enhanced

electric field higher than the un-etched plasmonic nanostructures. It is important to note that this

field enhancement is highly dependent on the configuration, both depth and thickness, of the

dielectric gap between metallic films.

These are so called gap modes, also present in MIM and IMI structures, where the high

energy or the hot spots are confined in the dielectric layer. This gap mode is also highly dependent

on the nature of the dielectric material, in this case air. The high enhancement of the

electromagnetic field and the generation of the hot spots seem very appealing to improve SERS

measurements. Furthermore, this intense local field region leads to a strong coupling to anything

trapped in the gap. This makes the etched pillar nanostructures excellent antennas for coupling

light into and out of localized emitters 102. When the material in the gap changes, spectral shifts in

the plasmon resonance frequency occurs, making plasmonic nanostructures highly sensitive and

therefore, desirable for chemical detection. Finally, the resonant wavelength highly depends on the

distance separation between the nanostructures, and it can be used to tune plasmonic devices to

work at a certain frequency.

79

7. Conclusions and Future Outlook

This thesis focused on two important aspects of surface plasmon resonance sensing:

theoretical analysis and sensor design and fabrication. A performance characterization and analysis

methodology was proposed and implemented, then the plasmonic optical fiber-based sensors were

functionalized and refractive index change tests and SERS measurements were completed.

Furthermore, the same characterization tests were performed after etching of the silver layers that

served to optimize the sensitivity of the sensors. A summary of this thesis will be presented in this

chapter, followed by the scientific contributions and future directions to be followed by the

research group.

7.1 Summary and Conclusions

The heart of this work consisted on the development of plasmon-based optical fiber probes

that integrated unconventional multimaterial multifunctional fibers and state-of-the-art techniques

to transfer nanostructures onto their tips. This new fabrication technique enabled the integration of

nano-plasmonic properties into fiber-based devices that already had unique optical and electrical

functionalities to be used in several different applications, but with a focus on biomedical

applications.

Theoretical considerations combined with a constant improvement of the bundle

fabrication technique enabled the transfer and fabrication of well-controlled plasmonic

nanostructures, and allowed to go from single-fiber to multi-fiber surface modification, which has

not seen in literature before. The combined efforts of two research groups resulted in plasmonic-

based multimaterial fiber probes with unprecedented performance as refractive index sensors and

SERS probes, with combined electrical functionalities.

80

Several advanced methods for controlling the fabrication of nanostructures were described

early in this thesis. They were then put to use for the fabrication of plasmonic nanostructures onto

multimaterial multifunctional fiber tips. First, by creating a nano-hole array that was then

transferred and used as a pattern to create multimaterial nanopillars that served to functionalize

previously fabricated polymer fibers, which were finally utilized as plasmon-based refractive

index sensors and as SERS probes.

The interactions between dielectric and metallic surface optical structures for the

manipulation of propagating surface plasmon polaritons were presented. Surface plasmons are

very sensitive to the dielectric properties near metal surfaces, and their refractive index can

modulate the high-concentrated electromagnetic fields generated by SPR. This in turn, allows to

monitor any dielectric refractive index changes, making the fabricated nano-plasmonic probes very

attractive chemical and biomedical sensors. To validate the results, this study considered both

experimental data from the transmission spectra of light travelling through the fiber probes and

FDTD simulated results of the transmission spectra of a similar substrate with periodic plasmonic

nanostructures on its surface.

The use of a reliable and consistent platform, combined with plasmonic hot spots composed

of noble metal nanostructures incubated in an extremely selective analyte allowed for the design

and development of highly enhancing and cost efficient SERS probes. In addition, the substrates

implemented in these sensing probes were biocompatible, making them very attractive and very

likely to transition into the field of biomedical research and diagnosis. This work demonstrated the

high SERS enhancement factors that can be achieved using an array of plasmonic nanostructures

to detect a well-known SERS analyte, BZT.

81

The optimization of the fabricated devices was achieved by etching the silver layers in

between the gold layers of every single nanostructure with chrome etchant. Since the etch rate of

silver immersed in chrome etchant is unknown, the depth of material etched was arbitrary.

However, the creation of this dielectric (air) gap between the gold layers allowed for the creation

of highly localized hot spots. These adjacent nanoscale dielectric gaps have shown strong field

confinement and enhancement in the gap regions due to the in plane, near field coupling across

the gaps. The enhancement was characterized and observed in both experimental results and FDTD

simulations.

The optimization approach described here provides an efficient pathway for further

development of plasmonic fiber based sensing probes, which allow the detection of trace

concentrations of known Raman markers, and could potentially detect practical target molecules

with low Raman cross-sections such as explosives, chemicals, and biomarkers. This work provided

a specific design and fabrication approach, regarding substrate fabrication and surface

modification, and the results obtained were quantified by calculating several figures of merit

related to the refractive index change sensitivity and SERS enhancement factor. However,

additional work will be required in order to understand the binding mechanisms and molecular

interactions in order to use the fabricated probes for label-free sensing.

The findings in this work related to the fabrication of plasmonic probes, optical and

electromagnetic enhancement effects of the plasmonic nanostructures, and the identification of the

characteristic properties of the substrate and nanostructures that can be tailored to maximize the

sensitivity and enhancement factors may lead to significant impact in the field of SERS and optical

fiber based sensors and sensor design, and this will be described in the following section.

82

7.2 Significance and Contributions

The further development of sensor technologies will require progress in the implementation

of sensing probes that are label-free, sensitive, fast, and non-invasive. One such device can be

achieved by using optical fibers platforms, more specifically multimaterial multifunctional fibers

that allow sensing of different phenomena. Different sensing techniques such as surface enhanced

Raman scattering, which is highly advantageous due to high signal specificity, speed is very

desirable. However, this method is still in the research stage in fast-growing fields such as

biomedical, environmental and chemical detection. In order to provide the needed technological

development to establish SERS as a future sensing technique, a better understanding of its

enhancement phenomena and further integration onto a desired substrate are needed. These goals

were accomplished in the present study through a detailed analysis of the probes nanostructures,

which can potentially be manipulated to affect the electromagnetic enhancement and to work at

desired frequencies.

Material selection plays an important role in any device fabrication and this holds true for

any potential biomedical sensing platforms that need to be biocompatible, flexible and sometimes

portable in order for them to be utilized in in-vivo scenarios. In this context, the multimaterial

fibers fabricated for this work were in fact polymer-based (unconventional) fibers, which have

several advantages such as low-cost, flexibility, multi-functionalities, and reliability. However,

due to their polymeric properties, they tend to have poor selectivity with respect to several solvents

that are commonly utilized during well-known fabrication techniques to deposit metallic

nanostructures. The significance of this work is that not only it allows for both conventional silica

and multimaterial fibers to be modified, but also that several fibers can be modified during the

same process by the creation of the fiber bundles, permitting a faster and high-throughput method.

83

7.3 Future Outlooks

The different contributions made in this work will certainly leverage the research and

development of future fiber-based sensors. The plasmonic-based optical sensors developed in this

thesis were initially designed and intended to be used in biological and biomedical applications,

especially in detection and monitoring of certain biomarkers and as neural probes. For instance,

one of the main advantages of using a fiber-based sensor is that sometimes they do not need to be

illuminated externally, this is thanks to the bidirectional propagation of the exciting light that

allows for portability and remote sensing. In addition, all the materials implemented in these

devices are biocompatible, therefore they can be implemented in label-free, in-vivo biosensing.

This is a valuable tool that enables real-time signal acquisition.

These devices also take advantages of SPR and SERS properties. Biosensors based on SPR

responses provide ultrahigh sensitivity, compactness, and multiplexing capabilities, the major

drawback is the lack of molecular specificity. Since their operation completely relies on SPR

responses to the refractive index changes of the surrounding media at the metal/dielectric interface.

This type of signals are however incapable of discriminating between specific and non-specific

binding, which may result in false positives. On the other hand, SERS combines the advantage of

SPR enhancement with unique spectral features of Raman signals, to enable molecular specificity.

Finally, as multimaterial fibers enable the integration of multi-sensing capabilities in an

optical fiber platform, not only spectral analysis can be achieved. Electrical sensing capabilities

embedded in an optical fiber probe are very desirable properties of many different sensors because

light can be sent in order to collect data but also in order to excite certain phenomena. This could

have the potential to be implemented and neural probes, where brain activity can be induced by

light and this can in turn be recorded by the embedded electrodes.

84

References

1. Ritchie, R. Plasma losses by fast electrons in thin films. Phys. Rev. 106, 874–881 (1957).

2. Barnes, W. L., Dereux, A. & Ebbesen, T. W. Surface plasmon subwavelength optics.

Nature 424, 824–830 (2003).

3. Roberts, M. M. et al. Elastically relaxed free-standing strained-silicon nanomembranes.

Nat. Mater. 5, 388–393 (2006).

4. Sannomiya, T., Scholder, O., Jefimovs, K., Hafner, C. & Dahlin, A. B. Investigation of

plasmon resonances in metal films with nanohole arrays for biosensing applications. Small

7, 1653–1663 (2011).

5. Vendamme, R., Onoue, S. Y., Nakao, A. & Kunitake, T. Robust free-standing

nanomembranes of organic/inorganic interpenetrating networks. Nat. Mater. 5, 494–501

(2006).

6. Markutsya, S., Jiang, C., Pikus, Y. & Tsukruk, V. V. Freely suspended layer-by-layer

nanomembranes: Testing micromechanical properties. Adv. Funct. Mater. 15, 771–780

(2005).

7. Nagpal, P., Lindquist, N. C., Oh, S. H. & Norris, D. J. Ultrasmooth patterned metals for

plasmonics and metamaterials. Science (80-. ). 325, 594–597 (2009).

8. Jia, P., Jiang, H., Sabarinathan, J. & Yang, J. Plasmonic nanohole array sensors fabricated

by template transfer with improved optical performance. Nanotechnology 24, (2013).

9. Suzuki, H., Sugimoto, M., Matsui, Y. & Kondoh, J. Effects of gold film thickness on

spectrum profile and sensitivity of a multimode-optical-fiber SPR sensor. Sensors

Actuators, B Chem. 132, 26–33 (2008).

10. Brolo, A. G., Gordon, R., Leathem, B. & Kavanagh, K. L. Surface plasmon sensor based

on the enhanced light transmission through arrays of nanoholes in gold films. Langmuir

20, 4813–4815 (2004).

11. Lindquist, N. C., Nagpal, P., McPeak, K. M., Norris, D. J. & Oh, S. H. Engineering

85

metallic nanostructures for plasmonics and nanophotonics. Reports Prog. Phys. 75,

(2012).

12. Stewart, M. E. et al. Nanostructured plasmonic sensors. Chem. Rev. 108, 494–521 (2008).

13. Cannon, A. & Cannon, A. H. Unconventional Microfabrication Using Polymers By.

(2014).

14. Xia, Y. Soft Lithography. Angew. Chemie (International ed.) 37, (1998).

15. Chou, S. Y., Krauss, P. R. & Renstrom, P. J. Imprint Lithography with 25-Nanometer

Resolution. Science (80-. ). 272, 85–87 (2016).

16. Hecht, J. City of light: the story of fiber optics. (Oxford University Press on Demand,

2004).

17. Alexander Schmidt, M., Argyros, A. & Sorin, F. Hybrid Optical Fibers - An Innovative

Platform for In-Fiber Photonic Devices. Adv. Opt. Mater. 4, 13–36 (2016).

18. Bayandir, M. et al. Metal – insulator – semiconductor optoelectronic fibres. Nature 431,

826–829 (2004).

19. Snyder, A. W. & Love, J. Optical waveguide theory. (Springer Science & Business Media,

2012).

20. Harrick, N. J. Electric Field Strengths at Totally Reflecting Interfaces. J. Opt. Soc. Am. 55,

851–857 (1965).

21. Consales, M. et al. Lab-on-fiber technology: Toward multifunctional optical nanoprobes.

ACS Nano (2012). doi:10.1021/nn204953e

22. Lab-on-Fiber Technology. 56, (Springer International Publishing, 2015).

23. Micco, A., Ricciardi, A., Pisco, M., La Ferrara, V. & Cusano, A. Optical fiber tip

templating using direct focused ion beam milling. Sci. Rep. 5, 1–10 (2015).

24. Giaquinto, M., Ricciardi, A., Cutolo, A. & Cusano, A. Lab-on-Fiber Plasmonic Probes for

Ultrasound Detection: A Comparative Study. J. Light. Technol. 34, (2016).

25. Lipomi, D. J. et al. Patterning the tips of optical fibers with metallic nanostructures using

86

nanoskiving. Nano Lett. 11, 632–636 (2011).

26. Smythe, E. J., Dickey, M. D., Whitesides, G. M. & Capasso, F. A technique to transfer

metallic nanoscale patterns to small and non-planar surfaces. ACS Nano (2009).

doi:10.1021/nn800720r

27. Lipomi, D. J. et al. Survey of materials for nanoskiving and influence of the cutting

process on the nanostructures produced. ACS Appl. Mater. Interfaces 2, 2503–2514

(2010).

28. Liu, T., Wei, Y. & Song, G. Advances of Optical Fiber Sensors For Coal Mine Safety

Monitoring Applications. 4–8 (2013).

29. Lopez-Cardona, J. D., Vazquez, C., Sanchez Montero, D. & Lallana, P. C. Remote Optical

Powering using Fiber Optics in Hazardous Environments. J. Light. Technol. 36, 748–754

(2017).

30. Stewart, G., Jin, W. & Culshaw, B. Prospects for fibre-optic evanescent-field gas sensors

using absorption in the near-infrared. Sensors Actuators B Chem. 38, 42–47 (1997).

31. Sensors, F. C. Fiber-Optic Chemical Sensors and Fiber-Optic Bio-Sensors. 80, 25208–

25259 (2015).

32. Ferguson, J. A., Boles, T. C., Adams, C. P. & Walt, D. R. A fiber-optic DNA biosensor

microarray for the analysis of gene expression. Nat. Biotechnol. 14, 1681–1684 (1996).

33. Heijmans, J., Southern, E., Tno, C., Pieter, F. & Imec, W. 4th European Conference of the

International Federation for Medical and Biological Engineering. 22, (2009).

34. Mohan, H., Gopal & Kumar, A. Design and Analyze the Refractive Index Sensor Having

the Discontinuity between Sensing Region and Cladding Area by Large Core Diameter.

Procedia Technol. 17, 289–294 (2014).

35. Kumawat, N., Pal, P. & Varma, M. Diffractive optical analysis for refractive index

sensing using transparent phase gratings. Sci. Rep. 5, 1–10 (2015).

36. Iadicicco A., C. A. C. A. B. R. G. M. Thinned fiber Bragg gratings as high sensitivity

refractive index sensor. IEEE Photonics Technol. Lett. 16, 1149–1151 (2004).

87

37. Stokes, D. L. & Vo-Dinh, T. Development of an integrated single-fiber SERS sensor.

Sensors Actuators, B Chem. 69, 28–36 (2000).

38. Jorgenson, R. C. & Yee, S. S. A fiber-optic chemical sensor based on surface plasmon

resonance. Sensors Actuators B Chem. 12, 213–220 (1993).

39. Slavík, R., Homola, J., Tyroký, J. & Brynda, E. Novel spectral fiber optic sensor based on

surface plasmon resonance. Sensors Actuators, B Chem. 74, 106–111 (2001).

40. Wood, R. W. XXVII. Diffraction gratings with controlled groove form and abnormal

distribution of intensity. London, Edinburgh, Dublin Philos. Mag. J. Sci. 23, 310–317

(1912).

41. Lord Rayleigh, O. M., P. R. S. On the dynamical theory of gratings. Proc. R. Soc. London.

Ser. A 79, 399 LP-416 (1907).

42. Swan, J. B., Otto, A. & Fellenzer, H. Observed Retardation Effects on the Energy of the

ω+‐Surface Plasmons in Thin Aluminium Foils. Phys. status solidi 23, 171–176 (1967).

43. Kretschmann, E. & Raether, H. Radiative decay of non-radiative surface plasmons excited

by light. Z. Naturforsch. 23, 2135–2136 (1968).

44. Willets, K. A. & Van Duyne, R. P. Localized Surface Plasmon Resonance Spectroscopy

and Sensing. Annu. Rev. Phys. Chem. 58, 267–297 (2007).

45. Esteban, Ó. et al. High-sensitive SPR sensing with Indium Nitride as a dielectric overlay

of optical fibers. Sensors Actuators, B Chem. 158, 372–376 (2011).

46. Maier, S. a. Plasmonics: Fundamentals and Applications. Physics 677, (2004).

47. Ashcroft, N. W. & Mermin, N. D. Solid state physics TT -. TA - (Holt, Rinehart and

Winston,).

48. Johnson, P. B. & Christy, R. W. Optical constants of the noble metals. Phys. Rev. B 6,

4370–4379 (1972).

49. Raether, H. in Surface plasmons on smooth and rough surfaces and on gratings 4–39

(Springer, 1988).

88

50. Halas, N. J. Plasmonics: An emerging field fostered by nano letters. Nano Lett. 10, 3816–

3822 (2010).

51. Anker, J. N. et al. Biosensing with plasmonic nanosensors. Nat. Mater. 7, 442–453

(2008).

52. Jain, P. K., Huang, X., El-Sayed, I. H. & El-Sayed, M. A. ChemInform Abstract: Noble

Metals on the Nanoscale: Optical and Photothermal Properties and Some Applications in

Imaging, Sensing, Biology, and Medicine. ChemInform 40, 7–9 (2009).

53. Zhao, J., Sherry, L. J., Schatz, G. C. & Van Duyne, R. P. Molecular plasmonics:

Chromophoreplasmon coupling and single-particle nanosensors. IEEE J. Sel. Top.

Quantum Electron. 14, 1418–1429 (2008).

54. Eck, D., Helm, C. A., Wagner, N. J. & Vaynberg, K. A. ‘Plasmon Resonance

Measurements of the Adsorption and Adsorption Kinetics of a Biopolymer onto. Gold

Nanocolloids’, Langmuir 17pp, 957–960 (2001).

55. Arai, T., Kumar, P. K. R., Rockstuhl, C., Awazu, K. & Tominaga, J. An optical biosensor

based on localized surface plasmon resonance of silver nanostructured films. J. Opt. A

Pure Appl. Opt. 9, 699–703 (2007).

56. Cheng, S. F. & Chau, L. K. Colloidal gold-modified optical fiber for chemical and

biochemical sensing. Anal. Chem. 75, 16–21 (2003).

57. Ligler, F. S. & Taitt, C. R. Optical Biosensors: Today and Tomorrow. (Elsevier Science,

2011).

58. Foley, J. J. et al. When are Surface Plasmon Polaritons Excited in the Kretschmann-

Raether Configuration? Sci. Rep. 5, (2015).

59. Ritchie, R. H., Arakawa, E. T., Cowan, J. J. & Hamm, R. N. Surface-plasmon resonance

effect in grating diffraction. Phys. Rev. Lett. 21, 1530–1533 (1968).

60. Homola, J., Yee, S. S. & Gauglitz, G. Surface plasmon resonance sensors: review. Sensors

Actuators B Chem. 54, 3–15 (1999).

61. Sharma, A. K. & Gupta, B. D. Fibre-optic sensor based on surface plasmon resonance

89

with Ag-Au alloy nanoparticle films. Nanotechnology 17, 124–131 (2006).

62. Feng, D., Zhou, W., Qiao, X. & Albert, J. Compact optical fiber 3D shape sensor based on

a pair of orthogonal tilted fiber bragg gratings. Sci. Rep. 5, 1–7 (2015).

63. Yee, K. S. Numerical Solution of Initial Boundary Value Problems Involving Maxwell’s

Equations in Isotropic Media. IEEE Trans. Antennas Propag. 14, 302–307 (1966).

64. Moreno, E., Rodrigo, S. G., Bozhevolnyi, S. I., Martín-Moreno, L. & García-Vidal, F. J.

Guiding and focusing of electromagnetic fields with wedge plasmon polaritons. Phys. Rev.

Lett. 100, 1–4 (2008).

65. Poh, C.-H., Rosa, L., Juodkazis, S. & Dastoor, P. FDTD modeling to enhance the

performance of an organic solar cell embedded with gold nanoparticles. Opt. Mater.

Express 1, 1326 (2011).

66. Taflove, A. & Hagness, S. C. Computational electrodynamics: the finite-difference time-

domain method. (Artech house, 2005).

67. Calculus - Differentiation the Rate of Change. Available at:

http://www.splung.com/content/sid/1/page/differentiation. (Accessed: 3rd April 2018)

68. Gao, H., Ouyang, M., Zhou, J. & Liu, D. Vector analysis of polarization properties of

rectangle phase grating. Opt. Commun. 271, 24–29 (2007).

69. Zhang, J., Zhao, X., Suo, Z. & Jiang, H. A finite element method for transient analysis of

concurrent large deformation and mass transport in gels. J. Appl. Phys. 105, 93522 (2009).

70. Alberty, J., Carstensen, C., Funken, S. A. & Klose, R. Matlab implementation of the finite

element method in elasticity. Computing 69, 239–263 (2002).

71. Nath, N. & Chilkoti, A. Label-free biosensing by surface plasmon resonance of

nanoparticles on glass: Optimization of nanoparticle size. Anal. Chem. 76, 5370–5378

(2004).

72. Walt, D. R. Miniature Analytical Methods for Medical Diagnostics. Science (80-. ). 308,

217 LP-219 (2005).

73. Fu, Y. & Bryan, N. K. A. Investigation of physical properties of quartz after focused ion

90

beam bombardment. Appl. Phys. B 80, 581–585 (2005).

74. Vaiano, P. et al. Lab on Fiber Technology for biological sensing applications. Laser and

Photonics Reviews (2016). doi:10.1002/lpor.201600111

75. Eijkelenborg, M. A. van et al. Microstructured polymer optical fibre. Opt. Express 9, 319–

327 (2001).

76. Henzie, J., Lee, M. H. & Odom, T. W. Multiscale patterning of plasmonic metamaterials.

Nat. Nanotechnol. 2, 549–554 (2007).

77. Gao, H., Zhou, W. & Odom, T. W. Plasmoinc crystals: A platform to catalog resonances

from ultraviolet to near-infrared wavelengths in a plasmonic library. Adv. Funct. Mater.

20, 529–539 (2010).

78. Monroy, I. T. et al. Data transmission over polymer optical fibers. Opt. Fiber Technol. 9,

159–171 (2003).

79. Koike, Y. Fundamentals of Plastic Optical Fibers Polymers. (Wiley-VCH, 2015).

80. IEC. Optical Fibres: Part 1-40: Measurement Methods and Test Procedures: Attenuation.

(2001).

81. Starke, R. & Schober, G. A. H. Microscopic theory of the refractive index. Optik (Stuttg).

140, 62–85 (2017).

82. Lamberti, A., Vanlanduit, S., De Pauw, B. & Berghmans, F. Influence of fiber bragg

grating spectrum degradation on the performance of sensor interrogation algorithms.

Sensors (Switzerland) 14, 24258–24277 (2014).

83. Lee, H.-W., Park, H.-J., Lee, J.-H. & Song, M. Accuracy improvement in peak positioning

of spectrally distorted fiber Bragg grating sensors by Gaussian curve fitting. Appl. Opt. 46,

2205 (2007).

84. Tosi, D. Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating

Sensors. Sensors 17, 2368 (2017).

85. Fleischmann, M., Hendra, P. J. & McQuillan, A. J. Raman spectra of pyridine adsorbed at

a silver electrode. Chem. Phys. Lett. 26, 163–166 (1974).

91

86. Ko, H., Singamaneni, S. & Tsukruk, V. V. Nanostructured surfaces and assemblies as

SERS media. Small 4, 1576–1599 (2008).

87. Chang, S., Ko, H., Singamaneni, S., Gunawidjaja, R. & Tsukruk, V. V. Nanoporous

membranes with mixed nanoclusters for Raman-based label-free monitoring of peroxide

compounds. Anal. Chem. 81, 5740–5748 (2009).

88. Sharma, B. et al. High-performance SERS substrates: Advances and challenges. MRS

Bull. 38, 615–624 (2013).

89. Smythe, E. J. et al. Optical Antenna Arrays on a Fiber Facet for in Situ Surface-Enhanced

Raman Scattering Detection. (2009). doi:10.1021/nl803668u

90. Moskovits, M. Persistent misconceptions regarding SERS. Phys. Chem. Chem. Phys. 15,

5301 (2013).

91. Kumar, S., Cherukulappurath, S., Johnson, T. W. & Oh, S. H. Millimeter-sized suspended

plasmonic nanohole arrays for surface-tension-driven flow-through SERS. Chem. Mater.

26, 6523–6530 (2014).

92. Jeykumari, D. R. S. & Narayanan, S. S. Fabrication of bienzyme nanobiocomposite

electrode using functionalized carbon nanotubes for biosensing applications. Biosens.

Bioelectron. 23, 1686–1693 (2008).

93. Scognamiglio, V. Nanotechnology in glucose monitoring: Advances and challenges in the

last 10 years. Biosens. Bioelectron. 47, 12–25 (2013).

94. Feyzizarnagh, H. et al. Protein sensing with aptamer immobilized on an antifouling binary

self-assembled monolayer. Ind. Eng. Chem. Res. 54, 4072–4077 (2015).

95. Gordon, J. G. & Ernst, S. Surface plasmons as a probe of the electrochemical interface.

Surf. Sci. 101, 499–506 (1980).

96. Refractive index of (C16H14O3)n (Polycarbonate, PC) - Sultanova. Available at:

https://refractiveindex.info/?shelf=organic&book=polycarbonate&page=Sultanova.

(Accessed: 15th April 2018)

97. Karabacak, T. Thin-film growth dynamics with shadowing and re-emission effects. J.

92

Nanophotonics 5, 52501 (2011).

98. Sundaramurthy, A. et al. Field enhancement and gap-dependent resonance in a system of

two opposing tip-to-tip Au nanotriangles. Phys. Rev. B - Condens. Matter Mater. Phys. 72,

1–6 (2005).

99. Lin, L. & Zheng, Y. Optimizing plasmonic nanoantennas via coordinated multiple

coupling. Sci. Rep. 5, 1–11 (2015).

100. Chu, Y., Banaee, M. G. & Crozier, K. B. Double-resonance plasmon substrates for

surface-enhanced raman scattering with enhancement at excitation and stokes frequencies.

ACS Nano 4, 2804–2810 (2010).

101. Chu, Y. & Crozier, K. B. Experimental study of the interaction between localized and

propagating surface plasmons. Opt. Lett. 34, 244 (2009).

102. Prodan, E., Radloff, C., Halas, N. J. & Nordlander, P. A Hybridization Model for the

Plasmon Response of Complex Nanostructures. Science (80-. ). 302, 419–422 (2003).