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Planar Total Internal Reflection Biofouling Sensors By Koo Hyun Nam A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Engineering - Mechanical Engineering in the Graduate Division of the University of California at Berkeley Committee in charge: Professor Liwei Lin, Chair Professor Costas P. Grigoropoulos Professor Dorian Liepmann Professor Michael Maharbiz Fall 2010

Planar Total Internal Reflection Biofouling Sensors · Planar Total Internal Reflection Biofouling Sensors By Koo Hyun Nam A dissertation submitted in partial satisfaction of the

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Page 1: Planar Total Internal Reflection Biofouling Sensors · Planar Total Internal Reflection Biofouling Sensors By Koo Hyun Nam A dissertation submitted in partial satisfaction of the

Planar Total Internal Reflection Biofouling Sensors

By

Koo Hyun Nam

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy

in

Engineering - Mechanical Engineering

in the

Graduate Division

of the

University of California at Berkeley

Committee in charge:

Professor Liwei Lin, Chair

Professor Costas P. Grigoropoulos

Professor Dorian Liepmann

Professor Michael Maharbiz

Fall 2010

Page 2: Planar Total Internal Reflection Biofouling Sensors · Planar Total Internal Reflection Biofouling Sensors By Koo Hyun Nam A dissertation submitted in partial satisfaction of the

Planar Total Internal Reflection Biofouling Sensors

Copyright 2010

by

Koo Hyun Nam

Page 3: Planar Total Internal Reflection Biofouling Sensors · Planar Total Internal Reflection Biofouling Sensors By Koo Hyun Nam A dissertation submitted in partial satisfaction of the

Abstract

Planar Total Internal Reflection Biofouling Sensors

by

Koo Hyun Nam

Doctor of Philosophy in Mechanical Engineering

University of California at Berkeley

Professor Liwei Lin, Chair

Planar, integrated microscale sensors utilizing prism-coupler type angular interrogation sensing

technique have been demonstrated. The main structure of the sensor consists of an optical

prism coupled to a built-in waveguide to introduce Fraunhofer diffraction when light ray comes

into the prism from the waveguide. The Fraunhofer diffraction creates spectrum of consecutive

rays over the sensing edge of the prism such that there is no need for the bulky scanning

mechanisms typically used in other macro scale sensing systems. Two types of sensors are

presented: (1) total internal reflection based critical point detection (CPD) sensor, and (2) surface

plasmon resonance (SPR) based resonance point detection (RPD) sensor.

The CPD sensor is fabricated by a simple, two-mask process which creates a right angle prism

with three sides with lengths of 1, 0.86, and 1.33 mm, respectively in the prototype design and a

waveguide with a cross sectional area of 4×0.25 μm2. The 0.25 μm-thick core and the 2.5μm-

thick cladding layers of the waveguide are made of silicon nitride and silicon dioxide,

respectively. The CPD sensing technique measures the shift of the critical point of the total

reflection as the results of change of refractive index due to biofouling. Optical simulations are

used to validate the working principle and the calculated biofouling sensitivity is comparable to

the other optical sensing methods. A baseline measurement has been conducted to verify the

operation of the sensor with an error of less than ± 0.002 R.I.U. During a 9-hour biofouling

measurement using milk as the media, a change in the refractive index as much as 0.0089 is

recorded as the result of biofouling.

The RPD sensing technique employs surface plasmon resonance as its sensing mechanism by

measuring the shift of the resonance point with respect to the change of the incident angle. The

design and fabrication process is similar to the fundamental structure of CPD sensors with an

additional deposition of a thin metal layer on the sensing edge of the prism. The theoretical

sensitivity is calculated as 90 deg RIU-1

, which is comparable with the state-of-the-art optical

sensors at 127 deg RIU-1

. The refractive index measurement for selected liquids agrees with the

values in the literature with an error range of less than ± 0.002 R.I.U. Furthermore, the

refractive index change of biofouling formation is measured to be 0.0078 for a 9-hour

experiment using milk as the testing media.

Professor Liwei Lin, Chair Date

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ii

Acknowledgments

I would like to thank my advisor, Professor Liwei Lin, for giving me the opportunity to

be at the forefront of this field of research and for the support, interest, and encouragement that

he has so generously provided from the days of my undergraduate studies at U. C. Berkeley up to

the present time. I am extremely grateful for what I have learnt from you. There are many other

people I would also like to thank for their help, encouragement, and support, including all of my

friends and associates, and I very much regret not adequately expressing my very deep

appreciation for all of you.

Most of all, I cannot find words capable of describing my appreciation for my parents.

You are the reason for which I live, for why I am the person I am, and for my success. So most of

all, I would like to dedicate this doctoral study to you. To my mother, Mrs. Yeon Soon Seo: you

are the strongest and sweetest person in the world. And to my father, Mr. Ki Hong Nam: you are

my hero, and there is nothing that will ever change that. Mom and dad, you are my tears, smiles,

and everything that I can have that is of any value or is worth living for.

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Contents

List of Figures and Tables ........................................................................................................... vi

Chapter 1 Introduction................................................................................................................. 1

1.1 Prism-coupler Type Angular Interrogation System........................................................... 1

1.1.1 Critical Point Detection Sensing ................................................................................. 3

1.1.2 Resonance Point Detection Sensing ............................................................................ 4

1.2 Chapter Overviews ............................................................................................................ 6

References ................................................................................................................................... 7

Chapter 2 Macroscale Prism-coupler Type Sensing using Fraunhofer Diffraction ............... 9

2.1 Introduction ....................................................................................................................... 9

2.2 Theoretical Background .................................................................................................. 10

2.2.1 Total Internal Reflection ........................................................................................... 10

2.2.2 Fraunhofer Diffraction .............................................................................................. 11

2.2.3 The Convolution of Reflection and Diffraction Patterns .......................................... 12

2.2.4 Detection of Biofouling ............................................................................................ 13

2.3 Numerical Simulation ...................................................................................................... 14

2.4 Working Principle............................................................................................................ 16

2.5 Experiment Protocols and Considerations ....................................................................... 17

2.5.1 Direct Refractive Index Measurement ...................................................................... 17

2.5.2 Media of Different Optical Properties ...................................................................... 17

2.5.3 Sources of Error ........................................................................................................ 17

2.5.4 Image Processing ...................................................................................................... 18

2.6 Sensing Experiment ......................................................................................................... 18

2.6.1 Experimental Setup ................................................................................................... 18

2.6.2 Experiment Results ................................................................................................... 19

2.7 Summary .......................................................................................................................... 22

References ................................................................................................................................. 23

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Chapter 3 Critical-Point-Detection (CPD) Sensing ................................................................. 25

3.1 Introduction ..................................................................................................................... 25

3.2 Microscale Sensor Design and Fabrication ..................................................................... 26

3.2.1 Sensor Design ........................................................................................................... 26

3.2.2 Fabrication Procedure ............................................................................................... 27

3.2.3 Design Variations...................................................................................................... 28

3.2.4 Fabrication Results.................................................................................................... 31

3.3 Experiments and Results ................................................................................................. 32

3.3.1 Experimental Setup ................................................................................................... 32

3.3.2 Calibration................................................................................................................. 34

3.3.3 Direct Refractive Index Measurement ...................................................................... 35

3.3.4 Biofouling Sensing.................................................................................................... 37

3.4 Discussions ...................................................................................................................... 38

3.4.1 General ...................................................................................................................... 38

3.4.2 Tribology................................................................................................................... 39

3.5 Summary .......................................................................................................................... 40

References ................................................................................................................................. 42

Chapter 4 Resonance-Point-Detection (RPD) Sensing ............................................................ 44

4.1 Introduction ..................................................................................................................... 44

4.2 Theoretical Background .................................................................................................. 45

4.3 Numerical Simulation ...................................................................................................... 46

4.4 Working Principle and Design ........................................................................................ 48

4.5 Microscale Sensor Fabrication ........................................................................................ 49

4.6 Experiments and Results ................................................................................................. 50

4.6.1 Experimental Setup ................................................................................................... 50

4.6.2 Image Processing ...................................................................................................... 51

4.6.3 Effect of Polarization ................................................................................................ 51

4.6.4 Experimental Results ................................................................................................ 52

4.7 Discussion ........................................................................................................................ 54

4.7.1 Design Variations...................................................................................................... 54

4.7.2 Determination of Sensitivity ..................................................................................... 55

4.8 Summary .......................................................................................................................... 56

References ................................................................................................................................. 58

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Chapter 5 Conclusions and Future Work ................................................................................ 60

5.1 Conclusions ..................................................................................................................... 60

5.2 Future Directions ............................................................................................................. 61

5.2.1 Self Cleaning Sensor using UV and F-IR Ray.......................................................... 61

5.2.2 Integration of Laser Diode and Photo Detector ........................................................ 62

5.2.3 Measurement of phase difference between s- and p-polarizations ........................... 63

5.2.4 Measurement in Total Internal Reflection Region .................................................... 64

5.2.5 Digitated Sensor Geometry ....................................................................................... 64

5.2.6 Thickness measurement of SPR-based sensor .......................................................... 65

5.2.7 Sensor using Fresnel diffraction ............................................................................... 65

References ................................................................................................................................. 67

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vi

List of Figures and Tables

Figure 1.1: Sensitivity plotted against size of current sensors and goal of this study. ................... 2

Figure 1.2: Schematic of proposed prism-coupler type microscale sensor. ................................... 2

Figure 1.3: Critical point shift on the reflectance profile under TIR conditions with regard to

changes in refractive index. ......................................................................................... 3

Figure 1.4: Typical reflectance and diffraction patterns for light of varying incident angles and

the convolution pattern of their combination as a resulting sensor signal. .................. 4

Figure 1.5: Resonance point shift on the SPR intensity profile according to changes of refractive

index. ............................................................................................................................ 5

Figure 1.6: Typical SPR intensity profile, diffraction patterns for varying incident angle of light

and the convolution patterns as resulting sensor signals. ............................................. 5

Figure 2.1: Reflectance profile and total internal reflection. ........................................................ 10

Figure 2.2: Normalized intensity of light and Fraunhofer diffraction. ......................................... 11

Figure 2.3: Schematic diagram of convoluted light patterns induced by reflection and diffraction.

.................................................................................................................................... 13

Figure 2.4: Output signals of different refractive indices. ............................................................ 15

Figure 2.5: Refractive index change versus angle of convolution peak. ...................................... 15

Figure 2.6: Schematic illustration of prism-coupler type sensing mechanism utilizing Fraunhofer

diffraction. .................................................................................................................. 16

Figure 2.7: Image analysis process illustrating how to find the critical point. ............................. 18

Figure 2.8: Complete optical setup for macroscale experiment. .................................................. 19

Figure 2.9: Typical output signal captured by webcam and corresponding theoretical patterns of

diffracted and reflected light separated. ..................................................................... 20

Figure 2.10: Output signals captured by CCD and corresponding intensity profiles for a milk

biofouling formation. ................................................................................................. 21

Figure 2.11: Position of critical point and corresponding refractive indices with respect to time.

.................................................................................................................................... 22

Figure 3.1: Schematic illustration of CPD sensing mechanism. .................................................. 26

Figure 3.2: Schematic diagram of light paths in a prototype CPD sensor. ................................... 27

Figure 3.3: Microfabrication procedures for proposed sensors. ................................................... 28

Figure 3.4: Optical simulation results showing coupling of a single mode of light and the

propagation loss during its passage through the waveguide. ..................................... 30

Figure 3.5: SEM image of sensing edge of sensor (x3,800 and x13,000). ................................... 31

Figure 3.6: SEM pictures of exit edge and waveguide entrance (x13,000 and x370). ................. 31

Figure 3.7: Edge of sensor beyond exit edge. ............................................................................... 32

Figure 3.8: (a) Microscale sensors on a chip, (b) diffraction pattern from waveguide, and (c)

reflection pattern. ....................................................................................................... 32

Figure 3.9: Microscale CPD sensor experimental setup. .............................................................. 33

Figure 3.10: (a) PDMS microchannel on sensor chip; (b) cross-sectional view of the PDMS

channel. ...................................................................................................................... 34

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vii

Figure 3.11: Segmented pattern of Fraunhofer diffraction showing the main observation area. . 34

Figure 3.12: Refractive index measurement results for air, water, ethanol and acetone. ............. 36

Figure 3.13: Experiment results of CPD sensor for different media of known refractive indices.

.................................................................................................................................... 37

Figure 3.14: Microscale sensing experiment results of TIR-based sensor for biofouling formation.

.................................................................................................................................... 38

Figure 3.15: Illustration of coupling light source and its effect at different angles of incidence. 39

Figure 3.16: Illustration of secondary diffraction at exit edge of sensor and possible noise

creation at the chip edge............................................................................................. 39

Figure 3.17: Schematic of erosive wear on (a) a CPD sensor and on (b) an SPR-based (RPD)

sensor. ........................................................................................................................ 40

Figure 4.1: Schematic of SPR-based RPD sensor. ....................................................................... 45

Figure 4.2: Results of numerical simulation with different refractive indices. ............................ 47

Figure 4.3: Refractive index change versus the angles of the convolution peaks. ....................... 47

Figure 4.4: (a) Schematic diagram illustrating RPD sensing mechanism; (b) surface plasma wave

(SPW) formation within metal, biofilm, and background. ........................................ 48

Figure 4.5: Two methods of metalizing the SPR sensor. ............................................................. 49

Figure 4.6: SEM picture of gold layer on the exposed edge of prism. ......................................... 50

Figure 4.7: Experimental setup of SPR-based sensor. .................................................................. 50

Figure 4.8: Image analysis process illustrating how to find the resonance point. ........................ 51

Figure 4.9: Image analysis process illustrating the resonance points of different polarization

states of light. ............................................................................................................. 52

Figure 4.10: Refractive index measurement results for water, ethanol, and acetone. .................. 53

Figure 4.11: Experiment results of RPD sensor for media of known refractive indices. ............. 53

Figure 4.12: Microscale sensing experimental result of the RPD sensor test for biofouling

formation. ................................................................................................................... 54

Figure 4.13: Reflectance variation with respect to the thickness of the gold (Au) layer. ............ 55

Figure 5.1: Schematic illustrating a strategy to remove biofilm deposition from a sensor using

ultraviolet and far-infrared rays as a means of cleaning. ........................................... 62

Figure 5.2: Schematic of a self-powered sensing device. ............................................................. 62

Figure 5.3: Response of reflectance in accordance with incident angle for s- and p-polarized light.

.................................................................................................................................... 63

Figure 5.4: Schematic of Three Exit Waveguide sensors and their corresponding points of

measurement on a convoluted light profile. ............................................................... 64

Figure 5.5: (a) Schematic of conceptual design of sensor using Fresnel diffraction, (b)

corresponding intensity profile. ................................................................................. 65

Table 1: Summary of Microscale Prism-coupler type Sensor for this study ................................ 29

Table 2: Summary of sensitivity study for various sensing techniques. ...................................... 56

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Chapter 1

Introduction

1.1 Prism-coupler Type Angular Interrogation System

Total Internal Reflection (TIR) is a well known physical phenomenon that has been

researched and utilized for optical observations for several decades [1, 2, 3, 4, 5]. Used as a

sensing technique, it has been appreciated for its ability to provide label-free sensing: that is,

analyses without the use of fluorescent or radioactive materials [6, 7]. The presence of the

critical points and surface plasmonic evanescent (decaying) waves are two of the most

representative mechanisms for sensing employing TIR. Among various TIR applications, the

prism-coupler method, also known as attenuated total reflection (ATR) method, is most

advantageous [8, 9] as the angular interrogation sensors measure variations with respect to the

changes of incident angle of light for high sensitivity and wide range detections [10, 11]. Other

techniques such as the optical fiber sensors [12, 13] and the grating-coupler type sensors [14, 15,

16] have been developed, but they are not as versatile as the prism-coupler type sensor in terms

of sensitivity and detection range [9].

Conventionally, in the prism-coupler type angular interrogation sensors, the change of an

incident light angle is applied by rotating the light source which requires bulky and expensive

rotational devices [17]. The rotating light source is especially problematic for micro-scale

optical experiments and in-situ online measurements. Another problem arises from the

extended scanning time. When used in multi-point measurements, long scanning times may

lead to inaccurate results and discrepancies between the sensors. In contrast, waveguide type

sensors are typically smaller in size, while their application could be limited because of lower

sensitivity and narrower detection range of the propagating light in the guide [8, 18, 19].

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Intensity

Measurement Type

Se

nsit

ivit

y

Capacity for Miniaturization

Waveguide

Type

Wavelength

Interrogation Type

Angular Interrogation

Type

78~90°

Breakthrough

= Goal

10-1 10-2 10-3 [m]1

10-6

([] RIU-1)

Figure 1.1: Sensitivity plotted against size of current sensors and goal of this study.

Figure 1.1 illustrates the sensitivity versus capacity for miniaturization plot, including

waveguide type, intensity measurement type, wavelength interrogation type and angular

interrogation type sensors. Clearly, the goal is to make miniaturized sensors with good

sensitivity as shown. In this study, we propose to adopt a simple optical phenomenon,

Fraunhofer diffraction, to replace the rotating light source employed in the angular interrogation

sensing technique for the scanning of the incident light angles within a prism-coupler structure.

This principle simplifies the detection mechanism such that the prototype microscale sensor

requires only a two-mask fabrication process. This microscale sensor consists of a built-in

waveguide with a prism-coupler to take advantage of Fraunhofer diffraction occurring at the end

of the waveguide. Since the proposed sensor is fully planar integrated; it can be made using an

IC fabrication process. Therefore, integration with other IC devices and micro-size fabrication

could be readily available, and a low unit cost should be achievable through mass production.

Furthermore, the angular interrogation type sensors typically have better sensitivity and we aim

to maintain the sensitivity of the proposed planar total internal reflection sensors.

Sensed Medium

Diffraction

Figure 1.2: Schematic of proposed prism-coupler type microscale sensor.

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The proposed sensor could potentially improve the sensitivity and detection range while

maintaining the benefits of using a simple waveguide structure as illustrated in Fig. 1.2. There

are a wide range of applications that may utilize this sensing structure, including process,

motion, gas, and chemical monitoring. Specific characteristics suitable for these applications

include: non-destructive nature for material characterization [20]; highly sensitive for in-situ gas

sensing [21, 22] and artificial olfactory sensing [23, 24]; and possible benefits from scaling

effects which enables the measurement of protein conformation [25], chemical sensing [26],

polymer concentration [27], and monolayer formation (biofouling) [28]. This research

concentrates on the possible applications for biofouling to reduce the maintenance cost in clean

water technologies.

Two types of sensing methods are investigated: Critical Point Detection (CPD) and

Resonance Point Detection (RPD), including details in analysis, fabrication, and experiments.

Both sensor designs enable: (1) the reduction of sensor size and the elimination of moving parts,

(2) the elimination of scanning operation, and (3) planar integration of the entire system.

Moreover, small-sized sensors can better enable multi-point local detections for improved

sensing accuracy for broader application areas.

1.1.1 Critical Point Detection Sensing

The CPD sensor detects the movement of the critical point in order to measure the

refractive index changes utilizing the TIR scheme. The shift of critical point in accordance with

the change of refractive index of the analyte occurs as is illustrated in Figure 1.3. This sensing

method makes use of the rapid drop of intensity at a certain angle of incident light under the TIR.

Since this is a simple physical phenomenon, no additional fabrication or manipulation is required

for sensing.

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1Critical Points

Response of

Refractive Index

Change

Angle of Incidence (deg.)

No

rma

lize

d In

ten

sity

Figure 1.3: Critical point shift on the reflectance profile under TIR conditions with regard to

changes in refractive index.

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When the reflectance change under TIR conditions is combined with the Fraunhofer

diffraction by a waveguide structure as proposed, resulting light signal becomes convoluted, as

shown in Figure 1.4. Compared to other optical sensors such as the SPR sensor which requires

a thin metal layer, the structure materials of this sensor is less vulnerable to erosive wear.

Therefore, this type of sensor is much better suited for environment that may require chemical

and mechanical polishing on the surface such as biofouling in water desalination stations.

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

=

*

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

Reflectance

Pattern

Diffraction

Pattern

Convolution

Pattern

Figure 1.4: Typical reflectance and diffraction patterns for light of varying incident angles and

the convolution pattern of their combination as a resulting sensor signal.

1.1.2 Resonance Point Detection Sensing

RPD sensors measure the refractive index of a material by detecting the movement of

resonance points through Surface Plasmon Resonance (SPR), and the shift of resonance point in

accordance with the change of the refractive index of an analyte as is illustrated in Figure 1.5.

Unlike the CPD sensor, RPD sensors require a thin metal layer to form the metal/dielectric

interface where surface plasmons resonate and propagate. Thin metal coating material and the

thickness of the layer are two key factors in the optimization of the SPR signals and gold layer of

several tens of nanometers in thickness is commonly used.

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15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

Response of

Refractive Index

Change

Angle of Incidence (deg.)

No

rma

lize

d In

ten

sity

Resonance Points

Figure 1.5: Resonance point shift on the SPR intensity profile according to changes of refractive

index.

When the intensity variations caused by SPR values with respect to the angle of the incident light

are combined with the Fraunhofer diffraction, the resulting light signal is a convolution pattern,

as shown in Figure 1.6. Compared with other optical sensing methods, this technology could

have greater sensitivity. Additionally, the sharply defined output signal offers great clarity for

signal detection in practical measurements.

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

Diffraction

Pattern

=

*

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

SPR Intensity

Profile

Convolution

Pattern

Figure 1.6: Typical SPR intensity profile, diffraction patterns for varying incident angle of light

and the convolution patterns as resulting sensor signals.

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1.2 Chapter Overviews

Chapter 2 discusses the concept of the proposed prism-coupler type sensing method

using Fraunhofer diffraction. A numerical simulation is conducted to investigate the feasibility

of this sensor and its sensitivity which is comparable to other current sensing methods. A

macroscale experiment using commercial optical components is conducted. The technique is

found to be feasible as a refractive index monitoring sensor.

Chapter 3 presents a discussion of the theoretical background of the proposed micro

CPD sensing technique for measuring the refractive index of an analyte through the utilization of

both Fraunhofer Diffraction and the convolution of reflected and diffracted light. A distinctive

feature of the prototype sensor is an integrated waveguide which takes advantage of the

Fraunhofer diffraction occurring at the end of the waveguide. The experimental results

demonstrate that this sensing technique enables a wider application area than conventional

prism-coupler type sensors while maintaining the quality of measurement. Since the material of

the sensor structure is stiff to resist erosive wear better than other materials used on the sensing

surfaces, tribological theory and techniques are employed to prove the actual superiority of this

class of sensor.

Chapter 4 is a study of Surface Plasmon Resonance (SPR) and its application to the CPD

sensor as presented in chapter 3. The advantage of SPR technology is its ability, under certain

conditions, to measure refractive indices with high selectivity. As is the case with the CPD

sensor discussed in Chapter 3, the proposed RPD sensor takes advantage of an integrated

waveguide. The numerical simulation and experiments are conducted to investigate the

feasibility of this sensor, and the result shows better accuracy than the CPD sensors.

Finally, the chapter 5 concludes the thesis and suggestions for future study are presented.

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References

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[15] K. Tiefenthaler and W. Lukosz, ―Sensitivity of grating couplers as integrated-

optical chemical sensors,‖ Journal of the Optical Society of America, vol. 6, pp.

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8

209-220, 1989.

[16] J. Vörös, J. J. Ramsden, G. Csucs, I. Szendr, and S. M. D. Paul, M. Textor, and N.

D. Spencer, ―Optical grating coupler biosensors,‖ vol. 23, pp. 3699-3710, 2002.

[17] H. C. Pedersen, W. Zong, M. H. Sørensen, and C. Thirstrup, ―Integrated

holographic grating chip for surface plasmon resonance sensing,‖ Optical

Engineering, vol. 43, pp. 2505-2510, 2004.

[18] C. R Lavers and J. S. Wilkinson, ―A waveguide-coupled surface-plasmon sensor for

an aqueous environment,‖ Sensors and Actuators B: Chemical, vol. 22, pp. 75-81,

1994.

[19] I. Abdulhalim, M. Zourob, and A. Lakhtaki, ―Surface Plasmon Resonance for

Biosensing: A Mini-Review,‖ Electromagnetics, vol. 28, pp. 214-242, 2008.

[20] D. Nedelkov and R. W. Nelson, ―Surface plasmon resonance mass spectrometry:

recent progress and outlooks,‖ Trends in Biotechnology, vol. 21, pp. 301-305, 2003.

[21] C. Nylander, B. Liedberg, T. Lind, ―Gas detection by means of surface plasmons

resonance,‖ Sensors and Actuators A, vol. 3, pp. 79-88, 1982.

[22] M. Niggemann, A. Katerkamp, M. Pellmann, P. Bolsmann, J. Reinbold and K.

Cammann, ―Remote sensing of tetrachloroethene with a micro-fibre optical gas

sensor based on SPR spectroscopy,‖ Sensors and Actuators B, vol. 34, pp. 328-333,

1996.

[23] J. Vidic, J. Grosclaude, R. Monnerie, M. Persuy, K. Badonnel, C. Baly, M. Caillol,

and L. Briand, ―On a chip demonstration of a functional role for odorant binding

protein in the preservation of olfactory receptor activity at high odorant

concentration,‖ Lab on a Chip, vol. 8, pp. 678-688, 2008.

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assessment of olfactory receptors activity in immobilizednanosomes: a novel

concept for bioelectronic nose,‖ Lab on a Chip, vol. 6, pp. 1026-1032, 2006.

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[27] G. Sakai, K. Ogata, T. Uda, N. Miura, N. Miura, and N. Yamazoe, ―A surface

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Chapter 2

Macroscale Prism-coupler Type Sensing

using Fraunhofer Diffraction

2.1 Introduction

A prism coupler is an instrument widely used to measure the refractive index and

thickness of materials as well as to couple light in a waveguide. Prism structure in a prism

coupler is utilized to introduce incident light from a variable angle source and to deliver the

reflected light from the prism surface to a detector or screen. For most applications, a prism

coupler characterizes the properties of an analyte using measurements of reflected light emitted

at various angles. Angle scanning devices such as goniometers are usually employed to change

the angle of incident light, and the measurement resolution of the prism coupler is dependent on

the rotational accuracy of the scanning device. For this reason, prism couplers commonly

require a bulky and expensive angle scanning device for high precision measurements.

The prism-coupler method has been researched for adoption in conventional devices

such as ellipsometry type sensors [1], and also in very high sensitivity SPR sensing techniques [2,

3, 4]. Among the prism-coupler type SPR sensors, fan-shaped light diverging schemes do not

need moving parts (for instance, a goniometer). Thus the latter design has been actively studied

in terms of its possibilities in miniaturization [5, 6]. However, due to the limitation that follows

from the fact that the divergence of light requires macro scale optical components such as lenses,

the prospects are remote for this sensor type being becoming a microscale device.

In this study, the divergence light within a diffraction pattern induced by a simple single-

slit is employed in a prism-coupler structure to create a microscale sensor. Therefore, in this

chapter, the feasibility of the sensing concept is first verified through macroscale experiments

utilizing reliable optical components such as commercial single-slits and right-angle prisms. A

precisely constituted macroscale experimental setup generates a TIR response, and a critical

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point is detected to analyze the refractive index of an analyte. Microscale fabrication and

detailed sensing experiments of CPD sensors are discussed later in Chapter 3. Although SPR is

not incorporated into the macroscale experiment in this chapter, the fundamental concept is

basically the same. An RPD sensor utilizing SPR is discussed in Chapter 4.

2.2 Theoretical Background

2.2.1 Total Internal Reflection

When the incident angle is low with respect to the angle normal to the interface between

two media with different refractive indices, a portion of the ray of light striking the interface is

transmitted and absorbed, and the remaining portion is partially reflected [7]. However, as the

angle of incidence increases, the reflectance of the light increases and eventually reaches a value

of 1 (100% reflection) at the critical point (Fig. 2.1 and Eqn. 2.1). The incident angle at critical

point is determined by the refractive index of the medium being measured; therefore the critical

angle can be calculated to determine the refractive index of a medium to be examined.

2

2

2

121

2

2

121

2

cos1cos

cos1cos

ii

ii

n

nnn

n

nnn

rR

(2.1)

30 35 40 45 50 55 60 65 700

0.5

1

1.5TE Reflection

Angle [deg]

R-T

E

n = 1

n = 1.333

n = 1.45

Angle of Incidence (deg.)

Reflecta

nce

Figure 2.1: Reflectance profile and total internal reflection.

The reflectance profiles in Figure 2.1 show how reflectance changes with regard to the refractive

indices of three selected media, air, water, and milk. For each medium, there are three critical

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points clearly shown on each of the curves. After experimentally determining the position of a

critical point, it is possible to redraw the profile, and thus to derive the value of refractive index.

This is the basic theoretical background of the sensing methodology employed by the CPD

sensing techniques examined in this study.

2.2.2 Fraunhofer Diffraction

Fraunhofer diffraction is a far-field optical phenomenon which can be observed when a

wave passes through an obstruction. Typically, light waves passing through slits or holes are

diffracted. Fraunhofer diffraction occurs as a result of the interference and reinforcement

interactions of incoming and diffracted waves [7, 8, 9]. In general, Fraunhofer diffraction is

approximated through the following equation:

2

0

sin

II (2.2)

is called sinc function and is defined as,

sin

d (2.3)

where d is the width of the slit and is the wavelength of the light source.

-10 -8 -6 -4 -2 0 2 4 6 8 100

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Angle of Incidence (deg.)

Norm

aliz

ed Inte

nsity

Figure 2.2: Normalized intensity of light and Fraunhofer diffraction.

When the light passes through a small opening or slit, the intensity of the spread of the light

varies with respect to the angle of diffraction, as shown in Figure 2.2. Due to the reinforcement

and destructive interference of light waves, numerous peaks and dark fringes are generated. In

particular, the region around the zero-order (central) peak is brighter than the others. This light

spreading ability of Fraunhofer diffraction can be utilized to manipulate light waves, especially

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in situations that limit the use of optical components such as a lens. In this study, the

Fraunhofer diffraction is utilized to enable fabrication of microscale planar devices as well as to

minimize the use of complex optical components.

As the distance between the slit and the detector decreases (typically, the position at

which the light signal is observed in the CPD sensor), the Fraunhofer diffraction begins to lose

its dominance over the final pattern of the light, and the final output light pattern begins to follow

Fresnel diffraction [10]. This distance was set to be the minimum design parameter

(dimension) of the sensor so that the sensor is only affected by Fraunhofer diffraction. The

boundary condition between Fraunhofer and Fresnel diffractions is defined by the Fresnel

Number, F , which is given by the following equation [11]:

L

dF

2

(2.4)

where d is a width of the slit (the aperture) and L is the distance between the slit and the

detector. When the Fresnel Number is much smaller than 1, the Fresnel diffraction begins to

dominate.

2.2.3 The Convolution of Reflection and Diffraction Patterns

When two or more patterns of light merge, the resulting pattern is a summation of each

component, which is called a convolution, and the interactions of light waves through

reinforcement and interference cause such convolutions. By setting the peak of the zero-order

Fraunhofer diffraction at a specific point, the profile of convolution for a light wave can be

derived as follows:

2

2

121

2

2

1212

0

sin1cos

sin1cos

sin

rr

rr

d

n

nnn

n

nnn

dcI

RII

(2.5)

where shiftcritr

For example, when reflection and diffraction occur simultaneously, the pattern of light at the

detector becomes complicated as illustrated schematically in Figure 2.3.

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15

20

25

30

35

40

45

50

55

60

65

0

0.2

0.4

0.6

0.8

1

=

*

15

20

25

30

35

40

45

50

55

60

65

0

0.2

0.4

0.6

0.81

Figure 2.3: Schematic diagram of convoluted light patterns induced by reflection and diffraction.

Convoluted by multiple light waves, the resulting pattern is affected by each individual signal.

Therefore, careful separation of these signals is necessary if there is a need to study any single

pattern contributing to the complex pattern of the convolution. In this study, only the light

reflection profile of the reflection-diffraction convolution pattern is allowed to vary, while the

diffraction pattern remains fixed. Therefore, image analysis is significantly simplified when

compared with the convolution patterns that would result from multiple varying patterns of light.

2.2.4 Detection of Biofouling

Biofouling is the consequence of an unwanted accumulation of biological substances on

exposed surfaces in aqueous environments. Such surfaces are found in pipeline systems [12,

13], heat sinks [14, 15], marine equipment [16, 17, 18, 19], the blood vessels of the human body,

[20] and teeth in the case of dental plaque [21, 22]. The substances that deposit and adhere on

these surfaces give rise to thin films of bacteria, algae, and fungi, as well as inorganic material.

Left unattended, these biofilms may result in the reduced efficiency of aquatic equipment and the

increased frequency of system maintenance. For example, thick biofilms deposited over time

result in dramatically increased maintenance costs because the usage of common antimicrobial

agents is not usually sufficient to remove the biofilms completely [23]. Today, neither the

mechanisms of the biofouling processes nor the procedures needed to control them are clearly

understood, such that the monitoring of the growth of biofilms is a fundamental and practical

issue.

As biofouling progresses to grow thicker, the optical properties of biofilms change.

When the thickness of biofilms increases, their refractive index increases accordingly [24].

However, state of the art biofouling sensors based on optical detection do not take into account

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changes in the refractive index of biofilms, and this could be a source of measurement errors in

those characterizations [25, 26].

Changes in the refractive index are relatively stable and predictable at the base of the

biofilm because its location is away from the disturbances of the fluid medium flowing above.

Thus protection is provided by biofouling materials between the base and the biofouling surface.

Furthermore, after the initial layer of biofilm is deposited, the newly formed biolayers can have a

great variety of compositions as well chemical and physical properties. The initial deposition

can be seen as medium or substratum capable of providing opportunities for colonization and

competition by other organisms. This unpredictable variation of the biofilm-fluid interface on

top of the biofilm surface can affect the layer thickness, diffusion depth of biofoulants, nutrients,

and other particulates, coefficient of friction, growth rate of the film itself, tendencies toward the

adhesion of organic and inorganic particulates and, significantly, the refractive index. These

variables make the properties of the surface layer of a biofilm difficult to predict and, therefore,

unsuited to the requirements of contemporary sensing technologies. Consequently, the

measurement at the bottom of a biofilm constitutes a more reasonable approach to determining

the baseline property of biofilm formations.

For this study, the refractive index at the interface between the surface of a sensor and

the biofouling media is measured to study the condition of the biofilm and characterized with

respect to time to monitor the formation of biofouling processes.

2.3 Numerical Simulation

Numerical simulation allows us to predict the convolution of reflection and diffraction

patterns of light and to show the feasibility of the sensing technique proposed for this study.

Figure 2.4 shows several cases of convolution patterns with media of differing refractive indices.

In the figures below, thick solid lines represent the convolution patterns which are likely to be

observed experimentally in measurements of the refractive index. The blue and red dotted lines

in the figures illustrate the reflection and diffraction of light, respectively. For each case, the

change of reflection pattern is the only factor contributing to the shift of the peak in the

convolution curve, and this peak constitutes the signal to be detected.

Unlike the original diffraction and reflection patterns, the peak of the convolution line is

sharp, and the tip of this signal clearly shifts with respect to the change of refractive index of the

analyte. As depicted in Figure 2.5, the peak shift in the convolution curve is a possible

indicator for the measurement of a medium‘s refractive index. The result indicates that the

changes of refractive index and corresponding critical angle are linearly related; therefore the

sensitivity is the slope of the fitting line. The theoretical sensitivity of the CPD sensor used in

this simulation was 36 deg. R.I.U.-1

.

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10 20 30 40 50 60 700

0.2

0.4

0.6

0.8

1

10 20 30 40 50 60 700

0.2

0.4

0.6

0.8

1

10 20 30 40 50 60 700

0.2

0.4

0.6

0.8

1

10 20 30 40 50 60 700

0.2

0.4

0.6

0.8

1

Re

flecta

nce

Relative Incident / Offset Angle (deg.)

Δn = 0 Δn = 0.01

Δn = 0.02 Δn = 0.03

Figure 2.4: Output signals of different refractive indices.

0 0.005 0.010 0.015 0.020 0.025 0.030

40.6

40.8

41.0

41.2

41.4

41.6

41.8

y = 36.37*x + 40.56

Cri

tical A

ngle

(d

eg

.)

Refractive Index Change (Δ R.I.U.)

Figure 2.5: Refractive index change versus angle of convolution peak.

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2.4 Working Principle

Δθ

CCD

L

D

Single Slit

Exposed Edge

Exit Edge

Input Edge

Light Source

Figure 2.6: Schematic illustration of prism-coupler type sensing mechanism utilizing Fraunhofer

diffraction.

Figure 2.6 illustrates the sensing principle of the macroscale experiment setup for a

prism-coupler type sensor employing Fraunhofer diffraction. The setup consists of a light

source, a single-slit, a right angle prism, and a CCD camera as a detector. The single-slit which

is joined to the light source diffracts light, and the reflected light emerging from the prism is

captured by the CCD. The divergent light reflects against the interface between the edge of the

prism and the analyte, and the refractive index of the analyte determines the position of the

critical point in the resulting light pattern. Apart from the utilization of a single-slit, the

configuration of experimental setup is identical to that of conventional prism-coupler type

sensors [27, 28, 29]. The shift in refractive index of the sensed medium is calculated through

the observation of the movement of the critical point positions of the total internal reflection.

The output signals captured by the CCD can record the position of the critical point of

the reflected light, and the refractive index of the media is calculated by the derivation based on

the Fresnel equation expressed in Equation 2.1 [7]. The path that the light travels is illustrated

in Figure 2.6, where L represents the total distance of light traveling from the input edge of the

prism to the CCD, D gives the distance the light traveling from the reflection point to the CCD,

and d is the shift of the critical point on the CCD detector. The basic formulation of Snell‘s

law states:

12

1

int /sin nnpocritical

(2.6)

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Therefore, the refractive index of medium being measured is given as follows:

Ldnnn icritprismicritprismanalyte /sinsin __ (2.7)

where crit_i and are, the critical angle at the initial stage (reference material) and the total

angle shift of the critical point due to the change of the refractive index during the experiment,

respectively. Likewise, nanalyte and nprism represent the refractive indices of analytes to be

measured and the prism, respectively.

2.5 Experiment Protocols and Considerations

2.5.1 Direct Refractive Index Measurement

The critical point of the output signal changes as soon as the prism‘s sensing facet

(exposed edge) is exposed to medium. However, since total internal reflection is a surface

phenomenon, it requires an appropriate period of time for the target medium to wet the sensing

surface. Otherwise molecules attaching at the surface will not be distributed homogenously,

resulting in an inaccurate measurement. This is a common problem for all optical sensors, and

it is an important consideration when there is need for precise measurement.

If the analytes are very viscous and adhesive, it will be difficult to remove the molecules

attaching to the sensing surface by purging with the reference material (such as water) when

cleaning the apparatus. Therefore, liquids with low viscosity are recommended for earlier

testing experiments if several analytes are to be measured sequentially by the same device. The

solubility of an analyte in the reference material is also an important factor in deciding the

sequence of measurements. Water is used as a reference material in this study because of its

good solubility with regard to many other liquids. Viscous liquids such as glycerol are tested in

the final stages measurement due to their resistance to the purging process.

2.5.2 Media of Different Optical Properties

In-situ measurements capable of observing the dynamic responses of an analyte are

possible with this sensing technique. Examples of dynamic responses include: the mixing of

liquids, cell growth and densification, as well as biological film deposition and aging. To

observe the formation and aging of biofouling, the sensing surface of the sensor is exposed to the

liquid containing the biofoulants which provide both the adhesive molecules necessary for

biofouling to occur and the feed nutrients for growth. To monitor and characterize biofouling,

the surface refractive index between the prism and analytes is measured and plotted with respect

to time.

2.5.3 Sources of Error

The improper arrangement and alignment of a sensor and optical components are

common sources of measurement error for most optical experiments. Because the intensity of

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light signal at each phase is a main target for observation, a stable and steady light source is

required in experiments.

The refractive index is also affected by the temperature of the medium. Therefore, the

thermal inhomogeneity, or temperature variation of the analyte and the sensor components

through which the light passes could be a source of measurement error. As a result, temperature

must be controlled throughout all experiments; otherwise compensation must be added during

the data processing process to compensate possible errors coming from temperature variations.

Humidity is also a factor that influences the transmission of light, but it is regarded to be a minor

source of error.

2.5.4 Image Processing

Output signals have been analyzed by Image-pro Plus (Media Cybernetics, USA), an

image processing software. The numerical results in Figure 2.7 clearly indicate the detection of

a critical point. Here, the critical point is revealed as the position after which the intensity of

the output signal rapidly diminishes. The flat region of the curve results from a partially

saturated region of the light pattern induced by Fraunhofer diffraction, and after the critical point,

the output signal decreases with the drop in reflectance.

Critical Point

Figure 2.7: Image analysis process illustrating how to find the critical point.

2.6 Sensing Experiment

2.6.1 Experimental Setup

Macroscale experiments were conducted using optical components including a

commercial single-slit diffraction aperture (precision air slit) and right-angle prism to determine

the feasibility of the sensing concept. As shown in Figure 2.8, the setup of this macroscale

experiment consists of a 630 nm laser source, a single-slit with a 5 um gap, a right-angle fused

silica prism coupled in a container in which several media with different refractive indices for

measurement, and a detector (the CCD chip in a webcam).

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Laser Source(λ=630nm)

Right Angle Prism(Fused Silica)

5 μm Slit

Medium Tank

(Air, Water, and Milk)

Webcam(CCD)

Figure 2.8: Complete optical setup for macroscale experiment.

In the setup, the incident light provided by the laser source is reflected from the interface

between the reflecting (sensing) facet of prism and the analyte and exits through the exit edge of

the prism. The pattern of reflection is changed in accordance with the refractive indices of the

analytes in the medium tank as discussed in previous sections of this chapter. The final optical

profile is then captured by the webcam.

2.6.2 Experiment Results

Because of the high quality of the commercial optical components used for this

macroscale experiment, the signals were clear and the image process generated precise

measurements was close to expected values. Figure 2.9 shows the first experiment on a clean

water and milk mixture. The experiment started with empty medium tank (air), and water was

added and came into contact with the sensing surface of the prism. Milk was then added and a

change in the refractive index of the mixture was observed. The figure shows captured signals

from each medium as well as the corresponding theoretical patterns of diffracted and reflected

light that have been manually separated into discrete patterns. The captured signals are the

convolution of the Fraunhofer diffraction and the Fresnel reflection, and the critical point appears

on the curve adjacent to the zero-order peak of the diffraction pattern. For the convolution, the

diffraction pattern does not move, while critical point shifts along the diffraction pattern

according to the change of refractive index of various types of media. These output signals

agree well with theoretical derivation given in Equation 2. 5.

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Air

Wate

rW

ate

r + M

ilk

Patte

rn o

f

Diffra

ctio

n

Patte

rn o

f

Refle

cta

nce

*

Fig

ure 2

.9: T

ypical o

utp

ut sig

nal cap

tured

by w

ebcam

and co

rrespondin

g th

eoretical p

atterns o

f diffracted

and reflected

light

separated

.

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Critical Point

Figure 2.10: Output signals captured by CCD and corresponding intensity profiles for a milk

biofouling formation.

Observations for the transient behaviors were also conducted to monitor the dynamic

responses of biofouling formation. Figure 2.10 shows the typical output signals captured by

CCD and its intensity profiles for the milk tested after 2, 4 and 8 hours into experiments,

respectively. It is observed that the critical point gradually moved leftwards and the

corresponding refractive indices variations can be calculated to quantify biofouling

characteristics.

The position of critical point was recorded with respect to time, and the refractive index

at each point monitored was calculated as shown in Figure 2.11. As illustrated in Figure 2.6,

there were two groups of setups for measurement in this experiment, and each group was defined

by a distance, D, of 5cm or 10cm, set between the sensing surface of prism and the detector.

Theoretically, the distance should not affect the calculation of the refractive index, and the final

refractive index results for both of the cases showed a reasonable tendency and were consistent

with theoretical predictions. Although temperature was carefully controlled during experiments,

compensation for unexpected temperature variation was conducted and has been displayed as a

dashed line in Figure 2.11.

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0 2 4 6 8 10 12 14 16 180

100

200

300

Rela

tive p

ixel

Time [per 30 min.]

Pixel movement and R.I. change

0 2 4 6 8 10 12 14 16 181.345

1.35

1.355

1.36

0 2 4 6 8 10 12 14 16 181.345

1.35

1.355

1.36

0 2 4 6 8 10 12 14 16 181.345

1.35

1.355

1.36

0 2 4 6 8 10 12 14 16 181.345

1.35

1.355

1.36

Refr

active I

ndex

Po

sitio

n o

f C

ritica

l P

oin

t (p

ixe

l)

Time (every 30 min.)

■ Group 1 (D = 5 cm)

● Group 2 (D = 10 cm)

■ Pixel Number (measured)

□ Reflective Index (calculated)

--- Temperature Effect

Re

fra

ctive

In

de

x

Figure 2.11: Position of critical point and corresponding refractive indices with respect to time.

2.7 Summary

In this chapter, prism-coupler type sensing mechanism utilizing the Fraunhofer

diffraction induced by a single-slit is studied to validate the proposed architecture for biofouling

sensing. Both numerical simulations and macroscale experiments have been conducted.

Fraunhofer diffraction has been generated by using a commercial single-slit, and a portion of the

diffracted light has reached the sensing edge of the prism with a broad range of incident angles.

The total internal reflection critical point can be determined from the convoluted light with the

combined patterns of the reflection and diffraction light patterns. The shift of the critical point

in accordance with the change of the refractive index of the analyte has been calculated by

numerical simulation. Experimental results from the prototype, macro scale system from

several liquids of different refractive indices have shown good consistency with theoretical

values. The refractive index of biofouling has been measured continuously with respect to

time, and the dynamic responses of biofouling characteristics have been recorded. In

conclusion, the macroscale experiment validates the concept of the proposed sensing principle.

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References

[1] Maven Biotechnologies website, www.mavenbiotech.com.

[2] Biacore, www.biacore.com

[3] EcoChemie website, www.ecochemie.nl

[4] K-MAC website, www.k-mac.co.kr

[5] Nomadics website, www.nomadies.com

[6] Reichert website, www.reichertai.com

[7] E. Hecht, Optics, 4th ed., Reading, Addison-Wesley, 1979.

[8] K. Singh and B. N. Gupta, "Fraunhofer diffraction in partially space coherent light

by slit aperture with amplitude filters," Optica, Acta, vol. 17, pp. 609-622, 1970.

[9] E. S. Lamar, "Fraunhofer Diffraction Patterns of Squares and Rectangles," Journal

of the Optical Society America, vol. 39, pp. 929-931, 1949.

[10] C. J, Bouwkamp, "Diffraction Theory," Reports on Progress in Physics, vol. 17, pp.

35-100 ,1954.

[11] Y. P. Kathuria, "Fresnel and far-field diffraction of a truncated elliptical Gaussian

beam due to an elliptical aperture," Journal of Modern Optics, vol. 34, pp. 1085-

1092, 1987.

[12] H. -C. Flemming, "Biofouling in water systems ? cases, causes and

countermeasures," Applied Microbiology and Biotechnology, vol. 59, pp. 629-640,

2002.

[13] K. P. H. Meesters, J. W. Van Groenestijn and J. Gerritse, "Biofouling reduction in

recirculating cooling systems through biofiltration of process water," Water

Research, vol. 37, pp. 525-532,2003.

[14] P.A. Pilavachi, "Heat exchanger R&D, a tool for energy conservation?activities

within the non-nuclear energy R&D programme of the european community," Heat

Recovery Systems and CHP, vol. 9, pp. 411-419, 1989.

[15] A. Nabi, P. Rodgers, and A. Bar-Cohen, "Prediction of Thermal Performance

Degradation of Air-Cooled Fine-Pitch Fin Array Heat Sinks due to Fouling,"

Semiconductor Thermal Measurement and Management Symposium, 2006 IEEE

Twenty-Second Annual IEEE, pp. 2-9, 2006.

[16] M. Wahl, "Marine epibiosis. I. Fouling and antifouling: some basic aspects,"

Marine Ecology Progress Series, vol. 58, pp. 175-189, 1989.

[17] S. Snyder, B. J. Zahuranec, M. Whetstone, "Biofouling research needs for the

United States Navy: Program history and goals," Biofouling, vol. 6, pp. 91-95,

1992.

[18] M. E. Callow, J. A. Callow, "Marine biofouling: a sticky problem," Biologist, vol.

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49, pp. 1-5, 2002.

[19] L. S. Godwin, "Hull Fouling of Maritime Vessels as a Pathway for Marine Species

Invasions to the Hawaiian Islands," Biofouling, vol. 19, pp. 123-131, 2003.

[20] J. A. Schaber, W. J. Triffo, S. J. Suh, J. W. Oliver, M. C. Hastert, J. A. Griswold, M.

Auer, A. N. Hamood, and K. P. Rumbaugh, "Pseudomonas aeruginosa Forms

Biofilms in Acute Infection Independent of Cell-to-Cell Signaling", Infection and

Immunity, vol. 75, pp. 3715-3721, 2007.

[21] P. D. Marsh and D. J. Bradshaw, "Dental plaque as a biofilm," Journal of Industrial

Microbiology & Biotechnology, vol. 15, pp. 169-175, 1995.

[22] T.M. Auschillb, N.B. Artweilerb, L. Netuschil, M. Brecxb, E. Reich, A. Sculeana,

"Spartial distribution of vital and dead microorganisms in dental biofilms,"

Archives of Oral Biology, vol. 46, pp. 471-476, 2001.

[23] J. W. Costerton, P.S. Steward, and E. P. Greenberg, ―Bacterial Biofilms: A Common

Cause of Persistent Infections,‖ Science, vol. 284, pp. 1318-1322, 1999.

[24] M.Leitz, A. Tamachkiarow, H. Franke and K. T. V. Grattan, ―Monitoring of biofilm

growth using ATR-leaky mode spectroscopy,‖ Journal of Physics D: Applied

Physics, vol. 35, pp. 55-60, 2002.

[25] M. G. Trulear and W. G. Characklis, ―Dynamics of biofilm processes,‖ Water

Pollution Control Federation, vol. 54, pp. 1288-1301, 1982.

[26] R. Bakke, R. Kommedal and S. Kalvenes, ―Quantification of biofilm accumulation

by an optical approach,‖ Journal of Microbiological Methods, vol. 44, pp. 13-26,

2001.

[27] R. Ulrich and R. Torge, ―Measurement of thin film parameters with a prism

coupler,‖ Applied Optics, vol. 12, pp.2901-2908, 1973.

[28] J. Midwinter, "Evanescent field coupling into a thin-film waveguide," IEEE Journal

of Quantum Electronics, vol. 6, pp. 583-590, 1970.

[29] H. Rigneault, F. Flory, and S. Monneret, "Nonlinear totally reflecting prism

coupler: thermomechanic effects and intensity-dependent refractive index of thin

films," Applied Optics, vol. 34, pp. 4358-4369, 1995.

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Chapter 3

Critical-Point-Detection (CPD) Sensing

3.1 Introduction

Total Internal Reflection (TIR) is a well known optical phenomenon when all incoming

energy is reflected back to the incident medium [1]. This phenomenon has been exploited in

several ways for a variety of sensing techniques and applications. TIR-based measurement

techniques have been under investigation for several decades. Notable practical studies began

in 1964 with Osterberg and Smith [2] who utilized a prism to couple a light beam into a surface

wave. Ulrich and Torge [3] utilized total internal reflection phenomena to characterize the

parameters of thin-film. Kitajima and Hieda [4] investigated the use of attenuated total

reflection (ATR) to measure the refractive indices of metal-foils. Nee and Bennett [5] studied

measurements of the refractive index of transparent materials. And recently, Patskovsky and

Meunier [6] developed a phase-sensitive silicon-based total internal reflection sensor using the

differential phase shift between p- and s- polarized components of reflected light.

The TIR-based methods have also been studied by many other researchers [7, 8, 9], but

they have not been widely utilized because of the development of the Surface Plasmon

Resonance (SPR) method which provides higher sensitivity compared with TIR approaches [10,

11, 12]. However there are drawbacks to the SPR technologies. The thin metal layers on the

surface of SPR-based sensors are vulnerable to mechanical damage; and this often leads to

unreliable measurements. In cases where surface friction could be a concern, the use of TIR-

based sensors is more desirable because of their greater structural reliability in resisting

mechanical damage including shearing and abrasion.

Complex and large-scale engineered systems could utilize the TIR technology such as

pressurized liquid transportation systems in desalination applications [13, 14, 15] and food

manufacturing plants [16, 17]. These systems operate on solutions containing solid materials

under high pressure. The improvement of the biofouling sensing can assist in the effective

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control of the cleaning processes as well as the real-time response to operational faults under

severe shearing conditions. Furthermore, there are other demands calling for the elimination of

the moving parts in conventional TIR-based sensors, such as the rotation goniometer. Such

structural simplification also enables a significant reduction of sensor size and scanning time,

especially for multi-points and/or mobile measurements. Furthermore, the planar integration of

the TIR sensor reduces the cost in device fabrication.

This chapter investigates the microscale total internal refection sensing techniques as

well as possible applications of the CPD sensor.

3.2 Microscale Sensor Design and Fabrication

3.2.1 Sensor Design

Laser Source

Coupling

Final Output

Signal

Core

Cladding Diffraction

Critical

Point

Exposed

Edge

Input

Edge

Exit Edge

Figure 3.1: Schematic illustration of CPD sensing mechanism.

Figure 3.1 illustrates the sensing principle of the prototype sensor which consists of a

light source, an integrated waveguide-prism structure, and a detector. The waveguide is

designed to deliver light from its open end to the prism-coupler, and the reflected light can exit

through the side-facet of the prism. The surface of the prism is exposed to the analytes, and

diffraction occurs at the input edge (the interface of the waveguide and prism) to spread light in

various directions. This design is similar to conventional prism-coupler type sensors without

the need for dynamic scanning of light sources.

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Δθ

CCD

L

θprism

D (5cm or 10 cm)

Waveguide

Exposed Edge

(1.33mm)

Exit Edge

(0.86mm)Input Edge

(1mm)

Figure 3.2: Schematic diagram of light paths in a prototype CPD sensor.

Figure 3.2 shows the schematic diagram of light paths in a prototype microscale sensor.

The waveguide and the materials used for the prism are the two major differences as compared

with the macroscale setup presented in chapter 2 while the basic sensing mechanisms are the

same. Therefore, the equation to calculate the refractive index of medium being measured is

modified as follows:

Ldnnn icritniticritnitanalyte /sinsin __ (3.1)

where nnit is the refractive indices of the silicon nitride which constitutes the core of the prism-

coupler. prism is a design parameter for the prism selected such that the initial critical point is

positioned appropriately on the CCD for ease of observation.

3.2.2 Fabrication Procedure

In this study, components of the proposed sensor were constructed separately to simplify

fabrication. First the body of sensor which consisted of the prism-coupler and waveguide was

built, and the external light source and photo-detector were assembled separately. Coupling

and alignment of the device were accomplished after all sensor components had been integrated.

As illustrated in Figure 3.3, a two-mask fabrication process was employed to construct

the built-in waveguide with integrated prism. A 2.5 μm-thick silicon dioxide (bottom cladding)

layer and 0.25 μm-thick silicon nitride (core layer) were deposited on a silicon substrate (Fig.

3.3a). The body of the prism-coupler and waveguide were defined with the first mask (Fig. 3.3b),

and the cross sectional area of the waveguide patterned in this step was 4×0.25 mm2. An

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additional 2.5 μm-thick layer of oxide (top cladding) was deposited on the top of the structure

(Fig. 3.3c). The final structure was defined by the second mask and the use of RIE (reactive ion

etching) to create smooth sidewall surfaces and to achieve a good aspect ratio (Fig. 3.3d).

Finally, the end of the waveguide was cut-opened by wafer dicing, and an optional polishing was

applied to reduce the insertion loss in the light signal. The dimensions of the geometry shown

in this section are determined by optical simulations, and this will be discussed in next section.

(a) (b)

(c) (d)

(b’)

(c’)

(d’)

Si

Silicon Dioxide Silicon Nitride

Figure 3.3: Micro fabrication procedures for proposed sensors.

Silicon nitride was used as the core layer because its refractive index is higher than that

of silicon dioxide to guide light into the device. Standard stoichiometric silicon nitride was

deposited using LPCVD (low-pressure chemical vapor deposition), and its refractive index was

2.05.

3.2.3 Design Variations

There are fabrication parameters that must be determined for optimal sensor

performance. One of the most important parameters is the thickness of each cladding and the

thickness of the core of the waveguide, all of which will affect the quality of resultant signal and

light intensity.

The thickness of the core layer in the built-in waveguide determines the number of the

modes of light the device can accommodate. In order to minimize this number to a single mode

of light for a clear resultant signal, the thickness of the silicon nitride core is investigated. In

general, the number of modes is inversely proportional to the wavelength of light source and

proportional to the diameter of core and the numerical aperture of waveguide. As a reference,

number of mode can be simplified as: [18]:

2

/.2

NAcoreofDiaModeofNumber (3.2)

where NA is numerical aperture and is the wavelength of the transmission light source.

Generally speaking, the strength of signal is directly proportional to the thickness of the silicon

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nitride core layer. In other words, the light delivering capacity of the waveguide significantly

depends upon the thickness of the core layer. Therefore, the core layer should be sufficiently

thick both to maintain optimal signal strength and to compensate for the insertion loss at the

entrance of the sensor where the light source is coupled with the waveguide. In this study, the

thickness of the core layer was determined by using the thickness that maximizes intensity of the

light, which can experience attenuation through insertion and propagation loss, within the

geometry of the rectangular waveguide which can allow the single mode of light. Another

fabrication constraint is that the stoichiometric silicon nitride cannot be deposited to a thickness

of more than 250 nm over silicon dioxide without risking the formation of cracks. To avoid

cracking, silicon nitride was deposited to 250 nm in thickness to minimize propagation loss.

The thickness of the cladding layer is another constraint. The cladding needs to be

thick enough to prevent excessive propagation leakage of light into the silicon substrate. Figure

3.4 shows several simulation results by using the optical software: BeamPROP (RSoft Inc.,

USA). The left side of Figure 3.4a is the cross sectional view of the waveguide with simulated

light intensity profile and the right side is the schematic three-dimensional illustration of the

waveguide with core and cladding layer. Figure 3.4b is the simulations result showing a

waveguide with insufficient cladding thickness of 1 m and the light intensity drops to about

0.025 of the original strength about 1000 m away from the entrance point of the original

intensity and continues to drop quickly. Figure 3.4c shows the same simulation with a 2.5 μm-

thick oxide layer and the light intensity is about asymptotic to 0.06 of the original strength at

about 1000 m away from the entrance and afterward. Considering the manufacturing process

that thicker cladding layer will be more difficult in the etching process, 2.5 m is selected as the

thickness of the cladding layer.

The sensor was designed to have a prism of 1, 0.86 and 1.33 mm in length, respectively,

for the exit, input, and exposed edges (as illustrated in Fig. 3.2). Two larger sensors have also

been designed with the same prism angle but larger edges (5 and 10 mm for the input edge,

respectively) to characterize the size effects. Table 1 summarizes the important parameters for

the prototype device.

Table 1: Summary of Microscale Prism-coupler type Sensor for this study

Component Dimension

Cladding thickness 2.5 m

Core thickness 0.25 m

Width of waveguide 4 m

Input edge (3 sensors) 1, 5, and 10 mm

PDMS channel height 200 and 300 m (Chapter 3.3.1)

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Ho

rizon

tal D

irectio

n (μ

m)

Pro

pa

gatio

n D

irectio

n (μ

m)

Pro

pa

gatio

n D

irectio

n (μ

m)

IntensityVertical Direction (μm)

Sin

gle

Mo

de

Lig

ht

Co

re

(a)

(b)

(c)

Cla

dd

ing

Th

ick

ne

ss

= 1

.0 μ

m

Cla

dd

ing

Th

ick

ne

ss

= 2

.5 μ

m

Figure 3.4: Optical simulation results showing coupling of a single mode of light and the

propagation loss during its passage through the waveguide.

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3.2.4 Fabrication Results

The quality of sensing results depends on the quality of fabrication processes including

mask alignment and the smoothness of the surface. Figures 3.5 and 3.6 show the etched

surfaces of the sensing (reflection) and exit edges of the prism and the entrance of the waveguide

into the prism-coupler. These figures show the sub-microscale roughness and the poor quality

of surface roughness at the entrance to the prism-coupler structure. These are the main sources

for the degradation of output light signal. Since the roughness of an etched surface depends

strongly on the etcher and etching recipes, using a higher quality silicon dioxide etcher could

yield a better surface than the general-purpose etcher that was used for this study. Possible

post-processing to smooth the surface could also improve the sensor performance.

Silicon

Dioxide

Silicon

Nitride

Figure 3.5: SEM images of sensing edge of sensor (x3,800 and x13,000).

Silicon

Dioxide

Silicon

Nitride

Waveguide

Entrance

Figure 3.6: SEM pictures of exit edge and waveguide entrance (x10,000 and x370).

In order to reduce light scattering, the exit edge of the prism has been set several tens of

micrometers from the edge of the sensor chip. However, as shown in Figure 3.7, damage to the

edge of the sensor chip is significant to introduce noises in the output signals.

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Chip EdgeChip Edge

Figure 3.7: Edge of sensor beyond exit edge.

A completely fabricated microscale sensor is shown in Figure 3.8a. Figures 3.8b and

3.8c show the measured diffraction and reflection patterns of the light traveling through the built-

in waveguide and prism-coupler. The waveguide and prism-coupler in the figure were

intentionally degraded after deposition processes to make the light path more visible.

Exposed Edge(Reflection Edge)

Waveguide

Prism-coupler

Diffraction

WaveguideReflection

Exposed Edge

(a) (b)

(c)

Figure 3.8: (a) Microscale sensors on a chip, (b) diffraction pattern from waveguide, and (c)

reflection pattern.

3.3 Experiments and Results

3.3.1 Experimental Setup

Microscale sensors are relatively difficult to test compared to macroscale sensors

because the small dimensions of the waveguide entrance. Reliable but complicated optical

components including a laser source and CCD were used in these experiments. As shown in

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Figure 3.9, a laser source was directly coupled with the opening of the built-in waveguide of the

sensor. The wavelength of the light source used was 780 nm because biofilms, which consist of

extracellular polymeric substances (EPS), sediments, and bacteria, are sensitive around this

wavelength [19]. Usually, each of the constituents of the biofilm has different optical

properties, but the mutual absorbance, which can introduce measurement errors, is relatively

small at wavelengths around 780 nm and higher [20, 21]. Furthermore, the reflectance is high

when the wavelength of light is greater than about 700 nm such that the output signal of the

sensor is stronger [22].

Laser Source(λ=780 nm)

CCD

Sensor

in Holder

Figure 3.9: Microscale CPD sensor experimental setup.

As shown in Figure 3.10, a polydimethylsiloxane (PDMS) channel was constructed and

placed on the sensor chip and the exposed edge was in contact with the liquid media. To

prevent leakage, the size of channel was determined in accordance with the viscosity of the

liquid media being measured. For the prototype experiments, a number of analytes including

milk were used as media, and the height of the microchannel was set from approximately 200 to

300 μm. The height of the channel diminishes as biofilms grow thicker during experiments;

therefore it is important to secure a sufficient initial height to prevent the blockage of the supply

of the liquid that contains the biofoulants. To minimize the accumulation of unwanted floating

substances as well as to avoid excessive shearing acting of the biofouling formation, the liquid

media was introduced at a flow rate at 0.1~0.5 ml/hr.

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In Out

Channel

(a) (b)

Figure 3.10: (a) PDMS microchannel on sensor chip; (b) cross-sectional view of the PDMS

channel.

3.3.2 Calibration

In the case of Fraunhofer diffraction, more than 80% of the light intensity concentrates

around the center of the zero-order peak within the range of one eighth of the peak to peak

distance as illustrated in Figure 3.11. The prototype sensor was designed to have the critical

point of the reference material (water) occur within this range which is selected as a main

observation area.

The base angle of the prism, prism, previously illustrated in Figure 3.2, was set to 41°.

This angle is close to the incident light angle of the total internal reflection from the silicon

nitride to the reference material (water) at 40.56º. The main observation area remains adequate

until the refractive index of analyte reaches about 1.4, which corresponds to the incident angle of

43.07º.

15 20 25 30 35 40 45 50 55 60 650

0.2

0.4

0.6

0.8

1

Distance to First Peak

1/8 Distance to

First Peak

Critical Point Shift Direction

Main Observation

Region

Norm

aliz

ed I

nte

nsity

Incident Angle (deg.)

Figure 3.11: Segmented pattern of Fraunhofer diffraction showing the main observation area.

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Once the sensor was tested with water, ethanol was tested, and was used for calibration

purpose. Ethanol is chosen as it can be easily purged or cleaned with water.

3.3.3 Direct Refractive Index Measurement

To illustrate the basic sensing principle as a refractive index sensor, direct refractive

index measurements were undertaken for a number of liquids, including water, ethanol, acetone,

and glycerol. Recorded signals, processed images, and critical points for each of the analytes

are displayed in Figure 3.12. Using the imaging software (Image-pro Plus), the positions of the

critical points are extracted from the output signals. As illustrated in Figure 3.13, the measured

refractive index values were in good agreement with the values in the literature. In this figure

the ―reference line‖ shows the divergence of each measurement for numbers reported in the

literature. In the case of the glycerol measurement, another sensor with a higher designed prism

base angle was used to shift the detection range for the increased refractive index. The error

range of the measurements for four selected media with different refractive indices was less than

± 0.002 R.I.U (Refractive Index Unit).

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Air

Wa

ter

Eth

an

ol

Ac

eto

ne

No

Critica

l Poin

t

Critica

l Poin

t

Critica

l Poin

t

Critica

l Poin

t

Refe

rence

Poin

t

Figure 3.12: Refractive index measurement results for air, water, ethanol and acetone.

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1.32 1.34 1.36 1.38 1.4 1.42 1.44 1.46 1.481.32

1.34

1.36

1.38

1.4

1.42

1.44

1.46

1.48

Refractive Index (literature)

Refr

active I

ndex (

measure

d)

Glycerol (R.I. 1.473)

Ethanol(R.I. 1.359)

Acetone (R.I. 1.360)

Water (R.I. 1.333)

Reference Line

Re

fra

ctive In

de

x (

me

asu

red)

Refractive Index (literature)

Figure 3.13: Experiment results of CPD sensor for different media of known refractive indices.

3.3.4 Biofouling Sensing

Figure 3.14 shows three independent sensor outputs in terms of pixel positions

(beginnings and ends of output profiles) with respect to time during the 9-hour experiment in the

environment of milk and water combination. The downward movements of the TIR critical

points (the top symbols) result from biofouling, and the corresponding change in the refractive

index is as much as 0.0089. Variations between each individual measurement could be due

mainly to the random quality of the biofouling accumulation process as well as fabrication

variations of different sensors [23]. The red curve at the bottom of the figure represents the

average pixel position of the reference point, the leftmost point of the output signal in the inset

picture. The positions of the reference points of individual measurements are indicated by the

symbols in the lower part of the figure. As is evident in Figure 3.14, throughout the duration of

the experiment, there was very little divergence from the reference point. Since the intensity of

the output signal before the critical point is within the region of total internal reflection, the

reference point does not shift. Therefore, this observation verifies that the shifts of critical

point were due to the change of the refractive index on the sensing surface.

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0 2 4 6 8 10 12 14 16 1840

60

80

100

120

140

160

180

200

220

Time (every 30 min.)

Poin

ts in P

ixel

Measurement 1

Measurement 2

Measurement 3

Critical Point

Reference PointPo

sitio

n o

f C

ritica

l P

oin

t (p

ixe

l)

Time (every 30 min.) Figure 3.14: Microscale sensing experiment results of CPD sensor for biofouling formation.

3.4 Discussions

3.4.1 General

The experimentation for this research was designed to be simple and straightforward

because this study is intended to examine the feasibility of a sensing technique. Therefore, the

complicated fabrication process of an integrated light source and photo-detector was not included

in the prototype sensor design. A more elaborate and accurate installation of the sensor

components would be required for further studies. As a result, it was not possible to obtain

exact shape of the output signal from different sensors. However, the general observations as

recorded support the feasibility study from the prototype sensors.

During the calibration process, multiple efforts were made to generate the best output

signal. First of all, the variables associated with the light source including its power and

coupling angle were adjusted to change the quality of output signal. As shown in Figure 3.15, a

parallel coupled light source may cause unexpected signal noises induced by scattering against

the facets of prism body and by the propagation of light through the silicon dioxide cladding.

Therefore, tilting the light source to certain angles provides better signals even though the

intensity of light drops due to the reduction of light intensity resulting from insertion and

propagation loss.

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Propagation through

Top Cladding

Partially Reflected

Figure 3.15: Illustration of coupling light source and its effect at different angles of incidence.

Secondly, a focusing lens was used to compensate low output signal strength by concentrating

the projected light and reducing the spot size of the light. However, manipulation of a light

source coupled with a lens was extremely difficult. Finally, the measurement direction of the

CCD also affects the quality of the output signal. As shown in Figure 3.16, the output signal

that exits the thin silicon nitride core layer is diffracted by the air at the exit edge of the sensor.

The lower parts of the light beam hit the silicon substrate, and the reflection of this light can

contain noises. Furthermore, when other parts of the light beam are reflected by the rough edge

of sensor chip, the noise becomes greater. To avoid these problems and obtain the best image,

optimal angles for positioning the detector had to be determined for the individual sensors.

Diffraction at Exposed

Edge of sensor

Light

Scattering

Figure 3.16: Illustration of secondary diffraction at exit edge of sensor and possible noise

creation at the chip edge.

3.4.2 Tribology

Wear is the process by which material is removed from a solid surface under mechanical

shearing conditions. There are several factors which cause wear, one of which is the impact of

particles of solids, liquids, and even gasses against a solid surface [24]. The rate of wear, or the

wear volume rate, is defined as:

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Hg

vsWkV e

2/' (3.3)

Here, particleofsizeHvfke ,, ; is the effect of particle speed; is the angle factor;

is the effect of material hardness; is abrasive size effect; v is particle velocity; and g

is gravitational constant. The above equation shows that wear is inversely proportional to the

hardness of material and directly proportional to the abundance of abrasive particles on the

surface of interest.

(a) (b)Particle that

causes wear

Figure 3.17: Schematic of erosive wear on (a) a CPD sensor and on (b) an SPR-based (RPD)

sensor.

The metal layer is the essential component of SPR-based sensors; therefore once the

metal layer is partially eroded or unevenly worn, the sensor loses functionality. As shown in

Figure 3.17b, the metal layer used in the SPR sensor, is typically made of gold (Au), which has a

hardness of 150 kg/mm² [25, 26]. Consequently, such sensors are vulnerable to erosive wear

due to their low hardness value. When exposed to harsh environments, the life expectancy of

this type of sensor is shorter than that of CPD sensors, especially when many particles come into

contact with the measuring surface. (e.g. pressurized sea water in desalination plants)

However, the CPD sensor shown in Figure 3.17a, which consists of dielectric materials,

has a higher hardness value, 3.5x10³ kg/mm², than would be found in an SPR-based sensor [27].

Therefore, CPD sensors are less vulnerable to erosive wear.

3.5 Summary

The feasibility of utilizing a planar, integrated critical-point-detection type sensor for

refractive index measurement and biofouling characterization is demonstrated in this chapter.

The CPD sensor for this research presents a novel approach to the usage of Fraunhofer

diffraction and introduces the possibility for conventional prism-coupler type sensors to be

planar and in the microscale. This study details the working principles of sensing mechanism,

design, fabrication and characterizations of the refractive index sensors, including image analysis

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41

and experimental verifications. The CPD sensor for this study utilizes a simple optical design

with a built-in waveguide as a prism-coupler sensor. Furthermore, the fabrication process is

simplified by the utilization of only two masks for the entire fabrication process. Optical

simulation of this sensor architecture and design/fabrication considerations are discussed. The

tribology aspects of the proposed sensor are analyzed. It is predicted this CPD sensor is better

suited for harsh environments due to the superior hardness of their exposed surfaces. Several

liquids have been tested as base-line characterizations for the sensor, and measurements of

refractive indices were in good agreement with the values given by manufacturers (literature)

with error ranges of less than ± 0.002 R.I.U. During the biofouling experiments, the sensor

measured the change of the surface refractive index of a testing liquid (milk), and a shift of as

much as 0.0089 during a 9-hour test due to biofouling has been measured. It is expected that

this sensing technique could find many potential applications, especially, where there is a need

for in-situ, multi-point local characterization of analytes.

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References

[1] E. Hecht, Optics, 4th ed., Reading, Addison-Wesley, 1979.

[2] H. Osterberg and L. W. Smith, "Transmission of Optical Energy Along Surfaces:

Part II, Inhomogeneous Media," Journal of the Optical Society America, vol. 54,

pp. 1078-1079, 1964.

[3] R. Ulrich and R. Torge, ―Measurement of thin film parameters with a prism

coupler,‖ Applied Optics, vol. 12, pp.2901-2908, 1973.

[4] H. Kitajima, K. Hieda, and Y. Suematsu, "Use of a total absorption ATR method to

measure complex refractive indices of metal-foils," Journal of the Optical Society

America, vol. 70, pp. 1507-1513, 1980.

[5] S. F. Nee and H. E. Bennett, ―Accurate null polarimetry for measuring the

refractive index of transparent materials,‖ Journal of the Optical Society America,

vol. 10, pp. 2076-2083, 1993.

[6] S. Patskovsky, M. Meunier, and A. V. Kabashin, ―Phase-sensitive silicon-based

total internal reflection sensor,‖ Optics Express, vol. 15, pp. 12528, 2007.

[7] E. Goormaghtigh, V. Raussens, J. Ruysschaert, ―Attenuated total re£ection infrared

spectroscopy of proteins and lipids inbiological membranes,‖ Biochimica et

Biophysica Acta, vol. 1422, pp. 105-185, 1999.

[8] A. Zhang and P. S. Huang, ―Total internal reflection for precision small-angle

measurement,‖ Applied Optics, Vol. 40, pp. 1617-1622, 2001.

[9] S. Patskovsky, I. Song, M. Meunier, and A. V. Kabashin, ―Silicon based total

internal reflection bio and chemical sensing with spectral phase detection,‖ Optics

Express, vol. 17, pp. 20847-20852, 2009.

[10] J. Homola, Surfaec, ―Plasmon Resonance Based Sensor,‖ Berlin, Springer, 2006.

[11] A. Otto, ―Excitation of nonradiative surface plasma waves in silver by the method

of frustrated total reflection,‖ Zeitschrift fur Physik A Hadrons and Nuclei, vol.

216, pp. 398-410, 1968.

[12] A. S. Barker Jr., ―Direct optical coupling to surface excitations,‖ Physical Review

Letters, vol. 28, pp. 892-895, 1972.

[13] C. C. K. Liua, J. Park, R. Migitaa and G. Qina, "Experiments of a prototype wind-

driven reverse osmosis desalination system with feedback control," Desalination,

vol. 150, pp. 277-287, 2002.

[14] L. WEN-TSO, "Biofilms in water separation membrane processes: From

community structure and ecological characteristics to monitoring and control," in

Civil Engineering, vol. Doctor of Philosophy: National University of Singapore,

2007.

[15] K. Ouazzania and J. Bentama, "A promising optical technique to measure cake

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thickness of biological particles during a filtration process," Desalination, vol. 206,

pp. 36-41, 2007.

[16] X. D. Chen, D. X. Y. Li, S. X. Q. Lin and N. Ozkan, "On-line fouling/cleaning

detection by measuring electric resistance??equipment development and

application to milk fouling detection and chemical cleaning monitoring," Journal of

Food Engineering, vol. 61, pp. 181-189, 2004.

[17] H. Bausera, H. Chmiela, N. Stroha and E. Walitza, "Control of concentration

polarization and fouling of membranes in medical, food and biotechnical

applications," Journal of Membrane Science, vol. 27, pp. 195-202, 1986.

[18] J. Crisp, Introduction to Fiber Optics, 2nd ed., Oxford, Newnes, 2001.

[19] A. W. Decho and T. Kawaguchi, ―Sediment properties influencing upwelling

spectral reflectance signatures: The ‗biofilm gel effect‘,‖ vol. 48, pp. 431-443,

2003.

[20] G. H. Meeten, A. H. North and F. M. Willmouth, "Errors in critical-angle

measurement of refractive index of optically absorbing materials," Journal of

Physics E: Scientific Instruments, vol. 17, pp. 642-643, 1984.

[21] P. R. Jarvis and G. H. Meeten, ―Critical-angle measurement of refractive index of

absorbing materials: an experimental study,‖ Journal of Physics E: Scientific

Instruments, vol. 19, pp. 296-298, 1986.

[22] S. L. Broschat, F. J. Loge, J. D. Peppin, D. White, D. R. Call, and E. Kuhn,

―Optical reflectance assay for the detection of biofilm formation,‖ Journal of

Biomedical Optics, vol. 10, pp. 044027, 2005.

[23] J. Wimpenny, ―Ecological determinants of biofilm formation,‖ Biofouling, vol. 10,

pp. 43-63, 1996.

[24] G. W. Stachowiak, and A. W. Batchelor, ―Engineering Tribology,‖ Burlington,

Elsevier Butterworth-Heinemann, 2005.

[25] J. A. Augis, C. C. LO, and M. R. Pinnel, "The hardness and ductility of sputtered

gold films," Thin Solid Films, vol. 58, pp. 357-363, 1979.

[26] N. Gane and J. M. Cox, "The Micro-hardness of Metals at very Low Loads,"

Philosophical Magazine, vol. 22, pp. 881-891, 1970.

[27] J. Z. Jiang1, F. Kragh1, D. J. Frost, K. Stahl and H. Lindelov, "Hardness and

thermal stability of cubic silicon nitride," Journal of Physics: Condensed Matter,

vol. 13, pp. 515-520, 2001.

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Chapter 4

Resonance-Point-Detection (RPD) Sensing

4.1 Introduction

Surface plasmon resonance (SPR) is an optical phenomenon that occurs when plane-

polarized light reflects against metal under the condition of total internal reflection. Similar to

the CPD sensing technique, this phenomenon may be used for measuring the refractive index of

an analyte at the surface of the sensor. SPR has been studied extensively for several decades,

especially for chemical and biological experimentations due to its outstanding sensitivity.

Ever since the first investigations of surface plasma waves were conducted by Wood in

1902 [1], innumerable experiments have been conducted, a vast body of research has emerged,

and many kinds of optical devices using the phenomenon have been invented. Otto [2] and

Kretschmann [3] independently conducted studies on the optical excitation of surface plasmons

and developed remarkable experimentations. Pockrand et al. [4] introduced the usage of SPR

for the characterization of thin films, while Gordon and Ernst [5] employed the phenomenon to

monitor the condition of metal interfaces. Nylander and Liqedberg [6, 7, 8] conducted notable

research in several investigations for the possible utilization of SPR for gas detection and

biosensing. Biacore International AB, a life science products company, now merged into GE

Healthcare, USA [9], opened up the commercial SPR biosensor market in 1990.

There are several different technological approaches to the utilization of the SPR

phenomenon. Two of the most representative methods are angular interrogation (the

measurement of the change of the resonant angle) and wavelength interrogation (the

measurement of the change of the resonant wavelength at a fixed incident angle) [10]. Most

devices using either of these approaches are based on the prism-coupler method, and

consequently this sensing technology is the most common and widely used in SPR sensing

devices. Decladded optical fiber with a thin, metal layer on top of the exposed area is another

well-known application using the SPR technique, but its lower sensitivity and narrow detection

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range prevent its widespread use.

Despite its exquisite sensitivity, the prism-coupler type SPR sensing technique is not

widely used for microscale applications due to its bulky structure. Instead, other kinds of

sensors such as the waveguide type are commonly used, although the sensitivity and detection

range of this particular sensor are not as good as the prism-coupler method.

This chapter proposes a new sensing technique which enables the microscale prism-

coupler type angular interrogation SPR sensing method, named ―RPD sensing.‖ This

technology employs the CPD sensor structure discussed in Chapter 3. The potential advantages

include possible good sensitivity despite its small device size and the elimination of scanning

operation and time. This simple methodology could find a broad range of applicable for a

variety of small-scale optical measurements

4.2 Theoretical Background

Surface Plasmon Resonance

Surface plasmons are electromagnetic waves on the interface shared by a thin metal film

and a dielectric material. When excited by photons, these surface plasmons propagate in the

direction parallel to such interface. This phenomenon is known as surface plasmon resonance.

The existence of surface plasmon resonance can be demonstrated in the simple procedure as

illustrated in Figure 4.1. Without the metal layer, a total reflection of light occurs, and 100% of

the light is reflected when the incident angle is equal to or greater than the critical angle. When

the interface of the prism and the analyte is coated with a thin film of a noble metal (typically

gold), the intensity of reflected light suddenly drops and then recovers as the angle of incidence

increases. This angle is defined as the Resonance Angle [11].

nmetal n1

Incident

Light Detector

Prism

Feed WaterBiofouling

Metal Layer

n2

SPR

Figure 4.1: Schematic of SPR-based RPD sensor.

This phenomenon is a consequence of the presence of surface charge density waves at

the dielectric/metal interface and has dielectric constants of different signs [12]. A surface

plasma wave (SPW) is an electromagnetic wave, specifically a transverse-magnetic (TM) wave,

that propagates along the interface. The SPW is defined with respect to its electromagnetic

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field distribution and its propagation constant, and the propagation constant, , is expressed by

the following equation:

2

2

dm

dm

dm

dm

n

nkk

(4.1)

where k is the free space wave number, m and d are the dielectric constants of the metal

and the dielectric, respectively, and dn is the refractive index of the dielectric.

When the wave vector of the incident light, kp, matches the wave vector of the surface

charge density waves, ksp, the surface plasmons resonate, and the electromagnetic field of the

SPW is confined at the interface and decays evanescently [13]. This resonance point is usually

displayed as an upside-down peak in the intensity profile of the detector‘s output signal. The

change in the refractive index gives the change of the propagation constant of the SPW

propagating along the metal layer, and this can be detected by monitoring the intensity profile of

output signal [14].

There are several types of sensors to detect the resonance point, and the sensor design

for this study is based on the angular interrogation technique which measures optical signals with

regard to the change of the incident angle. This sensing technology is acknowledged to offer a

higher sensitivity better than other kinds of SPR sensors, and it will be discussed in Section 4.7.2.

4.3 Numerical Simulation

A numerical simulation was conducted to observe the output signal of this sensing

technique, and the light patterns that resulted from the convolution of the diffractions and

reflections of the light affected by SPR were plotted. Figure 4.2 shows the result of a numerical

simulation of analytes (e.g. water containing biofoulants) with different refractive indices. The

solid lines represent convolution patterns, dotted blue lines illustrate the SPR signal, and dotted

red lines illustrate the diffraction of light. As depicted in the these graphs, the peak of the

convolution line is sharp, and the tip of the signal‘s upside-down peak clearly shifts to the right

with respect to the changing refractive indices of the analytes.

Using the resonance angles corresponding to the peak‘s shifting positions, the refractive

index of the analyte was determined and graphed against the incident angles as shown in the

Figure 4.3. The sensitivity of the SPR sensor used in this simulation was acquired from the

slope of the fitting curve to be 90 deg. R.I.U.-1

.

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-25 -20 -15 -10 -5 0 5 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-25 -20 -15 -10 -5 0 5 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-25 -20 -15 -10 -5 0 5 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-25 -20 -15 -10 -5 0 5 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Re

fle

cta

nce

Relative Incident / Offset Angle (deg.)

Δn = 0 Δn = 0.01

Δn = 0.02 Δn = 0.03

Figure 4.2: Results of numerical simulation with different refractive indices.

0 0.005 0.010 0.015 0.020 0.025 0.03040.0

40.5

41.0

41.5

42.0

42.5

43.0

43.5

y = 90.07*x + 40.45

Resonance A

ngle

(deg.)

Refractive Index Change (Δ R.I.U.)

Figure 4.3: Refractive index change versus the angles of the convolution peaks.

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4.4 Working Principle and Design

The basic structure of the RPD sensor used in this study is the same as the CPD sensor

discussed in the preceding chapter. As shown in Figure 4.4a, it differs only in the theory of its

operation and in the shape of the output signal generated. There are several types of SPR

sensors, and one of the most common setups, shown in Figure 4.1, is the Kretschmann

configuration. This type of SPR sensor was chosen for present study because of its prism-

coupler type is equivalent to that of a CPD sensor, and, consequently, such a configuration

requires no structural modification of the CPD sensor setup utilized in Chapter 3.

Laser Source

Coupling

Final

Output

Signal

Core

Cladding

Diffraction

Surface Plasmon

Resonance

Exposed

Edge

Input

Edge

Exit Edge

Thin Metal

Layer

(a) (b)

Biofilm

SPW

Metal Layer

Background Material

Prism-coupler (Sensor)

Figure 4.4: (a) Schematic diagram illustrating RPD sensing mechanism; (b) surface plasma wave

(SPW) formation within metal, biofilm, and background.

In cases where the target analyte or biofouling formation is as thick as the penetration

depth of the SPW (usually several hundreds of nanometers) [14], as shown in Figure 4.4b, the

real part of the propagation constant, , which is explained in Section 4.2.1, is changed by the

refractive index change of the analytes. The relationship between the propagation constant and

the refractive index change is approximately defined as follows:

nkRe (4.2)

where k is the free-space wave number discussed in the previous section in this chapter.

When a light is reflected at the boundary of the metal layer and the prism-coupler, the

evanescent wave propagates along the interface with a constant determined by the incident angle

of light. Therefore, the measured incident angle of the light at the event of resonance (the

resonance point or upside-down peak in Figure 4.2) can give the propagation constant, and,

therefore, the change in the refractive index of the analytes.

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4.5 Microscale Sensor Fabrication

The basic structure of the RPD sensor used this study is the same as the CPD sensor

discussed in the previous chapter. In other words, the structure of the CPD sensor is adopted

for the construction of the RPD sensor. There is only a single additional step required, the

deposition of a layer of metal on top of the sensing (exposed) edge of the CPD sensor.

Figure 4.5 shows the additional fabrication step required for the construction of the RPD

sensor. As shown, photoresist was used to specify the area to be metalized through a lift-off

process. There are two ways to metallize the sensor, but for easy deposition setup, a

metallization of only the reflection edge was conducted and 47 nm of gold (Au) was deposited

with an e-beam evaporator along with a 3 nm titanium adhesion layer. The thickness of the

gold layer was determined by a numerical simulation that will be discussed in Section 4.7.1.

The quality of the metal layer affects the quality of the output signal because the

roughness of the prism‘s reflection edge is critical for this microscale sensor. Figure 4.6 shows

the quality of gold layer deposited on the reflection (sensing) edge of the sensor. As in the

previously fabricated CPD sensor, a sub-microscale roughness has been induced during the

etching process and this would affect the quality of output signal.

Area to be Metalized

Photoresist(a)

(b)

Photoresist

Figure 4.5: Two methods of metalizing the SPR sensor.

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Au on

Silicon Dioxide

Au on

Silicon

Nitride

Figure 4.6: SEM picture of gold layer on the exposed edge of prism.

4.6 Experiments and Results

4.6.1 Experimental Setup

Measurements using an RPD sensor were conducted with a setup that was basically

identical to the one discussed in the preceding chapter. This sensor consisted of the optical

components used in the CPD sensor, and the experimental protocols under which the

experiments were performed were the same. However, since the surface plasma wave (SPW)

used to generate the resonance is a transverse-magnetic (TM) wave, a half-wave plate was added

to the experiment setup to filter light from the laser source in order to achieve an appropriate

polarization state of that light (Figure 4.7).

Laser Source(λ=780 nm)

CCD

Sensor

in Holder

Half-Wave

Plate

Figure 4.7: Experimental setup of RPD sensor.

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4.6.2 Image Processing

The profiles of the measured output signals of an RPD sensor differ from those

generated by a CPD sensor, although the way to find the resonance point (the inverted peak) is

identical. Figure 4.8 shows numerical results that clearly indicate the detection of the resonance

point which is apparent as the position at which the intensity of the output signal dips suddenly.

The flatness of the curve from about 180 pixels to around 300 pixels is the result of a partially

saturated region of the light pattern induced by Fraunhofer diffraction, and the intensity profile in

the region after the resonance point shows effect of the convolution of the diffracted light and the

SPR.

Resonance Point

Figure 4.8: Image analysis process illustrating how to find the resonance point.

4.6.3 Effect of Polarization

General-purpose polarizers do not prove sufficiently precise performance. Therefore,

for accurate measurement, calibration of polarizer is necessary. Figure 4.9 shows changes in

the output signal and the corresponding polarization state of the light wave. In the figure, the

polarizer was set to find the output signal with the sharpest resonance point as a means of

calibration.

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TM mode

TM + TE

TE mode

Resonance Point

Figure 4.9: Image analysis process illustrating the resonance points of different polarization

states of light.

4.6.4 Experimental Results

As was the case with the CPD sensing technique studied in Chapter 3, four different

media were selected and tested. Figure 4.10 shows the measurement of the resonance point of

each medium for this test rather than the critical point as was the case in the earlier examination

of CPD sensing. Figure 4.11 compares the refractive indices obtained from the experimental

results with values in the literature.

Based on its theoretical performance, the RPD sensor was expected to display better

selectivity. However, the actual result shows measurement errors in the range of ± 0.002 R.I.U.

These errors are independent of the SPR-based sensing method and arise from problems with the

alignment of the optical measurement set up as well as fabrication defects and problems in the

resolution of the measurement devices. As discussed in the preceding chapter, the alignment of

the optical devices is among the factors most likely to contribute to error. The incident light

that scatters on the side of the exit edge due to its roughness creates additional difficulties for

precise measurement.

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Water

Ethanol

Acetone

Reference Point

Resonance

Point

Resonance

Point

Resonance

Point

Figure 4.10: Refractive index measurement results for water, ethanol, and acetone.

1.32 1.34 1.36 1.38 1.4 1.42 1.44 1.46 1.481.32

1.34

1.36

1.38

1.4

1.42

1.44

1.46

1.48

Refractive Index (literature)

Refr

active I

ndex (

measure

d)

Glycerol (R.I. 1.473)

Ethanol(R.I. 1.359)

Acetone (R.I. 1.360)

Water (R.I. 1.333)

Reference Line

Re

fra

ctive

In

de

x (

me

asu

red

)

Refractive Index (literature)

Figure 4.11: Experiment results of RPD sensor for media of known refractive indices.

The procedure employed in the CPD sensor test for biofouling discussed in Chapter 3

was utilized in this test. As shown in Figure 4.12, during the 9-hour experiment three

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independent sensor outputs were measured in terms of pixel positions with respect to time. The

downward movements of resonance points (the symbols associated with the blue curve above the

inset) are results of biofouling. The corresponding refractive index change was 0.0078, a value

similar to the test results for the CPD sensor, and as was the case in the previous test, the

reference point did not shift significantly.

0 2 4 6 8 10 12 14 16 18

120

140

160

180

200

220

240

260

280

300

320

Time (every 30 min.)

Poin

ts in P

ixel

Measurement 1

Measurement 2

Measurement 3

Resonance Point

Reference PointPo

sitio

n o

f R

eso

na

nce

Poin

t (p

ixel)

Time (every 30 min.)

Figure 4.12: Microscale sensing experimental result of the RPD sensor test for biofouling

formation.

4.7 Discussion

4.7.1 Design Variations

In addition to the design variations for the CPD sensor discussed in the preceding

chapter, the optimal thickness of the additional metal layer requires investigations. Figure 4.13

depicts the simulation results detailing signal response as a result of SPR based on Equation 4.1

and 4.2. As shown in the figure, 47 nm was found to be the theoretical optimal value for the

thickness of the gold layer [15, 16]. Deep peaks ensure clear detection of resonance point, and

the upside-down peaks (dips in reflectance) at the resonance point observed for other thickness

values were shallower. The actual output signals measured in this study showed somewhat

shallow resonance points. The major cause for this problem was found to be thicker

depositions of gold layer induced by a non-uniform deposition process of evaporator used during

fabrication.

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35 36 37 38 39 40 41 42 43 44 450

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

35 36 37 38 39 40 41 42 43 44 450

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Increasing Au

thickness

47 nm

27 nm

Increasing

Au thickness

47 nm

67 nmR

efle

ctia

nce

Incident Angle (deg.) Figure 4.13: Reflectance variation with respect to the thickness of the gold (Au) layer.

4.7.2 Determination of Sensitivity

The most attractive element of the SPR sensor is its high sensitivity for a wide range of

scientific measurements. Homola et al. conducted notable and practical studies on the

sensitivity of several types of SPR sensors [17, 18]. In their papers, they began with basic

equations, such as Equation 4.1, describing the physical phenomena to mathematically derive

theoretical sensitivities for each case. The theoretically derived sensitivity of prism-coupler

type angular interrogation was determined to be 127 deg. R.I.U.-1

, while other types of SPR

sensing structures such as wavelength interrogation and intensity measurement with prism or

grating coupler-based SPR sensors had relatively lower sensitivities. Under the conditions for

the usage of a goniometer with an angular resolution of 4101 deg. [7], the resolution was

calculated to be 7108 R.I.U. as expressed in following equation:

sensor

component

tmeasuremenS

CRR (4.3)

where tmeasuremenR is the resolution of the measurement, and componentCR and sensorS are the

resolution of the component such as a goniomter, a wavelength modulator or a detector, and the

sensitivity of the sensor, respectively.

For this study presented in this chapter, the theoretical sensitivity of the sensing

technique was numerically derived by simulations, as discussed in Section 4.3. As mentioned

previously, the sensing device utilized here is a prism-coupler type angular interrogation SPR-

based sensor. The sensitivity acquired by the simulation was 90 deg. R.I.U.-1

, which compares

reasonably well to the mathematically derived value from the Homola‘s work. However, unlike

the Homola‘s calculation, since angle scanning is replaced by Fraunhofer diffraction, there is no

angular resolution for this work. Therefore the resolution of the measurement instrument is the

only factor which determines the resolution of the sensing system. Therefore, a resolution of

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the detector is required to be considered in the resolution calculation as it is able to deliver the

best performance to the system. One example of detector resolution is setting a CCD of 5 um-

pixel size placed 5cm apart from the sensor, and this gives approximately 4101 deg. of angular

resolution, which is equivalent to Homola‘s calculations. For this simulation model, the

resolution was calculated to be 6101 R.I.U using Equation 4.3. As expected, the sensitivity

of SPR-based model is comparable to the conventional prism-coupler type angular interrogation

SPR sensor, which has the highest value reported, and it is higher than that of the CPD models

discussed in Section 2.3. Table 2 summarizes the values for the sensitivity and resolution

discussed in this section.

Table 2: Summary of sensitivity study for various sensing techniques.

Sensitivity/Component

Resolution ([] RIU-1) Resolution (RIU) Reference

SPR-based sensor

Angular interrogation

Prism-coupler type

1.27×106 8×10-7

[7, 17]

SPR-based sensor

Wavelength interrogation

Prism-coupler type

4.85×105 2×10-6 [17]

SPR-based sensor

Intensity measurement

Prism-coupler type

5.75×104 2×10-5 [17, 19]

SPR-based sensor

Angular interrogation

Grating-coupler type

4.03×105 2×10-6 [7, 17]

SPR-based sensor

Waveguide type 2×104 5×10-5 [17, 20]

RPD sensor (SPR-based)

Angular interrogation Prism-coupler type

9.0×105 1×10-6

Section 4.3

CPD sensor

Angular interrogation

Prism-coupler type

3.6×105 3×10-6 Section 2.3

4.8 Summary

A prism-coupler type angular interrogation sensor was selected to demonstrate the SPR

devices and modified to remove the bulky rotating light source. This work has led to

significant benefits in size reduction to facilitate possible multi-point measurements. In order to

verify the feasibility and to calculate the theoretical sensitivity of the sensor, a numerical

simulation was conducted. The result indicates that the sensor developed in this study has

sensitivity of 90 deg. R.I.U.-1

. The body of this sensor is based on the CPD sensor in chapter 3

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and the only modification is the deposition of a thin metal layer on the sensing edge at the

interface between the sensor and the analyte. Once the prototype sensor was fabricated,

experiments were conducted with a setup very similar to the one used previously for the

prototype CPD sensor. The experimental results were collected through image processing and

the use of a polarizer. These results were similar to those of the CPD sensing technique.

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References

[1] R. W. Wood, ―On a remarkable case of uneven distribution of light in a diffraction

grating spectrum,‖ Philosophical Magazine, vol. 4, pp. 396-402, 1902.

[2] A. Otto, ―Excitation of nonradiative surface plasma waves in silver by the method

of frustrated total reflection,‖ Zeitschrift fur Physik A Hadrons and Nuclei, vol.

216, pp. 398-410, 1968.

[3] E. Kretschmann and H. Raether, ―Radiative decay of nonradiative surface plasmons

excited by light,‖ Zeitschrift Fuer Naturforschung, vol. 23A, pp. 2135-2136, 1968.

[4] I. Pockrand, J. D. Swalen, J. G. Gordon II, and M. R. Philpott, ―Surface plasmon

spectroscopy of organic monolayer assemblies,‖ Surface Science, vol. 74, pp. 237-

244, 1978.

[5] J. G. Gordon II and S. Ernst, ―Surface plasmons as a probe of the electrochemical

interface,‖ Surface Science, vol. 101, pp. 499-506, 1980.

[6] C. Nylander, B. Liedberg, T. Lind, ―Gas detection by means of surface plasmons

resonance,‖ Sensors and Actuators A, vol. 3, pp. 79-88, 1982.

[7] B. Liedberg, C. Nylander, and I. Lunstrom, ―Biosensing with surface plasmon

resonance-how it all started,‖ Biosensors and Bioelectronics, vol. 10, pp. i-ix,1995.

[8] B. Liedberg, C. Nylander, and I. Lunstrom, ―Surface plasmon resonance for gas

detection and biosensing,‖ Sensors and Actuators A, vol. 4, pp. 229-304, 1983.

[9] Biacore website, www.biacore.com.

[10] H. -P. Chiang, Y. -C. Wang, P. T. Leung, and W. S. Tse, ―A theoretical model for the

temperature-dependent sensitivity of the optical sensor based on surface plasmon

resonance,‖ Optics Communications, vol. 188, pp. 283-289, 2001.

[11] H. L. Lemberg, ―Surface plasmons in liquid mercury: Propagation in a nonuniform

transition layer,‖ Physical Review B, vol. 10, pp. 4079-4099, 1974.

[12] A. Ramanavieius, F. W. Herberg, S. Hutschenreiter, B. Zimmermann, I. Lapenaite,

A. Kausaite, A. Finkelsteinas, and A. Ramanavieiene, ―Biomedical application of

surface plasmon resonance biosensors (review),‖ Acta Medica Lituanica, vol. 12,

pp. 1-9, 2005.

[13] P. Pattnaik, ―Surface Plasmon Resonance,‖ Applied Biochemistry and

Biotechnology, vol. 126, pp. 79 – 92, 2005.

[14] J. Homola, ―Present and future of surface plasmon resonance biosensors, Analytical

and Bioanalytical Chemistry,‖ vol. 377, pp. 528.539, 2003.

[15] B. H. Ong, X. Yuan, S. C. Tjuin, J. Zhang, and H. M. Ng, "Optimized film

thickness for maximum field enhancement of a bimetallic surface plasmon

resonance biosensor," Sensors and Actuators B, vol. 114, pp. 1028-1034, 2006.

[16] P. Lecaruyer, M. Canva, and J. Rolland, "Metallic film optimization in a surface

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59

plasmon resonance biosensor by the extended Rouard method," Applied Optics,

vol. 46, pp. 2361-2369, 2007.

[17] J. Homola, S. S. Yee, G. Gauglitz, ―Surface plasmon resonance sensors: review,‖

Sensors and Actuators B, vol. 54, pp. 3-15, 1999.

[18] J. Homola, I. Koudelab, and S. S. Yee, ―Surface plasmon resonance sensors based

on diffraction gratings and prism couplers: sensitivity comparison,‖ Sensors and

Actuators B, vol. 54, pp. 16-24, 1999.

[19] C. Ronot-Trioli, A. Trouillet, C. Veillas, and H. Gagnaire, ―Monochromatic

excitation of surface plasmon resonance in an optical-fibre refractive-index sensor,‖

Sensors and Actuators A, vol. 54, pp. 589–593, 1996.

[20] A. Trouillet, C. Ronot-Trioli, C. Veillas, and H. Gagnaire, Chemical sensing by

surface plasmon resonance in a multimode optical fibre, Pure and Applied Optics,

vol. 5, pp. 227–237, 1996.

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Chapter 5

Conclusions and Future Work

5.1 Conclusions

The feasibility of prism-coupler type angular interrogation sensing using a planar,

integrated microscale sensor with a built-in waveguide has been investigated with two kinds of

sensing mechanisms, the CPD and RPD sensors. The feasibility of the concept of this sensing

technique was verified through macroscale optical experiments as discussed in Chapter 2. The

microscale sensors, on the other hand, have been designed to be as small as a few hundred of

micrometers, and these small structures are based on the utilization of Fraunhofer diffraction

which is observed at the end of the built-in waveguide. This diffraction is appropriately

positioned and firmly aligned within the sensor, and the built-in waveguide successfully

generates the convolution pattern of the combined diffraction and reflection at the detector

obviating the necessity of a scanner and, therefore, eliminating the time required for scanning.

As explained in Chapter 3, the prism-coupler type of angular interrogation sensing was

applied to a micro-sensor, classified as a CPD sensor. This CPD sensor has been designed and

successfully created through a simple two-mask fabrication process. The results of optical

simulations demonstrate the conceptual working principle of the sensing technique, and provide

a theoretical sensitivity comparable to that of other types of optical sensing methods.

Successful measurement has been conducted, and the results have been substituted into the

governing equations to determine the refractive index of the analytes. During the

measurements of several liquids, the error range has been evaluated at less than ± 0.002 R.I.U.

Although the error range of this prototype sensor is quite large compared to the theoretical

sensitivity, the measurement results are in good agreement with the reported values. A testing

liquid (milk) has been employed to monitor biofouling as a medium of changing refractive index.

The change measured was as much as 0.0089 R.I.U. during a 9-hour experimental duration.

This dielectric optical sensor could find applications in monitoring systems which measure

biofouling under conditions of erosive wearing.

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As has been established in Chapter 4, the prism-coupler type of angular interrogation

sensing method can be applied to a dielectric micro-sensor with a metal layer on top, classified

as an RPD sensor. On the basis of the CPD sensor structure previously studied, an RPD sensor

was designed and fabricated. Optical simulations were conducted prior to the actual

experiments in order to predict the optical responses of the output signals (the pattern of the

convoluted light) as a reference as well as to verify the feasibility of this sensing scheme. The

theoretical sensitivity of this proposed RPD sensing technique has been evaluated, and the

sensitivity of the technique has been determined to be as good as that of the state of the art

sensing method (the goniometer-driven prism-coupler type angular interrogation sensing

method). Several common liquids with different refractive indices have been tested with the

fabricated RPD sensor, and the refractive indices measured are in agreement with the reported

values within an error range of less than ± 0.002 R.I.U. For biofouling formation

characterization, the average refractive index change has been measured as 0.0078 R.I.U. during

a 9-hour experiment. It has been determined that the error range of the sensor is similar to that

of a CPD sensor. However, because this error is mainly the result of a low quality of

manufacturing process, the problem could be solved by refining the sensor-fabrication technique.

In summary, the sensitivity of the RPD sensor could as good as the bulky conventional SPR

sensor, while additional advantages are introduced. The significant reduction of device size and

the elimination of scanning time by this RPD sensor technology could lead to a wide spectrum of

applications, especially in multi-point sensing and mobile sensing devices.

5.2 Future Directions

Throughout this research, the theoretical bases and feasibility of microscale prism-coupler

type angular interrogation sensing techniques utilizing simple prototype sensors have been

examined in order to provide preliminary foundations for future study. In this section, a variety

of advanced applications and the methods of their fabrication as well as advanced sensing

techniques are discussed.

5.2.1 Self Cleaning Sensor using UV and F-IR Ray

Ultraviolet radiation (UV) is known to kill micro-organisms including bacteria [1].

Since the majority of biofouling processes are the results of microorganisms, UV rays can be

used to eliminate the chief cause of this problem [2]. Likewise, the thermal energy of Far-

Infrared (F-IR) radiation could breakdown fouling [3, 4]. When these two forms of radiation

are applied consecutively in a localized area, a significant reduction in the biofouling within that

area can be achieved. Using the UV and F-IR rays in the CPD sensor, the accumulated

biofouling on the surface of the sensor could be removed; hence the sensor could be reset to its

initial condition without the use of removal agents which are often very difficult to apply non-

intrusively. As illustrated in Figure 5.1, the provision of those rays from the exit edge of the

prism will avoid the intensity reduction caused by the waveguide on the input edge of the prism.

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Breakdown of Biofouling

Figure 5.1: Schematic illustrating a strategy to remove biofilm deposition from a sensor using

ultraviolet and far-infrared rays as a means of cleaning.

5.2.2 Integration of Laser Diode and Photo Detector

As discussed in the earlier chapters of this study, the construction of the prototype sensor

was simplified; therefore both the light source and the detector were excluded from integration

into the device during fabrication. To construct complete sensor device unit capable of working

independently, a laser diode [5, 6, 7] and photo-detector [8, 9] must be integrated into the sensor

chip along with the prism-coupler and built-in waveguide. This complete sensor device is

expected to be used directly for multi-point detection for characterization of inhomogeneous

materials in large-scale plants.

The integration of an energy harvester and RF transmitter into a sensor is also possible

for a stand-alone, self-powered device. A possible example is a prism-coupler type angular

interrogation sensor driven by a piezoelectric generator, which emits wireless signals used to

characterize an analyte [10]. For example, in water systems, small water-powered sensors

embedded at multiple points may be employed for monitoring the system (Figure 5.2).

Piezoelectric

Generator Rod

Figure 5.2: Schematic of a self-powered sensing device.

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5.2.3 Measurement of phase difference between s- and p-polarizations

Along with measurement of light intensity, another method for determining the

refractive index of an analyte is offered by the measurement of the phase difference, also induced

by total internal reflection, between s and p polarizations [11]. According to the Fresnel

equation, reflectance, in fact, incorporates two components: the reflectance of the light polarized

with respect to the direction of propagation of electric field (TE, s-polarized); and the reflectance

of light polarized with respect to the magnetic field (TM, p-polarized). The reflectance given in

terms of these discrete values is usually denoted as Rs and Rp, respectively, and given by [12]:

2

2

2

121

2

2

121

sin1cos

sin1cos

ii

ii

s

n

nnn

n

nnn

R

, and

2

2

2

2

11

2

2

2

11

cossin1

cossin1

ii

ii

p

nn

nn

nn

nn

R

(5.1)

To measure the refractive index of an analyte, the phase difference between the s and p-

polarizations of the reflected light is measured by using light sources of differing polarization

states. In such a case, the refractive index can be obtained by substituting the measurement

values into the Fresnel equation. For the sensor used in this study, the comparison of two

output signals obtained at different polarization states can provide information to calculate the

change in refractive index for an analyte.

20 30 40 50 600

0.2

0.4

0.6

0.8

1.0s-polarized

p-polarized

Re

fle

cta

nce

Incident Angle [deg.] Figure 5.3: Response of reflectance in accordance with incident angle for s- and p-polarized light.

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5.2.4 Measurement in Total Internal Reflection Region

The cloudiness of suspended particles in a liquid is referred to as turbidity and is

typically measured through the absorption and scattering of light by the suspended solids. This

sensing method has been traditionally used as a means of monitoring biofilm development [13,

14]. However, the technique is accurate only when the particles suspended in the liquid

medium are homogeneously distributed — an event which has limited the ability of this sensing

method to achieve reliable measurements.

Despite its unsuitableness for accurate measurements of biofouling, the turbidity

measurement is very simple and efficient. The region in the total internal reflection on the

reflectance profile does not change until the critical point appears. In other words, the region

after critical point conserves the original pattern of its diffracted light. Therefore, if there is any

change in the region, it must be due to a change in turbidity between measurements. This

turbidity measurement could be used as a secondary measuring tool for more precise

characterization of analytes.

5.2.5 Digitated Sensor Geometry

-25 -20 -15 -10 -5 0 5 10 15 20 250

0.2

0.4

0.6

0.8

1

Rela

tive I

nte

nsity

Signal Pattern at Shift of 0.04

Relative Angle from Zero Order of Diffraction Pattern

-25 -20 -15 -10 -5 0 5 10 15 20 250

0.2

0.4

0.6

0.8

1

Rela

tive I

nte

nsity

Signal Pattern at Shift of 0.02

Relative Angle from Zero Order of Diffraction Pattern

-25 -20 -15 -10 -5 0 5 10 15 20 250

0.2

0.4

0.6

0.8

1

Rela

tive I

nte

nsity

Signal Pattern at Shift of 0

Relative Angle from Zero Order of Diffraction Pattern

Detector 1

Detector 2

Detector 3

Figure 5.4: Schematic of Three Exit Waveguide sensors and their corresponding points of

measurement on a convoluted light profile.

As the output signal exits the prism, there is a great possibility that the signal will

become weaker or distorted by the external environment between the detector and the exit edge

of the prism. The solution to this problem is to build exit waveguides. As shown in Figure

5.4, three separate exit waveguides are illustrated. Each guide picks up the signals

corresponding to a fixed reflectance angle and only three points appear on the graph as an

example. The exit waveguide encases the output signal up to the detector to prevent weakening

or distortion of the signal [15]. Because only guided signals reach the photo-detector, there

should be less noises resulting from light scattered at the prism‘s exit edge or from outside light.

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Furthermore, there is a good chance that the scattered light at the reflection edge inside the prism

will not fall within the insertion range of the exit waveguides. Therefore, the waveguide itself

could have a filtering capacity. As discussed earlier in this section, it is possible to integrate the

laser diode and photo-detector into the design and it would be straightforward to add the

additional waveguides.

5.2.6 Thickness measurement of SPR-based sensor

During the discussion of the working principle in Section 4.4 (Equation 4.2), only the

case of an analyte or biofilm of thickness comparable to or thicker than the depth of the SPW

field was considered. However, if the thickness of medium to be sensed is much thinner than

the SPW field depth, the propagation constant is expressed as follows:

ndknn

m

dr

Re

2Re

2

(5.2)

where rn is the refractive index of the reference material [16]. This suggests that it may be

possible to discover a way to measure a very small thickness change in a biofouling formation at

the initiation stage of tens of nanometers if the refractive index of the biofilm is provided by

another measuring device such as, for example, a CPD sensor [17].

5.2.7 Sensor using Fresnel diffraction

Theoretically, the smallest dimension of the sensor design used in this study is about 300

μm, the minimum scale at which Fraunhoffer diffraction becomes dominant. If the distance of

light travel is less than 300 μm for this setup, Fresnel diffraction is more significant than

Fraunhoffer diffraction. In such a case, the sensor design must be modified. In the event of

light waves incident upon a diffraction grating, the resultant image as illustrated in Figure 5.5b

(Talbot image) can be acquired when the detector is set at the proper distance from the grating

plane [18, 19]. Figure 5.5a shows the conceptual design of the sensor using Fresnel diffraction

with all aforementioned factors considered.

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

x 10-6

0

0.5

1

1.5

2

2.5

(a) (b)Multi-Angled

Reflection Edge

Figure 5.5: (a) Schematic of conceptual design of sensor using Fresnel diffraction, (b)

corresponding intensity profile.

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In the figure, the prism has edges of multiple angles of decline, and each of the angled

edges corresponds to an individual slit of the diffraction grating. Each ray propagating through

the individual slits is reflected by the angled edge of prism, and the intensity of this reflected

light will indicate the position of the critical point. The governing equation for this principle is

derived as follows:

2

2

121

2

2

121

22

20

sin1cos

sin1cos2

cos2

coscos214

1

,

rr

rr

d

n

nnn

n

nnn

L

xm

L

x

L

zmI

RzxII

(5.3)

where the factors in first bracket specify the influence of Fresnel diffraction, and the values in the

second bracket refer to the influence of the reflected light.

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