design and fabrication of a near-infrared spectroscopy

Meng Yee Ling

systems for sensing applicationsDesign and Fabrication of a near-infrared spectroscopy

Academiejaar 2007-2008Faculteit IngenieurswetenschappenVoorzitter: prof. dr. ir. Paul LagasseVakgroep Informatietechnologie

Scriptie ingediend tot het behalen van de academische graad van

Begeleider: Joost BrouckaertPromotor: prof. dr. ir. Dries Van Thourhout

i

Toelating tot bruikleen

De auteur geeft de toelating dit afstudeerwerk voor consultatie beschikbaar te stellen en de-len van het

afstudeerwerk te copieren voor persoonlijk gebruik. Elk ander gebruik valt onder de beperkingen van het

auteursrecht, in het bijzonder met betrekking tot de verplichting de bron uitdrukkelijk te vermelden bij het

aanhalen van resultaten uit dit afstudeerwerk.

Permission for usage (English version)

The author gives her permission to make this work available for consultation and to copy parts of the work

for personal use. Any other use is bound to the restrictions of copyright legislation, in particular regarding

the obligation to specify the source when using the results of this work.

Meng Yee Ling 6th

June 2008

ii

ACKNOWLEDGEMENTS

I would like to thank the opportunity given to me by the Erasmus Mundus Consortium (EMMP) Master of

photonics for studying in University of Ghent, Belgium. Special thanks to Roel Baets, Geert Morthier and

Dave Steyaert for the welcoming stay in Belgium. This has been an extraordinary learning experience that I

will cherish for life.

I would also like to thank my promoter Dries Van Thourhout and my supervisor Joost Brouckeart for being

so magnanimous throughout my learning experience. They have been extremely considerate, especially

generous in providing me advice and constant guidance during my project. I have gained invaluable

knowledge, and even more, patience and determination.

My gratitude also goes to all members of INTEC department for their hospitality and help. Special thanks

goes to Steven Verstuyft for helping me with the metallization and electroplating processing work in the

cleanroom, Peter Geerinck for the wirebonding of detectors, Jeroen Allaert for the electronics board design

and implementation, Iwan Moreels and Professor Dirk Poelman for near infrared absorption experiments. I

am greatly indebted with their expertise, guidance and kindness.

Last but not least, to my beloved family and friends, thank you for instilling faith, hope and joy in me. They

are my pillar of strength and inspiration. The journey could not have been better, without you.

iii

ABSTRACT

The project presents the design and fabrication of a spectrometer-on-a-chip based on a photonic integrated

chip (PIC) with a planar concave grating (PCG) and metal-semiconductor-metal (MSM) photodetectors

integrated on the silicon-on-insulator (SOI) waveguides. The planar concave grating (PCG) is the

wavelength demultiplexer of the spectrometer system which diffracts and focuses the incident light into 30

output waveguide channels with a spectral resolution of 3.2nm. The subsequent optical signals of each

output waveguide are detected by InAlAs/InGaAs MSM photodetectors integrated on top of these output

waveguides.

The spectrometer chip is glued onto a ceramic package with the MSM photodetectors wire bonded to

package. The package is further mounted onto an electronic circuit board. The board contains switches and

a transimpedance circuit to convert the photocurrent to a voltage output. Two biasing schemes have been

presented for MSM and PIN detectors respectively. The MSM detectors are tested and experiments showed

a 0.06 A/W responsivity at 1570nm with an internal responsivity is 0.71 A/W. Photocurrent read out from

the MSM detectors resembles the fibre coupler response. The transimpedance circuit introduces an error of

5% in voltage output for photocurrent in the range of 10nA to 10µA.

Design and fabrication of a near-infrared spectroscopy

system for sensing applications

Meng Yee Ling

Supervisor: Ir. Joost Brouckaert, Promotor: Prof. Dr. Ir. Dries Van Thourhout

Abstract- We present the design and fabrication of a

spectrometer-on-a-chip based on a photonic integrated

circuit (PIC). This PIC is fabricated on a silicon-on-insulator

(SOI) substrate and the main components are a planar

concave grating (PCG) and heterogeneously integrated

InGaAs metal-semiconductor-metal (MSM) photodetectors.

The PCG acts as a wavelength filter and is fabricated with

deep UV lithography. It diffracts and focuses the incident

light into 30 output waveguide channels with a spectral

resolution of 3.2nm. The optical signals of the 30 channels

are then detected by the 30 MSM detectors integrated on top

of the output waveguides. The detectors are wire bonded

onto a package and the corresponding photocurrents

generated are converted into electrical read out signals by a

custom designed printed circuit board.

Keywords – Near infrared spectroscopy, planar concave

grating, MSM photodetector

I. INTRODUCTION

Conventional Near infrared (NIR) spectroscopy systems are

big and bulky lab equipments which have to be contained in

a stationary location. They are also expensive and require

costly technical maintenance. They offer extensive range of

wavelength measurements and usually exceed the

requirements of industrial applications.

Here we introduce the spectrometer-on-a-chip which

can operate as a miniature NIR spectrometer at lower cost.

The spectrometer is based on planar concave grating (PCG)

which acts as wavelength diffraction component and metal-

semiconductor-metal (MSM) photodetectors.

The operation of the spectrometer is discussed in

section II, followed by the wire bonding and packaging in

section III and finally experiment results in section IV.

II. OPERATION OF THE DEVICE

The optical signal is injected from a single mode fibre onto

the spectrometer chip via a fibre coupler [1]. An silicon-on-

insulator (SOI) waveguide will then route the light to the

PCG.

The PCG used in this chip is a 30 channel wavelength

filter which acts as a demultiplexer grating defined by

completely etching through the 220nm thick silicon layer. It

yields a free spectral range (FSR) of 115nm and an

operational wavelength range spanning from 1500nm to

1600nm. The corresponding 30 output channel response is

spaced 3.2nm apart with a FWHM of 1nm [2].

There are 30 InAlAs-InGaAs MSM detectors integrated on

top of the 30 output waveguides [3]. These detectors each record

signals of different wavelength region of the dispersed spectrum.

The photocurrent generated will be proportional to the input

optical power.

III. WIRE BONDING AND PACKAGING

A. Wire bonding

A mask is designed for metallization of Ti/Au (20nm/200nm)

Schottky contacts on the detectors. There are 30 MSM

photodetectors on top of the 30 output waveguide channels.

Since the output waveguides are spaced 25µm apart, we need to

design a fan out from the detector contacts to a bigger wire bond

contacts. The big wire bond contacts are 250µm x 250µm to

accommodate aluminium wire (32µm) bonding.

The metallization is done with lithography and deposition of

Ti/Au aligned onto the underlying MSM detectors. The thickness

of Au (200nm) is not sufficient for wire bond and electroplating

(KAuCn2) is used to add the thickness of the wire bond contacts

(3-5µm) as shown in figure 2.

Figure 2: Added thickness on the wire bond contacts.

The spectrometer chip is the glued onto a PGA 68 ceramic

package. Aluminium wires are bonded onto the package and

then to the contacts on the chip via ultrasonic bonding. The

results can be seen in Figure 3.

Figure 3: Wire bonding process and final product.

B. Electrical read out circuit

A bias voltage is supplied to the MSM detectors to sweep

out the carriers generated. The photocurrent will then be

converted to a voltage reading by a transimpedance circuit.

The basic electrical read out configuration is as in figure 4.

Figure 4: Schematic for electrical read out circuit.

We use CMOS analogue switches to sequentially

switch the photocurrents from the detector to the

transimpedance circuit. The digital switching is done via

parallel port with Labview interface vi.

IV. EXPERIMENTS

A tunable laser is used as a light source. Under no

illumination, the dark currents of the 30 MSM detectors are

measured for a bias voltage from -6V to 6V. We would

expect a dark current of 4nA to 10nA [3]. With a

comparison, we found out that 15 detectors are functioning.

Among 15 faulty detectors, 8 are suspected to be short-

circuited showing extremely high dark currents while others

are disconnected (very low dark currents).

By tuning the laser to the peak transmission of each

detector, the I-V curve for different optical power of input

fibre is measured. The external responsivity of the detectors

measured at a bias voltage of 6V is calculated from the I-V

curve and plotted in figure 5.

External responsivity of detectors

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

R ext (A/W)

Figure 5: External responsivity of detector 9 to 23.

Since the detectors circuit from 1570nm onwards are

not functioning, it is difficult to compare the whole response

to the response of the fibre coupler and the transmission

grating. However, the responsivity of the detectors is

observed to increase from 1520nm to 1570nm which agrees

with the fibre coupler response.

On-chip loss (Planar concave grating) of the spectrometer is

approximately 4.6 dB at 1570nm and the coupling loss at

1570nm is 6dB. The insertion loss is thus approximately 10.6dB.

From experiment, the external responsivity, Rext of detector 23

(1570nm) is 0.062 A/W. Internal responsivity, Rint is calculated

as waveguideoutputP

fibreinputPRR extInt

__

__*= . For the transmission at

1570nm, the internal responsivity is 0.71 A/W.

Photocurrent versus wavelength plot

0.E+00

1.E-02

2.E-02

3.E-02

4.E-02

5.E-02

6.E-02

7.E-02

8.E-02

9.E-02

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

Photocurrent (m

A)

det 23

det 22

det 21

det 20

det 19

det 18

det 17

det 16

det 15

det 14

det 13

det 12

det 11

det 10

det 9

Figure 6: Optimised photocurrent versus wavelength plot.

Under a constant optical power of input fibre (1mW) and

tuning the laser to the peak transmission of each detector, the

photocurrent is plotted as in figure 6. The electrical board

photocurrent read out of the detectors showed that the peak

wavelength response of detectors agrees with the PCG response

with a resolution of approximately 3.2nm.

However, the crosstalk of the photocurrent read out from

the electronic circuit is approximately -11dB. This crosstalk has

increased from the crosstalk of -25dB before the packaging of

the spectrometer. The reason for this might be due to the losses

introduced during the packaging such as the metallization, wire-

bonding and electrical board circuit read out. All this processing

steps could introduce on chip losses.

V. CONCLUSION

A spectrometer on a chip connected to an electronic read

out board is presented. The responsivity of the detectors is

measured and the photocurrent of the detectors is measured with

the electrical circuit board.

VI. REFERENCES

1. D. Taillaert , F. V. Laere, M. Ayre, W. Bogaerts, , D. V.

Thourhout, P. Bienstman and R. Baets, “Grating couplers for

coupling between optical fibers and nanophotonic waveguides,”

Japanese Journal of Applied Physics, Vol. 45, No. 8A, pp. 6071-6077,

2006.

2. J. Brouckaert, W. Bogaerts, P. Dumon, D. V. Thourhout and R. Baets,

“Planar Concave Grating Demultiplexer Fabricated on a Nanophotonic Silicon on Insulator Platform”, J. Lightwave technology, Vol. 25, No. 5,

pp. 1269-1275, 2007.

3. J. Brouckaert, G. Roelkens, D. V Thourhout and R. Baets, “Compact InAlAs-InGaAs Metal Semiconductor Metal Photodetectors Integrated on

Silicon on Insulator Waveguides”, IEEE Photonics Technology Letters,

Vol. 19, No. 19, pp. 1484-1486, 2007.

iv

Contents

CHAPTER 1 Introduction 1

1.1 Near Infrared (NIR) spectroscopy background physics………………………………………. 1

1.1.1 The harmonic oscillator……………………………………………………………… 2

1.1.2 The anharmonic oscillator……………………………………………………………. 3

1.2 Beer Lambert’s Law…………………………………………………………………………… 4

1.3 Conclusion……………………………………………………………………………………… 5

CHAPTER 2 Aim of Project 6

CHAPTER 3 Miniaturized Near Infrared Spectrometers 8

3.1 Grating based spectrometer…………………………………………………………………….. 9

3.1.1 Aluminium grating spectrometer……………………………………………………… 10

3.1.2 Planar double grating spectrometer…………………………………………………… 11

3.1.3 Waveguide concave grating spectrometer…………………………………………….. 12

3.2 Design and operation of spectrometer chip of the project………………………………………12

3.2.1 Fibre coupler………………………………………………………………………… 12

3.2.2 Planar concave grating………………………………………………………………… 13

3.2.3 Metal-semiconducto-metal (MSM) photodetectors…………………………………… 14

3.3 Comparisons of miniature spectrometers………………………………………………………..15

CHAPTER 4 Absorption experiments and Calibration 16

4.1 Measurement of water content in ethanol……………………………………………………… 16

4.1.1 Preparation of samples and experiment setup………………………………………… 16

4.1.3 Spectra of water ethanol mixtures……………………………………………………... 17

4.2 Measuring blend levels of biodiesel with conventional fuels…………………………………... 18

4.2.1 Preparation of samples and experiment setup…………………………………………. 19

4.2.2 Spectra of blends levelsof biodiesel with conventional fuel…………………………... 19

4.3 Calibration of absorption spectrum…………………………………………………………….. 20

4.3.1 Univariate Analysis: Single Wavelength calibration…………………………………..20

4.3.1.1 Prediction in univariate analysis……………………………………………... 21

4.3.2 Multivariate Analysis: Principle Component Analysis (PCA)………………………... 21

4.3.2.1 Predictions in PCA…………………………………………………………… 22

4.3.3 Error analysis………………………………………………………………………….. 25

4.4 Analysis of Results …………………………………………………………………………….. 26

4.4.1 Univariate calibration:water ethanol mixtures………………………………………… 26

4.4.2 PCA calibration: water ethanol mixtures……………………………………………… 27

4.4.3 Univariate calibration: blend levels of biodiesel with conventional fuel……………… 30

4.4.4 PCA calibration: blend levels of biodiesel with conventional fuel……………………. 31

4.4.5 Comparisons of univariate analysis and PCA analysis……………………………….. 33

4.4.6 Advantages of Principle Components Analysis (PCA)……………………………….. 33

v

CHAPTER 5 Planar Concave Grating responses 34

5.1 Planar concave grating…………………………………………………………………………. 34

5.1.1 Crosstalk………………………………………………………………………………. 35

5.1.2 -10dB Crosstalk……………………………………………………………………….. 36

5.1.3 -20dB Crosstalk……………………………………………………………………….. 37

5.1.4 Grating response of the spectrometer…………………………………………………... 38

5.2 Limitation………………………………………………………………………………………. 39

CHAPTER 6 Wire Bonding and Electrical Read-Out 40

6.1 Layout of MSM detectors ……………………………………………………………………… 40

6.1.1 MSM photodetector metallization mask………………………………………………. 41

6.1.2 PIN photodetector metallization mask………………………………………………… 42

6.1.3 Metallisation processing steps………………………………………………………… 43

6.1.4 Wire bond test………………………………………………………………………… 46

6.2 Electrical read-out board………………………………………………………………………... 48

6.2.1 Schematics of voltage read out circuit………………………………………………… 48

6.2.1.1 MSM photodetector board…………………………………………………… 49

6.2.1.2 PIN photodetector board……………………………………………………... 50

6.2.2 Selection of electronic components…………………………………………………… 50

6.2.3 Error in output voltage reading………………………………………………………... 52

CHAPTER 7 Experiments on Spectrometer-on-a-chip and the electrical board 54

7.1 Measuring the dark current of the detectors……………………………………………………. 54

7.1.1 Experimental results…………………………………………………………………… 55

7.1.2 Defects of detectors…………………………………………………………………… 56

7.2 Measuring the responsivity of the detector……………………………………………………... 57

7.2.1 Experimental results…………………………………………………………………… 57

7.3 Measuring the output current and voltage from the printed circuit board……………………… 60

7.3.1 Crosstalk………………………………………………………………………………. 62

7.3.2 Voltage reading from printed circuit board………………………………………….... 63

Conclusion and perspective 65

Appendices 66

References 72

List of Figures 74

List of Tables 77

vi

List of Symbols

k force constant

m mass

h Plank constant

I1 transmitted light intensity

I0 incident light intensity

c concentration of the sample

l optical path length

ε molar extinction coefficient

NIR near infrared

PIC photonic integrated chip

SOI silicon on insulator

MSM metal-semiconductor-metal

PCA principle component analysis

λ wavelength

ηext external quantum efficiency

R responsivity

q coulomb charge

v frequency of incident light

1

CHAPTER 1

Introduction

1.1 Near Infrared (NIR) Spectroscopy background physics

Spectroscopy is a study of interaction of light waves with matter. When light radiates on the object of interest,

it will be absorbed, transmitted or scattered. Hence, by comparing the light properties before and after

penetrating through the sample, information about the sample could be obtained. Near infrared (NIR)

spectroscopy is a measurement technique based on absorption of matter using light in near infrared region,

780µm to 2500µm.

At room temperature, the atomic bonds of matter (solid, liquid or gas) vibrate at lowest energy state or

otherwise at fundamental frequencies. When near infrared light illuminates on the matter, the atom-to-atom

bonds will feel this incident photon energy. If the energy or frequency of the photon matches the energy needed

to excite the molecules to higher energy state (overtones and combination vibrations), this photon will be

absorbed by the molecules.

This absorption further leads to a low transmission at the corresponding photon energy (frequencies). Thus, by

analysing the spectrum of light after penetration of a sample, we could identify the molecular bonds which

possess those particular vibration frequencies.

Different molecules have different bonding strength and hence different vibrational frequencies. This renders

each molecule a unique body with different identification. Therefore, near infrared spectroscopy is popular for

qualitative analysis and quantitative measurements of functional groups of OH, CH, NH and CO and has been

widely adapted as a sensor in many industrial applications, i.e. pharmaceutical, food and beverages etc.

In the coming section we will study in brief the physics that governs the vibrational frequencies of atomic

bonds, followed by Beer Lambert’s Law which is used to relate absorbance to concentration of samples.

Chapter 1 Introduction

2

1.1.1 The Harmonic Oscillator

At room temperature, molecules vibrate in the least energy state allowed. By assuming Hooke’s Law and

deriving from the vibration of a diatomic harmonic oscillator, we can calculate the lowest or fundamental

frequencies of any two atoms connected by a chemical bond.

Figure 1.1. Diatomic oscillator with masses m1 and m2.

Consider a diatomic oscillator model in figure 1.1 with vibrating masses m1 and m2, the vibrational frequency

vo is [1]: m

kvo π2

1= ------------Eq. (1)

where k is the force constant of the bond, m is reduced mass of the two atoms

21

21

mm

mmm

+= .

Although the reduced masses of molecules such a CH, OH and NH are quite similar, the fundamental

vibrational frequencies between them would differ due to different bond strength, k and length [1].

Instead of continuous energy levels as predicted by the classical model, quantum mechanics has shown

otherwise that there are only several discrete vibrational energies, En that are allowed.

+=

2

1nhvE on ; ...2,1,0=n ------------Eq. (2)

where h is the Plank’s constant.

For polyatomic molecules, we can treat them as a series of diatomic, independent, harmonic oscillators.

Equation 2 can then be generalized as [1]:

hvnnnnEN

i

i )2

1(,...),,(

63

1

321 += ∑−

=

; ...)2,1,0,...,,( 321 =nnn ------------Eq. (3)


3

A nonlinear molecule containing N atoms will have 3N − 6 vibrational degrees of freedom, while a linear

molecule has only 3N − 5. These vibrational degrees of freedom correspond to the number of fundamental

vibrational frequencies of the molecule.

Energy levels are equidistant for harmonic oscillator model and the selection rule only allows transitions

between neighbouring energy levels such that 1±=∆n [1]. At room temperature, most molecules populate the

ground level, n =0. Transitions from ground state to n=1 is termed as the fundamental transition.

1.1.2 The Anharmonic Oscillator

In molecules, electron clouds and the charges of nuclei of the two bound atoms will impose a limit during

compression step, hence creating an energy barrier. On the other hand, when the stretch of electron clouds

exceeds the bond restoring ability, the bond will break and thus the vibrational energy will reach the

dissociation energy (figure 1.2) [1].

It is also observed that the energy levels in anharmonic oscillator are not equal as in the harmonic oscillator

model. The energy levels become closer as the vibrational energy increases [1]. The energy levels are modified

to be:

2

2

1

2

1

+−

+== nvnvhc

EG oo

nn χ ------------Eq. (4)

where c is the speed of light and χ is the anharmonicity constant.

Figure 1.2. Energy diagram of an ideal diatomic oscillator and anharmonic diatomic oscillator.


4

In the anharmonic oscillator model, the selection rules loosen up to include transitions to more than one energy

level. Apart from the fundamental modes, vibrational transitions corresponding to ,...3,2 ±±=∆n are also

allowed. These additional transitions are called first, second, and so forth overtones [1].

Besides the overtones, combination bands are also observed where the vibrational transitions are the sum and

difference of fundamental and overtone bands. Near infrared region is filled with overlaps of overtone and

combination bands.

1.2 Beer Lambert’s Law

Beer Lambert’s Law relates the absorbance of light to the concentration of the samples. The law states that the

reflected or transmitted light through a substance is dependent on the chemical (molecular absorbance),

physical (scattering/reflective) properties of the sample and optical path length traversed.

Figure 1.3. Transmission through sample contained in a cuvette.

Transmission of light, T through a liquid sample can be defined as the ratio of transmitted light intensity to

incident light intensity: lcc

I

IT εα −− === 1010

0

1 ------------Eq. (5)

where I1 is the transmitted light intensity, I0 is the incident light intensity, c is the concentration of the sample, l

is the optical path length and ε is the molar extinction coefficient1.

Absorbance for liquids is then defined as:TI

IA

1loglog 10

0

110 =

−= ------------Eq. (6)

Overall, absorbance of a liquid sample can be stated as lcA ε= ------------Eq. (7)

1a measure of how strongly a chemical species absorbs light at a given wavelength.


5

1.3 Conclusion

Near infrared spectroscopy operates in the region of 780µm to 2500µm and is based on molecular overtone and

combination vibrations.

Generally, overtones and combination bands have a much lower intensity than fundamental modes in the mid

infrared region. Hence the molar extinction coefficient in the near infrared region is small. This results in a

lower sensitivity of the probing system. However, this also allows near infrared light to penetrate much further

into the sample and this is particularly useful for probing samples with little to no preparation as compared to

mid infrared spectroscopy.

We have also seen the Beer Lambert’s law which relates the absorption of a material to the concentration of the

absorptive element. This relation will be used to analyze concentration of liquids in subsequent near infrared

absorption measurement.

6

CHAPTER 2

Aim of Project

The goal of the project is to design and fabricate a miniaturized Near Infrared (NIR) spectroscopy system based

on a planar concave grating (PCG) on a silicon on insulator (SOI) photonic integrated chip (PIC). This PIC

consists of a fibre coupler, a planar concave grating and InGaAs metal-semiconductor-metal (MSM)

photodetectors heterogeneously integrated on top of the outgoing SOI waveguides.

Figure 2.1: Schematic view of spectrometer on a chip.

Figure 2.1 shows a schematic view of the spectrometer-on-a-chip design. Light is first coupled into the chip via

a fibre coupler. The light is the guided to the planar concave grating (PCG) demultiplexer which separates and

focuses the light into 30 different wavelength channels. 30 InGaAs MSM photodetectors are integrated on top

of the 30 output waveguides to measure the optical power in the 30 different wavelength channels respectively.

Fibre coupler

grating

Planar Concave

Grating

MSM detectors

Ti/Au wire bond

pads

Aluminium wire

bond

Single mode

fibre

Ceramic

package

SOI platform

Chapter 2 Aim of Project

7

Now, the project will focus on converting the light signals detected by the detectors into electrical output

signals. These electrical output signals (current or voltage) will be a proportional to the optical power detected

by the MSM photodetectors.

The proposed read out mechanism is to package the spectrometer on-a-chip by gluing it onto a ceramic

package. The 30 MSM photodetectors is wire bonded onto the ceramic package contact pads and the package is

mounted onto an electronic circuit board. This board contains switches and a current to voltage converter

(transimpedance circuit) to produce linear voltage read out that corresponds to the photocurrent of the detector.

The 30 detectors will be sequentially biased by controlling the switches and the corresponding voltage will be

read out using a multimeter. The control of switches is done from a computer and the output voltage of

transimpedance circuit is read out on a multimeter which is synchronised to the computer.

The final product of the project would be to produce a miniature spectrometer with electrical output readings

from the detectors.

The next chapter will start with information of present miniature spectrometers and comparing it with the

spectrometer-on-a-chip of this project. Chapter 4 will be on absorption measurements and calibration. Chapter

5 will be on crosstalk analysis of the planar concave grating responses. Then we will proceed to the design of

wire bonding and electronic board. Finally, the thesis will include the experiment on characterization of

photodetectors and the read out of photocurrent from electronic board.

8

CHAPTER 3

Miniaturized Near Infrared Spectrometer

Conventional Near infrared (NIR) spectroscopy systems are big and bulky lab equipments which have to be

contained in a stationary location. They are also expensive and require costly technical maintenance. These

equipments offer extensive range of wavelength measurements and the performances usually exceed the

requirements of industrial applications. Therefore a NIR spectrometer which is smaller, easier to maintain

while performs in the specific wavelength of interest is much desirable.

Having said so, miniaturized near infrared (NIR) spectrometers have been realized over the past few years to

better suit some of the industrial needs. New generations of miniaturized optical spectrometers involves

microfabrication of optical components and subsequent assembly on a micro-optical platform. The dimension

of spectrometers can be further reduced with nano-scale integration of photonics components on a silicon on

insulator (SOI) platform.

In the coming section we will discuss some of the work conducted by research groups to produce miniaturized

spectroscopy systems. Following the review, we shall introduce the design and operation of the spectrometer-

on-a-chip of this project.

Spectrometers are usually classified by their wavelength selection/filter method and among the popular

wavelength filter devices are gratings, interferometers and prisms. Here, we shall only discuss the grating based

spectrometers.

Chapter 3 Miniaturized Near Infrared Spectrometer

9

Grating based spectrometer

Figure 3.1: Basic grating configuration.

A grating based spectrometer uses a grating to filter light into different wavelengths. As can be seen in figure

3.1, the incident light passes though an opening slit and is collimated by a mirror or lens. The light is then

diffracted into different spectral components upon illuminating on the grating. The diffracted wavelength

spectrum will depend strictly on the grating resolution and design.

Different wavelengths will be focused and scanned successively onto the exit slit by rotating either the grating

or the output focusing mirror. The incident light can then be analysed by studying the wavelength components

of the distributed spectrum.

3.1.1 Aluminium grating spectrometer

Kong et al. reported an aluminium grating spectrometer integrated on a silicon wafer [4]. The infrared

spectrometer consists of two independently processed silicon wafers. The first wafer contains the aluminium

grating while the second wafer contains the thermopile based detector array. Two wafers are bonded using a Si-

Si low temperature fusion bonding technique.

Figure 3.2: Schematic structure of the aluminium grating spectrometer [4].


10

Figure 3.2 shows the incident light is diffracted by the aluminium grating. Then, it propagates through the

silicon substrate and it is detected by an array of polysilicon thermopiles. Silicon is transparent for wavelengths

exceeding 1µm and thus is suitable as a platform for the near infrared optical path.

Polysilicon thermal detectors are implemented in this design due to the inability of silicon to detect infrared

light. They also require no electrical biasing and are reported to be easier to fabricate [4]. However, the system

requires a chopper to modulate the light beam because the thermal detectors do not respond to continuous

radiation.

The device reported a detectable wavelength range of 13µm for a silicon optical path for a 4µm grating

constant [4].

3.1.2 Planar double grating spectrometer

Grabarnik et al. reported a miniature spectrometer built from two flat diffraction gratings. In this design, the

second grating provides compensation of aberrations introduced by the first grating.

The spectrometer works in reflection mode with two glass wafers aligned parallel facing each other. The light

is first reflected from a stripe mirror which also acts as a slit. Then the reflected light undergoes twice

diffraction upon impinging on grating 1 and 2. The light further passes through the glass and is recorded by the

detector.

Figure 3.3: Schematic view of compact planar spectrometer [5].

The device is mounted on the surface of a charge coupled device (CCD) sensor that records the light spectrum.

The operating wavelength range is from 450nm to 750nm giving a 300nm visible bandwidth. The spectral

resolution is reported to be 3 nm and the device is 3 x 3 x 11 mm3 in size [5].


11

Figure 3.4: The experimental set up of compact planar spectrometer [5].

3.1.3 Waveguide concave grating spectrometer

Figure 3.5: Waveguide concave grating spectrometer [6].

Mohr et al. reported a planar grating spectrograph based on 3 layer resist polymer waveguides. The 3 layer

resist consists of 50µm thick core of polymethylmethacrylate (PMMA) with n1 =1.49 and 17.5µm thick

cladding layers of copolymer composed of methlmethacrylate (MMA) and tetrafluorpeopylmethacrylate

(TFPMA) with n2 ranging from 1.49 to 1.425.

Optical fibres are adjusted to couple light into the polymer waveguide in horizontal direction by structuring

fixed fibre grooves. The light is then diffracted by the self focusing reflecting grating fabricated on the polymer

by deep-etch X-ray lithography. The diffracted spectrum is then focused and projected onto 10 optical fibres

that further channel the spectral components to a photodetector array.

The device area is 18 x 6.4mm2 and the operation wavelength range is from 720nm to 900nm with a spectral

resolution of 20nm [6].


12

3.2 Design and operation of the spectrometer chip of the project

The spectrometer-on-a-chip of this project has similar operating principles as the waveguide concave grating

spectrometer mentioned in section 3.13. However, we have utilise the high refractive index difference of SOI

waveguides (nsilicon=3.47, nsilicon_oxide = 1.44) and also integrated on-chip photodetectors instead of output fibres

fixed on the grooves connected to detectors. This greatly reduces the size of the spectrometer.

The spectrometer chip of the project consists of fibre coupler, planar concave grating and InGaAs

photodetectors integrated on silicon on insulator (SOI) platform. Silicon on insulator (SOI) platform consists of

a layer of 220nm thick silicon on top of a 1µm thick oxide layer on a silicon substrate. The large refractive

index difference between the silicon and silicon oxide layer enables very compact integration of optical

waveguides and components.

In this project, light is coupled onto the spectrometer chip from free space via a fibre coupler. The light

propagates through photonic wire waveguides and diffracted by the planar concave grating onto 30 output

waveguide channels. The optical signals of 30 channels are detected by 30 InGaAs metal-semiconductor-metal

photodetectors respectively. The following section will briefly explain the workings of each optical component

on the spectrometer chip.

3.2.1 Fibre coupler

Due to the large mismatch of the mode size of a typical single mode fibre with a diameter of 9um and a single

mode waveguide with a cross-section of 0.1um2, there will be huge losses of optical power when trying to

couple light directly from one to the other [10]. Therefore, a fibre grating coupler is used to efficiently couple

light onto the chip.

Figure 3.6: Diffraction grating layout for fibre to waveguide coupling [10].


13

The coupler grating operates on the Bragg diffraction principle whereby the incident light waves interfere with

the scattered light wave to form constructive interference, θλ sin2dm = , where m is the diffraction order, λ is

the incident wavelength, d is the grating pitch and θ is the incident angle.

The input single mode fibre is titled at 10 degrees incidence angle to operate in first order Bragg diffraction

from the grating. The first order diffracted light is then coupled into the 12µm broad ridge waveguide. This

light further propagates through the tapered waveguide into a narrow photonic wire with a width of 500nm

which is formed by etching completely through the 220nm thick silicon layer. The peak coupling efficiency of

the fibre coupler is 30% (-5.2dB) at 1550nm and the 1dB bandwidth is approximately 40nm [10].

Figure 3.7: Coupling efficiency for fibre coupler with air interface and 630nm grating pitch[10].

3.2.2 Planar concave grating (PCG)

This light from the photonic wire propagates in a slab mode when the wire opens up to the unetched free

propagation region (FPR) of the planar concave grating (PCG). The PCG is designed based on conventional

Rowland geometry and is able to diffract light and to focus the light into a series of output waveguides [12].

Figure 3.8: Planar Concave Grating based on Rowland configuration [12].


14

The Planar concave grating used in this chip is a 1x 30 demultiplexer defined on a SOI wafer with a silicon top

layer of 220nm and a buried oxide layer of 1um [12]. The grating is defined by completely etching through the

220nm thick silicon layer. The input diffracted light by the grating can be focused onto the circumference of

the Rowland circle with a reflection angle,di θθθ −= , where θi is the incident angle with respect to the centre

of the circle, θd is the diffracted angle with respect to the centre of the circle This is further determined by using

the grating equation ( )eff

din

mdλ

θθ =+ sinsin , where d is the grating pitch, m is the order of diffraction, λ is the

free space wavelength and neff is the effective refractive index of the slab mode.

The design of the grating on the chip yields a free spectral range (FSR) of 115nm and the 30 output channels

range from 1500nm to 1600nm. The corresponding 30 output channel response is spaced 3.2nm apart with a

FWHM of 1nm.

Following the diffraction, different wavelengths are re-focused onto the 30 output waveguides and are detected

by photodetectors integrated on top of the waveguides. III-V photodetectors are integrated on SOI waveguides

due to the transparency of silicon to infrared lights of >1µm.

3.2.3 Metal-semiconductor-metal (MSM) photodetectors

Figure 3.9: Schematic view of waveguide integrated MSM detector [13].

Due to its high absorption, InGaAs are good semiconductor material to be used as near infrared light detectors

especially for the telecommunication wavelength region, 1330nm to 1550nm. The composition of InxGa1-xAs

can be tailored to yield a bandgap absorption wavelength from 800nm to 2600nm.

Metal-Semiconductor-Metal (MSM) detectors are defined by bonding unprocessed InAlAs-InGaAs dies onto

processed SOI waveguide wafer using low temperature divinyl-disiloxane benxocyclobutane (DVS-BCB)

bonding process [13]. The InP substrate is then removed and the photodetectors can be further defined on a

wafer-scale and lithographically aligned with respect to the underlying SOI waveguides [13].


15

No fibre couplers are needed as in the case for PIN photodiodes and directional coupling of light from

waveguide to the detector is achieved.

In0.53Ga0.47As is used as the active absorption layer in the detector. A thin layer of InAlAs is implemented

between the Ti/Au schottly contacts and InGaAs active layer to raise the Schottky barrier to prevent leakage

current (dark current). There is a 20nm InAlAs-InGaAs digital graded superlattice layer to decrease the

bandgap discontinuities between InAlAs and InGaAs absorption layer [13]. Two Schottky electrodes (Ti/Au)

are further deposited on top of the thin film detector to provide biasing contacts while at the meantime create a

lateral confinement for underlying waveguide [13].

The reported detector has a responsivity of 1.0 A/W at a wavelength of 1.55um and low dark current of 4.5nA

[13].

3.3 Comparisons of miniature spectrometers

Brief comparisons are made between the miniaturized spectrometers mentioned previously:

Device

Dimension

Operating

spectral range

Spectral

resolution

Remarks

Aluminium grating

spectrometer

(Year 2001)

Not reported

grating pitch of

4um, wavelength

range < 4um (air)

Not

reported

Grating pitch limits the

spectral resolutions

Planar double grating

microspectrometer

3 x 3 x 11 mm3

450nm – 750nm

3nm

Non coplanar optical path.

Stray light problems

Waveguide concave

grating spectrometer

(Year 1991)

18mm x 6.4mm

720nm – 900nm

20nm

No integrated detectors on

chip

Planar Concave

grating spectrometer

(SOI chip used in this

experiment)

6x3mm2

1500nm-1600nm

3.2nm

Planar structure and no

moving parts

Table 3.1: Comparison of grating spectrometers.

16

CHAPTER 4

Experiments and calibration

We are interested to measure absorbance of material in the near infrared region which could subsequently be

measured by the grating spectrometer on a chip of this project. In this chapter, we will conduct two absorption

measurements: measuring the water content in ethanol and blend levels of biodiesel with conventional diesel.

These two measurements yield distinguishing absorbance bands in the near infrared range from 1400nm to

1700nm.

Once the absorbance spectrum is obtained, there are several calibration techniques that can be used for spectral

analysis. We will look at the shortcomings of univariate analysis and then proceed to the multivariate analysis

method, Principle Components Analysis (PCA) for generating calibrations for future predictions of analyte

concentrations.

4.1 Measuring the spectrum of water ethanol mixtures

4.1.1 Preparation of samples and experiment setup

We prepare a calibration set of water ethanol mixtures by mixing pure compounds. 10 samples of de-ionized

(DI) water with concentration from 0% to 20% with increase step of 2% in ethanol were prepared.

Figure 4.1: Cuvette holder used in experiment.

Chapter 4 Absorption experiments and Calibration

17

The liquid samples were contained in a plastic cuvette holder with an optical path length of 1cm. SMA

multimode fibres are used as transmission fibres. The transmission spectra of the samples were then measured

with an Optical Spectrum Analyser (OSA) with resolution setting of 2nm. A superluminescence broadband

Light Emitting Diode (SLED) with centre wavelength at 1500nm is used as the light source. The SLED

spectrum is recorded as in figure below.

Superluminescence LED spectrum

-45

-35

-25

-15

1450 1500 1550 1600 1650

wavelength

dB

m

Figure 4.2: SLED output spectrum.

The transmission spectra of the liquid samples were recorded in a wavelength region from 1450nm to 1600nm

and further converted into absorbance spectra using the formula, onTransmissi

Absorbance1

log=

4.1.2 Spectra of water ethanol mixtures

The transmission spectra of samples are collected and normalized with respect to an empty cuvette

transmission spectrum. The spectra are further normalized with the pure ethanol transmission spectrum and

converted to absorbance spectra.

1460 1480 1500 1520 1540 1560 1580 1600

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Absorbance spectra of water mix ethanol ethanol100

water2

water4

water6

water8

water10

water12

water14

water16

water18

water20

Ab

so

rba

nce

wavelength (nm)

Figure 4.3: Transmission through different water ethanol mixtures contained in a cuvette.


18

Figure 4.3 shows the recorded absorbance of samples in the wavelength range of 1450nm to 1590 nm. The

water absorption at 1450nm increases with increasing concentration of water in ethanol. This absorption is

caused by the first overtone band of the OH stretching mode in the infrared region (3450 cm-1

x2 =6900 cm-1

=

1450nm) [14].

Another absorption band at 1580 is also observed. However, this OH overtone peak is attributed from the OH

bond from ethanol as well as from water. Thus, we will only analyse the water concentration by taking into

account the peak at 1450nm.

1460 1480 1500 1520 1540 1560 1580 1600

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Relative Absorbance of water mix ethanol

water2

water4

water6

water8

water10

water12

water14

water16

water18

water20

Re

lative

Ab

so

rba

nce

wavelength (nm)

1460 1480 1500 1520 1540 1560 1580 1600

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Gaussian Fit Relative Absorbance

water2

water4

water6

water8

water10

water12

water14

water16

water18

water20

Re

lative

Absorb

ance

wavelength (nm)

Figure 4.4:.Normalised absorbance curve of water ethanol mixtures (left) and gaussian fit curve (right).

Figure 4.4 shows the normalised absorbance of different samples with respect to pure ethanol. The noisy

spectra are due to the use of multimode (SMA) fibres in the experiment to couple the light in and out of the

cuvette. Thus before generating the calibration, the spectra are smoothed by a Gaussian fit and the

corresponding absorbance curve is shown on the right graph.

We can be concluded that the absorbance increases as the water content in ethanol increases. The peak

absorbance is noticed to be at 1450nm.

4.2 Measuring blend levels of biodiesel with conventional fuels

It is becoming more crucial to develop a method that can accurately, rapidly monitor the blend levels of

biodiesel with conventional fuel at a reduced cost. Near infrared spectroscopy has potential to fill these

requirements due to ease of sample handling [15].


19

4.2.1 Preparation of the samples and experiment setup

We prepared a calibration set of different blend levels of biodiesel with conventional fuels by mixing pure

compounds. 10 samples of biodiesels with concentration from 0% to 100% with increase step of 10% in

conventional fuel were prepared.

The transmission spectra of the samples were recorded with a CARY 5000 UV-VIS-NIR photospectrometer by

Varian. Using the Cary WinUV software, we recorded transmission spectra of the liquid samples from 1400nm

to 2400nm with grating resolution set at 1nm.

4.2.2 Spectra of blend levels of biodiesel with conventional fuel

Normalised Absorbance of Biodiesels blend levels with

conventional fuel

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1651 1653 1655 1657 1659 1661 1663 1665 1667 1669

wavelength (nm)

Ab

so

rba

nc

e

Biodiesel 10%

Biodiesel 20%

Biodiesel 40%

Biodiesel 60%

Biodiesel 80%

Biodiesel 90%

biodiesel 100%

Biodiesel 30%

Biodiesel 50%

Biodiesel 70%

Figure 4.5: Normalised absorbance spectrum of different blends of biodiesel in conventional fuel.

Figure 4.5 shows the normalised absorbance spectra of biodiesels with respect to conventional diesel fuel in the

wavelength range from 1651nm to 1670 nm. This region demonstrated an increase in absorbance with respect

to increase of biodiesel blend levels in conventional diesel.

This region will be included in the calibration range to predict the blend levels of biodiesel, in this case the

methyl soyate with the petroleum derived diesel fuel.


20

Blend levels of biodiesel in conventional fuel

0.1

0.11

0.12

0.13

0.14

0.15

0.16

0.17

0.18

0.19

0.2

1900 1910 1920 1930 1940 1950 1960

wavelength (nm)

Transmission %

diesel_100%

DF_9_BIO_1

DF_8_BIO_2

DF_7_BIO_3

DF_6_BIO_4

DF_5_BIO_5

DF_4_BIO_6

DF_3_BIO_7

DF_2_BIO_8

DF_1_BIO_9

biodiesel_100%

Figure 4.6: Transmission spectrum of different blends of biodiesel and conventional fuel.

Another region to distinguish the blend levels is observed around 1930nm. This region can be included in the

calibration technique for the prediction. However, as can be seen in figure 4.6, the transmitted signal is very

low and this poses a limit to the sensitivity of the calibration system.

4.3 Calibration of absorption spectrum

It is important to generate a calibration equation that relates the concentration of analyte to the optical data we

recorded. This is to provide an interpretation and also a means to predict future samples.

4.3.1 Univariate Analysis: Single Wavelength calibration

The analyte concentration versus wavelength relationship could be deduced at the peak of the absorbance band.

Figure 4.7: Error free single absorbance band [1].


21

In a simplified and idealized model, the height of the absorbance peak is strictly proportional to the

concentration of the analyte. Taking unity path length of 1cm and substituting in Beer’s law, we have:

CA ε=

where A is the absorbance, ε is the molar extinction coefficient and C is the concentration of analyte. We will

rearrange the equation above in terms of absorbance because we are interested in concentration. The inverse

Beer’s Law is thus AC 1−= ε or rather bAC = , where the inverse molar extinction coefficient 1−ε is a

constant and now replaced by b . The graph for the univariate analysis at wavelength of choice can then be

plotted as in figure 4.8.

Figure 4.8: Calibration line in univariate analysis [1].

Linear Regression is used to find the best fit line across all the points. This line is called the calibration line and

has the equation 110ˆ AbbC += , where C is the concentration of analyte, 0b is the intercept from the

regression, ib is the regression coefficient at wavelength i and iA is the corresponding absorbance.

4.3.1.1 Prediction in univariate analysis

The calibration line we obtain at the chosen wavelength is used for future prediction of the analyte

concentrations. For samples with an unknown analyte concentration, the absorbance at the chosen wavelength

is substituted on the calibration equation and the corresponding water concentration can be calculated.

4.3.2 Multivariate analysis: Principle Components Analysis (PCA)

In multivariate analysis, the spectrum that relates to the change in analyte concentration is analysed at more

than one wavelength.


22

Figure 4.9: Absorbance band of multivariate case (more than one wavelength) [1].

Often there are absorbance band overlaps at the spectral peak as is shown in figure 4.9. In this situation, the

peak absorbance accounts for absorbance from different chemical bonds. In this case, there is a need to include

more wavelengths in the calibration.

Other reason on why univariate analysis is insufficient is due to the peak absorbance shifting caused by

hydrogen bonding, refractive index shifts or other physical parameters. This renders the chosen peak

absorbance wavelength unsuitable to generate a linear calibration line as per Beer’s Law. Therefore, more than

one wavelength has to be included for calibration to yield a better result.

There are several popular multivariate analysis method such as Multiple Linear Regression (MLR), Partial

Least Squares (PLS) and Principle component analysis (PCA). However, only PCA will be use to analyse the

results.

4.3.2.1 Predictions in PCA

Principle Component Analysis (PCA) is a mathematical technique which constructs an approximation to the

absorbance spectrum to be predicted. PCA generates new axes to define the data. These axes are generated with

the intention of plotting the data in terms of maximum variance. In other words, when plotted against the new

axis, the data has a maximum variance from the axis [1].

The steps to PCA analysis are as below. More detailed understanding of PCA can be found in literature [1].

a. Obtain optical data

In the experiment, n spectra are obtained for a range of wavelengths. For example in the figure 4.10, 4 samples

of different analyte concentration from 1450nm to 1600nm are measured. This yields n = 4 number of spectra,

m number of wavelength points.


23

Figure 4.10: Example of 4 absorbance spectra for a m wavelength points.

b. Subtract the mean

A mean spectrum for the 4 spectra is calculated, mXXXX ,...,, 321

. Then for each of the 4 spectrums, we

subtract the mean spectrum. This results in a new mean subtracted optical spectrum for the 4 samples.

iii XXXmean −=_ ; for i = 1,2,3….m.

c. Calculate the cross product matrix and the sum of cross product matrix

A m x m cross product matrix is created from each spectrum (n spectra = n matrices). The i,j th term in the

matrix corresponds to the product of mean subtracted absorbance at i th wavelength, and the mean subtracted

absorbance at j th wavelength. )_)(_(),(_ ji XmeanXmeanjiprodX = ; for i, ,j = 1,2,3….m.

The sum of cross product matrix is thus just the summation of all cross product matrices.

∑=

=n

k

kprodXprodXsum1

___

d. Calculate the principle components

The principle components, PC are the eigenvectors of the sum_X_prod matrix. This gives:

[ ][ ] [ ]prodXsumkprodXsumPC ____ = , where X = sum_X_prod matrix, PC is the eigenvector and k is the

eigenvalue.

The eigenvectors with corresponding large eigenvalues accounts for maximum variance in data points due to

effects of real physical phenomena on the spectra. Since we are interested in the difference of spectra with

relation to changes in analyte concentration, we shall choose the eigenvectors that with large eigenvalues.

These eigenvectors are then arranged in descending order. For mathematical reason, the number of

eigenvectors, p included has to be equal or smaller than the lesser of n and m. eigenvectors with very low


24

eigenvalues can be discarded without compromising the prediction analysis. Hence, data compression is

achieved here.

This set of newly selected and arranged eigenvectors (p x m matrix) are called the principle components (PC).

The eigenvectors are new axes that characterize the data. Now we have to transform the data such that they are

expressed in terms of the eigenvector axis.

e. Calculate the scores of Principle Components

The scores (S) are calculated as, ( ) dataAbsorptionOpticalPCSi __∗= . The scores are related to the concentration

as ...ˆ22110 +++= SbSbbC , where ib are the calibration coefficients. We can then obtain the calibration

coefficients with mulitlinear regression fitting [1].

f. Calculate coefficients of optical data

We retain the calibration coefficients, ib and the principle components, PC used to create the calibration. We

will now relate the scores and the calibration coefficients to the optical data.

Since score are defined as ...2211 ++= APAPS iii , where Aj is the optical data for the jth wavelength and Pji

is the value of the ith principle component at the jth wavelength. Substituting Si into concentration equation, we

obtain ( ) ( ) .........ˆ232322212113132121110 +++++++++= APbPbPbAPbPbPbbC .

This can be further simplified as ...ˆ22110 +++= AkAkbC --------------------------Eq (4.1)

where km is the coefficients of the optical data Am.

g. Perform prediction calculations

After obtaining all the optical data coefficients, b0 and km, the absorbance spectrum, Am (m wavelengths data

points) can be directly substituted into the equation 4.1 to give a predicted concentration. Figure 4.10 below

shows the flow of PCA analysis.

( )

•

•

•

•

•

•=

mp

m

m

m

pp PC

PC

PC

PC

PC

PC

PC

PC

PC

PC

PC

PC

PC

.

,3

,2

,1

2,

2,3

2,2

2,1

1,

1,3

1,2

1,1

..... Descending order of eigenvalues


25

Figure 4.11: Principle Component Flow Chart [1].

4.3.3 Error analysis

The error, e is defined as the difference between the predicted concentration, C and the reference concentration,

C . CCe ˆ−= . The root mean square error (RMSE) will be used to compare the performances of calibration

models: ( )

∑=

−=

n

i

ii

n

ccRMSE

1

2ˆ

, where n is the number of samples[1].


26

4.4 Analysis of Results

4.4.1 Univariate calibration: water ethanol mixtures

Univariate analysis: water ethanol mixtures at

1450nm

y = 0.0905x - 0.0274

0%

5%

10%

15%

20%

25%

0 0.5 1 1.5 2 2.5 3

Absorbance

% w

ate

r concentr

atio

n

Figure 4.12: Univariate calibration line calculated for water ethanol mixtures at 1450nm.

Figure above is a plot of percentage of water concentration in ethanol versus the absorbance at 1450nm for

each sample. The calibration set consists of 10 ethanol samples with 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%,

18% and 20% of water concentration. After fitting with partial least regression in excel, the calibration line

obtained gives 0b = -0.0274 and 1b =0.0905.

Referring to the inverse Beer’s Law equation, 110

ˆ AbbC += , we will plot the predicted water concentration

versus the known reference water concentration in ethanol by using the newly obtained calibration equation,

10905.00274.0ˆ AC +−= . Table 4.1 shows the reference value versus the prediction value calculated.

Reference

water concentration

Predicted

water concentration

2 % 1.52 %

4 % 4.69 %

6 % 4.84 %

8 % 8.80 %

10 % 10.47 %

12 % 12.44 %

14 % 14.59 %

16 % 16.73 %

18 % 16.27 %

20 % 19.61 %

Table 4.1: The univariate prediction table of water ethanol mixtures.


27

Univariate analysis:

Prediction concentration versus known

concentration for water ethanol mixtures

R2 = 0.9780

5

10

15

20

25

0 5 10 15 20 25

known water concentration %

pre

dic

ted %

Figure 4.13: Prediction versus known water concentration in ethanol mixtures at 1450nm.

The root mean square error, RMSE (see 4.3.3 Error Analysis) is 0.85% and the correlation coefficient is 0.978.

Correlation coefficient, R2 is a measure of how well the data fits the regression line with R

2=1 being the best

fit. The error calculated assumed the test samples are prepared with no error. However, the samples are

prepared with an uncertainly of ± 0.1ml yielding an error of 1% in 10 ml sample.

4.4.2 PCA calibration: water ethanol mixtures

Now we will proceed with multivariate analysis of water ethanol mixture. The generation of principle

components (PCs) are done with Matlab and the generation of calibration coefficients from the scores of PCs

are done with Excel linear regression fit.

Principle components are calculated and the corresponding eigenvalues are plotted as in figure 4.13. PCs with

large eigenvalue are retain for further calibration. This greatly reduces the data dimension and barely

compromises the calibration accuracy. Eigenvalues that has low values and plateau to a constant do not

contribute to the efficiency of the calibration and are not included.

Eigenvalues generated from the sum of cross product

matrix for water ethanol mixtures

-10

40

90

140

0 50 100 150

eig

env

alu

es

Figure 4.14: Eigenvalues of calculated from the sum of cross product matrix.


28

It is observed here that there is one single eigenvalue which has a very high value, nearly 140 times higher than

other eigenvalues. Including PCs with such low magnitude eigenvalues <1, would not contribute to the

performance of the prediciton. In this case, we retained only one set of principle component knowing that it

does not compromise the prediction and this greatly reduces the data dimension. The scores for each sample are

then calculated as: ( ) ( )m

m

i AAAAA

PC

PC

PC

PC

PC

S ••∗

•

•

•= 4321

4

3

2

1

where Si is the scores for ith sample and PCm is the set of principle components and Am is the absorbance of

optical data for whole range of wavelength, m. Figure 4.15 plots the Scores for each sample calculated based on

the principle component retained.

Water Ethanol Mixtures: Scores of

principle components plot

y = 0.0149x - 0.03

0%

5%

10%

15%

20%

25%

0 5 10 15 20

Scores

%w

ate

r concentr

ation

Figure 4.15: Plot of concentration of water in ethanol versus Scores.

The linear regression fit gives a calibration coefficient 03.00 −=b and 0149.01 =b . These calibration

coefficients will be retained together with the principle component to generate optical data coefficients that

cover the whole range of the spectrum (m wavelengths).

•

•∗+=

•

•

mm PC

PC

PC

bb

k

k

k

2

1

10

2

1


29

This is very convenient towards future prediction of sample concentrations because the optical spectrum

obtained can be directly substituted with the optical data coefficients to calculate the concentration. There will

be no wavelength selection as in univariate case to generate a prediction.

( ) ( )mi AAAAAtscoefficiendataopticalC ••∗= 4321__

We can now predict the water concentration in ethanol by multiplying the spectrum (A1, A2, A3,… Am) for each

sample with the newly obtained optical data coefficients (b0,, k1, k2, … km) as shown by the relation above.

PCA Reference

water concentration

Predicted

water concentration

2 % 1.34 %

4 % 4.83 %

6 % 4.78 %

8 % 8.88 %

10 % 10.60 %

12 % 12.73 %

14 % 14.42 %

16 % 16.92 %

18 % 16.16 %

20 % 19.29 %

Table 4.2: The PCA prediction table of water ethanol mixtures.

PCA analysis:


concentration for water ethanol mixtures

R2 = 0.9715

0%

5%

10%

15%

20%

25%

0% 5% 10% 15% 20% 25%


pre

dic

ted

%

Figure 4.16: Prediction versus known water concentration in ethanol mixtures using PCA.

The Root mean square error (RMSE) is 0.96% and the correlation coefficient is 0.9715.


30

4.4.3 Univariate calibration: blend levels of biodiesel with conventional fuel

The same steps as in previous section are repeated for biodiesels blend levels analysis.

Univariate analysis: Biodiesel blend levels at 1664nm

y = 347.58x - 2.1105

0

20

40

60

80

100

120

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Normalised Absorbance

% B

iodie

sel

Figure 4.17: Calibration line calculated for biodiesel conventional fuel mixtures at 1664nm.

Figure 4.17 is a plot of the percentage of biodiesel in conventional diesel versus the absorbance at 1664nm for

each sample. The calibration set consists of 10 conventional fuel samples mixed with 10%, 20%, 30%, 40%,

50%, 60%, 70%, 80%, 90% and 100% of biodiesel. After fitting with partial least regression in excel, the

calibration line obtained gives 0b = -2.1105and 1b =347.58.

From the calibration line, predictions of samples are carried out:

Univariate prediction of

Biodiesel %

Reference %

10 7.76

20 20.93

30 30.16

40 40.11

50 51.07

60 60.88

70 71.84

80 79.41

90 89.01

100 98.80

Table 4.3: The univariate prediction table of biodiesel blend levels.


31

Univariate analysis:


concentration for Biodiesel blend levels

R2 = 0.9983

0

20

40

60

80

100

120

0 50 100


pre

dic

ted

%

Figure 4.18: Prediction for biodiesel conventional fuel mixtures at 1664nm.

The root mean square error (RMSE) is 1.18% and the correlation coefficient is 0.9983.

4.4.4 PCA calibration: blend levels of biodiesel with conventional fuel

In the multivariate analysis for biodiesel blend levels, the principle component with the largest eigenvalue is

retained for further calibration.

Eigenvalues (Principle components) for

biodiesel blend levels

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

-4 1 6 11 16 21

eig

en

va

lue

s

Biodiesel blend levels:

Scores of principle components plot

y = 121.67x - 0.7222

0

20

40

60

80

100

120

0 0.5 1

Scores

%b

iod

iese

l

co

nce

ntr

atio

n

Figure 4.19: Plot of eigenvalues of PC (left) and plot of scores (right) for biodiesel blend levels.

This will give a plot of one dimensional Scores plot as seen in figure 4.20 (right).


32

Biodiesel blend levels:

Scores of principle components plot

y = 121.67x - 0.7222

0

20

40

60

80

100

120

0 0.5 1

Scores

%b

iod

iese

l

co

nce

ntr

atio

n

Figure 4.20: Plot of biodiesel concentration in conventional fuel versus Scores.

The linear regression fit gives a calibration coefficient 7222.00 −=b and 67.1211 =b . This coefficient is

retained together with the principle component to generate the full spectrum optical data coefficients using the

same way as before.Prediction is carried out by multiplying the spectrum with the optical data coefficients.

PCA prediction of Biodiesel % Reference %

10 7.76

20 20.93

30 30.16

40 40.11

50 51.07

60 60.88

70 71.84

80 79.41

90 89.01

100 98.80

Table 4.4: The PCA prediction table of biodiesel blend levels.

PCA analysis:


concentration for Biodiesel blend fuel

R2 = 0.9988

0

20

40

60

80

100

120

0 50 100

known biodiessel concentration %

pre

dic

ted

%

Figure 4.21: Plot of prediction value versus reference value of biodiesel concentration in diesel.

The Root mean square error (RMSE) is 1.00% and the correlation coefficient is 0.9988.


33

4.4.5 Comparisons of Univariate analysis and PCA analysis

An overall listing of the Root mean squared Error (RMSE) of both calibration methods:

Water ethanol mixtures Biodiesel mix fuel

Univariate analysis 0.85% 1.18%

PCA analysis 0.96% 1.00%

Table 4.5: Comparisons of analysis method.

Overall, biodiesel blend level measurements exhibit higher error as compared to water ethanol measurement

due to the large blend level range 0-100% tested. If the blend level is restricted to smaller range as in ethanol,

0-20%, the corresponding error would also decrease.

Principle component analysis (PCA) and univariate analysis of data show similar accuracy for the

measurements conducted above. However, univariate analysis is usually not preferred due to its wavelength

selection limitations. The error of the univariate analysis would also increase when analysing complex

absorbance band due to shifts of absorbance peak.

4.4.6 Advantages of Principle Components Analysis (PCA)

There is no need for a wavelength selection in calibration as is required in univariate analysis and multilinear

regression technique (MLR) [1]. It is relatively easier to obtain more precise results with the help of computer

calculations of principle components.

Since the coefficients of optical data calculated have the same dimension as the number of wavelengths in the

spectrum, it is easy to just relate the entire optical spectrum obtained and predict the analyte concentration [1].

34

CHAPTER 5

Planar concave grating responses

The planar concave grating (PCG) is the wavelength demultiplexer of the spectrometer-on-a chip. In this

chapter, we will study the effects of the resolution and the crosstalk of the PCG demultiplexer. Several grating

transmission spectrums with different crosstalks are compared.

5.1 Planar concave grating (PCG)

The transmission spectrum of the 30 channel Planar Concave Grating demultiplexer is plotted in figure 5.1. By

replacing each of the grating facet with a distributed Bragg reflector (DBR), the on-chip loss is decreased from

6.3dB down to approximately 3dB.

Figure 5.1: Grating transmission spectrum of 30 channels PCG demultiplexer.

The spectral peaks of each output channel are spaced approximately 3.2nm apart spanning from 1502nm to

1594.8nm. The loss of the peak transmission is approximately -3dB with full width half maximum (FWHM) of

the channels is around 1nm. The crosstalk between channels is better than -20dB.

Chapter 5 Planar Concave Grating responses

35

The transmission spectrum of the central wavelength (1550nm) channel is used as a model transmission

spectrum for all 30 channels spaced at 3.2nm apart. This newly generated transmission spectrum for all 30

channels will be used as a grating transmission reference in subsequent crosstalk simulations.

Figure 5.2: Newly generated grating transmission spectrum of the 30 channel PCG demultiplexer.

5.1.1 Crosstalk

Crosstalk is the signal that is undesirable and ideally does not belong to the channel. Crosstalk signals appear as

side lobes to the transmission spectrum and are reproducible from channel to channel. Comparing to the

transmission of optical slab modes without the grating, it is certain that the side lobe structure is due to the

errors in the grating[18]. Thus, crosstalk is highly dependent on the accuracy of the grating definition. In

reality, grating facets deviates from the ideal position and produces phase errors between each facet and its

neighbours. These phase errors further introduce sidemodes and deteriorate the channel spectra [18].

Figure 5.3 (pink curve) shows the ideal response which does not record any crosstalk signals whereas the blue

curve recorded crosstalks of signals outside the ideal spectral range.

grating response of single channel

-50

-40

-30

-20

-10

0

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

real

ideal

Figure 5.3: Qualitative spectrum view of the ideal channel response and the real channel response.


36

Different crosstalk values are compared to have an idea on the influence on the output waveguide signals.

These output waveguide signals will be a summation of the total signals within the response range of the

channel. An incoming light source transmission spectrum with a narrow dip with FWHM of 5nm as shown in

figure will be superimposed with the grating transmission responses of the 30 channels.

5.1.2 -10 dB crosstalk

Grating transmission with -10dB crosstalk

-14

-12

-10

-8

-6

-4

-2

0

2

1500 1520 1540 1560 1580 1600

w avelength (nm)

optical signal (dBm)

Figure 5.4: Incoming optical signal (blue) superimpose on the grating transmission profile with -10db crosstalk.

Figure 5.4 shows the simulation of a 5nm absorbance band (blue curve) at 1550nm with -10dB loss and the 30

grating responses with -10dB crosstalk. We will simulate the corresponding signal strength of 30 output

waveguides for this -10dB crosstalk grating response.

Signal output for -10dB crosstalk

-12-10

-8-6-4-202

1500 1550 1600

wavelength (nm)

no

rmalise

d o

utp

ut

optical sig

na

l (d

Bm

)

output optical signal

input optical signal

Figure 5.5: Simulated output signals (blue) compared with input signal spectrum (red).

Figure 5.5 shows the normalised output signal for 30 waveguides (blue dots) as compared with simulated input

signal. As we can see, the low transmission (-10dBm) in the region of 1550nm can not be distinguished from

the output signals of the 30 channels (blue dots). This is due to the crosstalk at -10dB that introduces large

amount of noises from other channels. These noises have overwhelmed the true signal and corrupted the

information carrying signal.


37

5.1.3 -20dB crosstalk

Signal output for grating transmissision with -20dB

crosstalk

-25

-20

-15

-10

-5

0

5

1500 1520 1540 1560 1580 1600

w avelength (nm)

sig

nal (

dB

m)

Figure 5.6: Incoming light profile (blue) superimpose on the grating transmission with -20dB crosstalk.

The same profile of transmission/absorption band of FWHM 5nm with an extinction ratio of 10dB is imposed

with grating responses of crosstalk -20dB as shown in figure 5.6.

signal output for grating transmission with -20dB

-12

-10

-8

-6

-4

-2

0

2

1500 1520 1540 1560 1580 1600

wavelength (nm)

norm

alis

ed o

utp

ut

sig

nal

(dB

m)

output signal

intput signal

Figure 5.7: Simulated output signals (blue dots) compared with input signal spectrum (red).

Figure 5.7 shows the output signals (blue dots) detected from the 30 output waveguides. The low transmission

at 1550nm is detected but with an extinction ratio of approximately -3.2dB. The noise caused by the high

crosstalk has decreased the extinction ratio of 6.8dB. This noise value is too high and has corrupted more than

half of the input signal.

Thus, crosstalk at -20dB is inadequate for transmission analysis of input signal with FWHM of 5nm or less.


38

5.1.4 Grating response of the spectrometer

Signal output for spectrometer grating transmission

-50

-40

-30

-20

-10

0

10

1500 1520 1540 1560 1580 1600

wavelength (nm)norm

alised s

ignal (d

Bm

)

Figure 5.8: Incoming light profile (blue) superimpose on the spectrometer grating transmission with better than

-20dB crosstalk.

Now we will have a comparison with the grating transmission of the spectrometer chip. The crosstalk of the

grating is better than -20dB. Simulating the response of the incoming signal, we obtained the following signal

output for 30 channels.

Figure 5.9: Simulated output signals (blue dots) compared with input low transmission (red) spectral

information falling on the centre of channel response (left) and at the edge of channel response (right).

Figure 5.9 shows the output signals at 30channels can adequately reproduce the incoming light spectrum. The

input low transmission with an extinction ratio of 10dB at 1550nm is detected as a transmission with decreased

extinction ratio of 8.5dB at the output of the grating. 1.5dB deterioration is present on the signal.

This shows that the crosstalk value of the grating response of the design is sufficiently good to produce an

approximation to the light signal (FWHM = 5nm) with low transmission of -10dB falling on the centre or edge

of channel response.

signal output for spectrometer grating transmission, lower

transmission falling at the centre of channel response

-12

-10

-8

-6

-4

-2

0

2

1500 1520 1540 1560 1580 1600

wavelength (nm)

norm

alis

ed o

utp

ut

sig

nal

(dB

m)

output signal

intput signal

Low transmission (-10dB) of 5nm FWHM falling at the

edge of peak transmission

-12

-10

-8

-6

-4

-2

0

2

1500 1520 1540 1560 1580 1600

wavelength (nm)

no

rma

lis

ed

ou

tpu

t s

ign

al

(dB

m)

output signal

intput signal


39

5.2 Limitation

The previous simulations were carried out on signal with an extinction ratio of 10dB at 1550nm with FWHM of

5nm. Most absorbance bands in the liquid are broader than 5nm and thus the grating resolution of 3.2nm is

sufficient for detecting liquid absorbance bands. This is true for spectral information (low transmission)

occurring at the centre of the channel transmission.

The worse case scenario is when optical signals contain spectral information less than the grating resolution of

3.2nm, i.e. , a very narrow dip in transmission of FWHM 1nm falling on the edge of the channel response as

shown in figure 5.10 (red curve). The grating would not be able to recover the spectral information. We would

not be able to observe any spectral changes by looking at the output signals of the channels.

Figure 5.10: Simulated low transmission falling on the edge of channel response (left) and corresponding

output signal of the 30 channels (right).

After some straightforward simulations, the spectrometer grating resolution of 3.2nm with a crosstalk better

than -25dB enables sufficiently good reproduction of optical signals containing spectral information more than

3.2nm. This is adequate for spectrometry measurements whereby the absorbance band of analytes are much

broader than the grating resolution.

To be able to better resolve spectral information, the grating channel responses should resemble a flat-top

response.

Signal (FWHM=1nm) falling on the edge of channel

response

-20

-15

-10

-5

0

5

1530 1540 1550 1560 1570

wavelength (nm)

no

rma

lis

ed

sig

na

l (d

Bm

)

Low transmission (-10dB) of 1nm FWHM falling at

the edge of peak transmission

-12

-10

-8

-6

-4

-2

0

2

1500 1520 1540 1560 1580 1600

wavelength (nm)

no

rma

lise

d o

utp

ut sig

nal

(dB

m)

output signal

intput signal

40

CHAPTER 6

Wire Bonding and Electronic read-out board

In this chapter we will describe the wire bonding of the on-chip MSM photodetectors to the ceramic package.

Processing steps to define gold contact pads for the photodetectors and the electronic board will be discussed.

We also designed a back-up bonding mask and electronic board for PIN photodetectors.

6.1 Layout of MSM detectors

There are 30 MSM photodetectors on top of the 30 output waveguide channels. The output waveguides are

spaced 25µm apart. Therefore, this limited space is not sufficient for electrical wire bond pads (wire bond

diameter 32µm). We need to define a fan out from the detector contacts to a bigger wire bond contacts.

Figure 6.1: 30 MSM detectors integrated (vertical straight line) and the Ti/Au contacts on the detectors [13].

The 30 MSM detectors are defined on top of the waveguides in a same line distanced 25µm apart as shown in

figure 6.1. The titanium/gold (thickness of 20nm/200nm) Schottky contacts with a dimension of 22µm x 40µm

are deposited on top of the MSM detectors.

25 µm

Detector 1

Detector 2

Detector 3

Ti/Au contact 1

Ti/Au contact 2

Ti/Au contact 3

40µ

m

Chapter 6 Wire Bonding and Electronic read out board

41

There will be only 31 Ti/Au contacts defined on the same plane for the 30 detectors as opposed to 60 contacts

(2 contacts for each detector) needed. Referring to figure 6.1, the Ti/Au contact 2 will be shared among

detector 1 and detector 2 while Ti/Au contact 3 will be shared by detector 2 and detector 3 and the list goes on

for the rest of the detectors.

6.1.1 MSM photodetector metallization mask

Figure 6.2 below shows the wire bond mask designed for 30 MSM photodetectors. Since the Schottky contacts

are coplanae, there is only one bonding mask needed for metallization of 30 detectors. The Schottkty contacts

of the detectors are connected to bigger contact pads for wire bonding. The wire bond pads are designed to be

250µm x 250µm spaced 50 µm apart.

Figure 6.2: The wire bond mask on MSM detectors.

The dimension of the spectrometer SOI chip is approximately 6mm x 3mm. Therefore, we have chosen Pin

Grid Array (PGA) 68 ceramic package with due to its big die cavity dimension, 1.16cm x 1.16cm that provides

sufficient space to glue the spectrometer chip.

Figure 6.3: The bonding mask for defining wire bond pads (blue) and PGA ceramic package top view.

250µm

250µm 30 MSM detectors

50µm

The layout of wire bonding mask is designed such that it is

compatible with the bonding pad layout in the chosen ceramic

package (See Appendix A for PGA 68 layout). The PGA 68

package has 17 contact pads on each side which gives a total

of 68 pins. The contact pads on the SOI chip are thus designed

to have 7 contacts on the top, 17 contacts on the right and 7

contacts on the bottom.


42

6.1.2 PIN photodetector metallization mask

A wire bonding mask is designed for PIN photodiodes for back-up purposes. An InP/InGaAsP PIN

photodetector integrated on top of a SOI waveguide is shown below in figure 6.4.

Figure 6.4: III-V photodetectors bonded on SOI waveguide circuit [14].

The ohmic contacts of the PIN photodetectors have to be defined separately in the processing due to the fact

that these contacts are not in the same plane. Thus, two masks will be needed to define the n-ohmic contact and

p- ohmic contact separately. Figure 6.5 below shows the bonding mask for PIN photodetector contacts.

Figure 6.5: The wire bond mask on PIN detectors.

Two bonding masks are needed where the green mask (figure 6.5) is the common contact pad for p-ohmic

contact and the blue mask is the n- ohmic contacts. Due to the extra processing steps needed define the PIN

detector structure and to define the p-contacts and then the n-contacts, MSM detectors are preferred to PIN

photodiodes to be integrated on the chip.

InP undercladding

(n-doped)

InP uppercladding

(p-doped)

InGaAs absorbing layer

n- ohmic contact p- ohmic contact

30 PIN

detectors

250µm

250µm


43

6.1.3 Metallization processing steps

The metallisation process of the photodetectors is carried out in the cleanroom in Zwijnaarde. The processing

include twice lithography, deposition of Ti/Au and electroplating.

Electroplating is needed to increase the thickness of the gold contact pads as thickness of the initial evaporation

of Ti/Au (20/200nm) is not sufficient for wire bonding. Adding the gold thickness by evaporation is expensive

and thus we have opted for gold electroplating.

1st step: Lithography for metallization

The SOI chip with processed III-V photodetectors is first spin coated with positive photo resist (AZ5214) and

put on the hot plate for soft bake and to remove solvents. The wire bonding mask is aligned onto the underlying

photodetectors on the chip with the mask aligner. The chip is then exposed with 300nm light in vacuum contact

mode for 16 seconds. The polymer chains of the exposed photoresist are broken render it vulnerable.

After exposure, the chip is heated on the hotplate at 120° for 2 minutes. This baking process will cross link the

broken polymer chains of the exposed photoresist. The bonding mask is now removed and the whole chip is

subjected to a flood exposure for 40 seconds. This cross linked part of the photoresist is now insoluble with

developer.

The chip is then developed by immersing in developer AZ 400 and water at 1:3 ratio for approximately 22

seconds. The cross-linked photoresist on the chip will remain while the others are washed away. The chip is

rinsed thoroughly in de-ionised (DI) water to stop further development.

The idea of using a positive photoresist and image reversal is to obtain a negative slope profile for the

photoresist. This is advantageous for further processing steps such as lift off of metal layer. After blow drying

the chip, the chip is observed under the microscope to make sure the photoresist pattern is fully developed.

2nd

step: Evaporation of Titanium/Gold

With the photoresist clearly defined, titanium (20nm) is evaporated onto the chip followed by 200nm of gold.

3rd

step: Lift-off Gold

After evaporation, the chip is immersed in acetone to lift off the remaining photoresist and the metal on top of

it. Now the schottky contacts on the MSM detectors, the connectors and big contact pads are defined (refer to

figure 6.2).


44

4th

step: Cover the photodetectors with BCB

The chip is spin coated with BCB and cured. This is to protect the photodetectors and metal contacts on top of

photodetectors from oxidation. The BCB that covers the square wire bond pads is further etched away by

reactive ion beam etching.

5th

step: Deposition of Titanium on chip

Titanium is evaporated on the whole chip. This is to provide a conducting platform for further electroplating

process.

6th

step: Lithography + deposition of Ti/Au + Lift off to define big bonding contacts

The first 3 steps are repeated. However, the mask with only the square bonding contacts is used to open the

gold bonding contacts (250µm x 250µm) for added thickness. After lift off, Ti/Au big contact pads are define

for electroplating. This is done because for electroplating, a top later of gold is necessary.

7th

step: Lithography to open squares for gold electroplating

This lithography step using the mask of just square bonding pads is repeated. This is necessary to ensure the

gold is plated within the square bonding pads during the electroplating process.

8th

step: Electroplating of Gold

The chip is now ready for electroplating. The chip is clipped at the cathode of the electrode and immersed in a

mixture of gold salt, potassium gold cyanide (KAuCn2) and water. The solution is heated to 65°C and stirred

with a magnetic rod. Current (3mA) is the applied across the electrodes.

The plating thickness varies proportional with the immersed time and temperature of the solution. After about 2

minutes of electroplating, the chip is removed from the process and rinsed with water. Thickness of more than

800nm is required for good wire bonding. The measured gold thickness achieved from electroplating is

approximately 3 to 5um.

The chip is then dipped in mild hydrofluoric (HF) acid to remove the titanium conducting platform.


45

Figure 6.6: The flow of defining bonding pad contacts.

Figure 6.7: Added thickness on the wire bonding pads (brown).

1st lithography step

Evaporation of Titanium (20nm) followed by

Gold (200nm)

Lift off of Ti/Au

2nd

lithography step + evaporationg of Ti/Au (20nm/200nm)

+ lift off

Electroplating

Dip in diluted HF to remove titanium

Coat with BCB + etching +

deposition of Ti (conductive platform)


46

6.1.4 Wire bond test

The SOI chip with electroplated contact pads is glued onto the ceramic package with epoxy glue and cured for

robustness.

Figure 6.8: Top view of the spectrometer chip glued onto the ceramic package.

Aluminium wires of 32µm are used for wire bonding from SOI chip to package. An ultrasonic welding process

is used to make a bond in which a combination of vibration and force to effectively scrub the interface between

wire and substrate is used. This cause a very localised temperature rise, promoting the diffusion of molecules

across the boundary. Figure 6.9 shows the wedge being lowered to make a wire bond onto the contact pads.

Figure 6.9: Lowering the bonding wedge to make the bond.

The dimension of the bonding pads on the SOI detectors are 250um x 250um. The aluminium wire is first

bonded onto the gold pads of the ceramic package and then to the gold bonding pads on the chip.

The ceramic package provides a robust wire bond platform and thus the bonding starts from the package bond

pads. The bonded wire is then pulled from the bond pad on the package to the bond pad on the chip and with


47

the right force, the bond wedge is lowered, pressed against the bond pads and terminate the wire bond

connection. This procedure is to prevent the gold bonding pads on the SOI chip to be lift off during the pulling

of the wires.

Figure 6.10: Successful bonding (left) and lift off of bonding pad (right).

Figure 6.10 shows the wire bonds on the SOI chip. One of the bond pads was lifted off together with the wire

after the termination of the bond. This is due to bad adhesion of the Ti/Au contacts with the underlying SOI

substrate.

Figure 6.11: Complete wire bond chip.

Figure 6.11 shows a complete bonded SOI chip on a package. Two of the contact pads on the chip were lifted

off during the blow drying process of the chip. Again, this is caused by the bad adhesion of the Ti/Au contact

pads with underlying BCB layer.

Adhesion could be improved by ensuring cleanliness of the chip before defining the contacts. Subjecting the

chip to 1 minute oxygen plasma to roughen the surface of BCB before defining the Ti/Au contacts can further

improve the adhesion of Ti/Au on BCB.


48

6.2 Electrical read-out board

A photodetector generates a photocurrent which is proportional to the incident light intensity. For this

spectrometer chip, we will supply a bias voltage to the detectors to sweep out the carriers. And since we are

accustomed to measure electronic signals in terms of voltage, we will use a current to voltage converter o

produce a voltage reading proportional to the photocurrent generated by the detector.

There are 30 photodetectors integrated on the 30 output waveguides of the grating respectively. Each detector

measures a part of the diffracted light spectrum from the grating spanning from 1500nm to 1600nm. We design

2 boards for MSM photodetectors and PIN photodetectors respectively. The circuit have the same switches and

transimpedance circuit except with the different biasing path for the detectors.

6.2.1 Schematic of voltage read-out circuit

The idea is to read out the voltage signals of 30 photodetector. This can be done by sequentially switching

photocurrent generated from the 30 detectors to the current to voltage converter. The ceramic package carrying

the chip is plugged into a socket instead of soldering directly onto the board. This is done for the ease of testing

different samples.

The basic schematic for electronic read out circuit is shown in figure 6.12 (See Appendix B for complete

electronic schematic layout). The schematics and PCB board is drawn with Eagles 4.12r2 Light software.

Figure 6.12: Schematic of electronic read out circuit with switch and current to voltage converter.


49

The photocurrent from the detectors can be selected by inserting analogue switches between them and the

current to voltage converter. The selection bits of the switch are controlled by the parallel port data out pins of

the computer. The photocurrent from each detector is then selected by sending the right selection bits to the

switch. A labview vi is used to interface and control the parallel ports pins (See Appendix C for selection bits

and Labview vi).

A bias voltage is supplied to the detector to sweep out the carriers generated by and the photocurrent is

converted into an output voltage by the OpAmp transimpedance circuit. A multimeter is used here to record the

output readings.

Two biasing schemes are needed for each MSM and PIN photodetectors due to the different layout of the

contacts for both the detectors (full schematics can be found in Appendix B).

6.2.1.1 MSM photodetector board

MSM detectors can be seen as back to back connected Schottky diodes. As these detectors are symmetric, the

current-voltage (I-V) characteristics should also be symmetric. So the polarity of the bias voltage is not

important. The bias scheme proposed has alternate biasing polarity for alternate MSM detectors.

Figure 6.13: Schematic of MSM detector biasing circuit.

Figure 6.13 shows the biasing scheme for the MSM detectors. The first MSM detector is positively biased

through the upper switch and the photocurrent will flow through the lower switch to the transimpedance circuit.

The second MSM detector will be negatively biased due to sharing of a contact with the first detector. The


50

photocurrent of the second MSM detector will have opposite sign to the first MSM detector. This is designed

considering the responsivity of MSM detectors is symmetrical for positive ad negative bias.

6.2.1.2 PIN photodetector board

Figure 6.14: Schematic of PIN detector biasing circuit.

Figure 6.14 shows the biasing scheme for PIN photodetectors. The PIN photodetectors have a common ohmic

contact that can be biased (V_bias) at the same time. The photocurrent of each detector is switched to the

transimpedance circuit respectively. For these detectors, the polarity is important and the photodiodes should be

inversely biased.

6.2.2 Selection of electronic components

For the board of MSM photodetectors, four CMOS 4052 8x1 analogue switches and one CMOS 4053 4x1

analogue switch are used to sequentially switch the photocurrent from the photodetector. The CMOS family of

analogue switches are chosen for their good performance with low “OFF” leakage currents (10pA) and low

“ON” resistance (80Ω). They provide logic level conversion for digital addressing signals and also dissipate

extremely low power over full supply voltage range, up to 15V [19].

As we know, electronic components are not ideal and the operational amplifier (OpAmp) used in the

transimpedance circuit will introduce some offset voltage to the output readings. In reality, the input resistance

of the opamp is not infinite. This allows a small amount of current to flow into the opamp. This current will be

further amplified by the negative feedback gain.


51

Furthermore, the dark current of the photodetector can impose error on the I-V gain of the circuit and produce

DC offset error in the converter’s output. This dark current offset error will be negligible for larger currents but

can cause considerable error in smaller currents. Since we are operating in a very low current region, from 5nA

to 10µA, this offset error could cause considerable error in the output voltage.

The simplest way to minimize the offset error would be to choose an OpAmp with low DC offset voltage and

low input bias current. By setting an error budget for the voltage read out from the transimpedance circuit, we

can choose a suitable OpAmp.

We will set our error budget to 1% of the output voltage. That means that for maximum output voltage of 1V,

we will have ± 0.01 V error. First we will determine the necessary open loop gain for this error budget.

OpAmp gain error is defined to be

CL

OL

A

Ae

+=

1

1; where AOL is the open loop gain and ACL is the closed loop

gain. Thus, the open loop gain is ( )11 −=e

AA CLOL .

For our design, the close loop gain, ACL is 100k (feedback resistance 100k) and error is 0.01. Hence, the

calculated minimum open loop gain, AOL has to be more than 70dB.

We have chosen OPA 132 as the OpAmp for the transimpedance circuit as it has an open loop gain of 120dB,

very low input bias current of 50pA and low input offset voltage of 0.5mV. Error will be calculated for this

model. The sources of offset voltage are as follow:

a) Dark current of photodetector

A dark current of 10nA will impose an offset voltage of 1mV.

RIV darkDoff ×−=_

b) Input Bias Current OPA 132

The low input Bias current of the OPA 132 of 50pA will induce an offset of 5µV which will be negligible.

c) Input offset voltage of OPA 132

Input offset voltage of the OPA 132 is 0.5mV and thus is within the 1% error region.


52

The theoretical offset voltage is within tolerance range and the OPA 132 is suitable to be used in the

transimpedance circuit.

Figure 6.15 shows the PCB board layout of the circuit.

Figure 6.15: PCB board layout.

6.2.3 Error in output voltage reading

A voltage to current converter (transimpedance) circuit with a feedback resistance, R of 100kΩ is chosen here.

Figure 6.16: Schematic of transimpedance circuit with feedback resistance of 100kΩ.

The output voltage with respect to the incoming photocurrent is calculated as:

RIV pdout ×−=

Below is the expected photocurrent from the detectors and the converted output voltage:

Socket for

SOI chip

Analogue

switches

Supply

pins

Current to voltage converter

Parallel port connected to PC to control switches (labview .vi) interface


53

Photodetector State Photocurrent I-V converter output voltage

dark 5nA 0V

bright 10µA 1V

Table 6.1: Expected photocurrent versus output voltage.

The dark current of the detector is expected to be in range of 5nA to 10 nA. When light is illuminating on the

detectors, 10µA is the expected average generated photocurrent. With a feedback resistance of 100kΩ, the

corresponding output voltage expected would be 1V. After obtaining the electrical board, the I-V gain curve is

tested on the transimpedance circuit by injecting current from 10nA to 50µA. Figure 6.17 shows the I-V gain

curve from 10nA to 10 µA.

Voltage-Current gain curve

y = 100.01x - 0.4776

-10

190

390

590

790

990

0 2 4 6 8 10

Current (uA)

Volta

ge (

mV

)

Voltage-Current gain curve

y = 100.01x - 0.4773

0.01

0.1

1

10

100

1000

10000

0.001 0.01 0.1 1 10 100

Logscale Current (uA)

Logscale Voltage (mV)

Figure 6.17: Plot of I-V gain curve of transimpedance circuit of the board, linear (left), logscale (right).

The transimpedance circuit exhibits good linear current to voltage conversion starting from current as low as

0.1µA. In the region of operation from 0.1µA to 10 µA, the linear regression fit gives Voltage (mV) =

100.01*current (µA) -0.4773. The offset voltage is approximately 4.7mV.

Thus for 1µA photocurrent generated, the conversion voltage by the transimpedance circuit yield 99.53mV.

When compared with ideal conversion voltage of 0.1V (gain=100000), an error of 0.5% is obtained.

54

CHAPTER 7

Experiments on Spectrometer-on-a-chip and the electrical

board

Experiments are carried out to characterise the 30 metal-semiconductor-metal (MSM) photodetectors integrated

on the output waveguides from the concave grating and also to read out the photocurrent and voltage output

from the electrical board. It is essential to check the functionality of all the 30 detectors and characterise their

dark currents and responsivities. We will then measure the corresponding electrical output from the detectors

and analyse the performance of the board.

There are 30 MSM detectors integrated on top of the 30 output waveguides from the grating. This filter splits

the incoming light into 30 spectral components that is subsequently detected by the 30 detectors. Thus, each

photocurrent detected by the MSM detector is proportional to the optical power of different spectral component

of the light spectrum.

7.1 Measuring the dark current of the detectors

Under no external photon injection, there should be ideally no electron-hole pair generation in the

photodetector and hence no current flow under a constant voltage bias. However, when the detector is subjected

to a voltage bias, there is a measure of small current in the absence of light. This small current is termed as the

dark current.

Dark current is due to thermal electron-hole pair generation in the material. It is also viewed as one of the

contributing noise factor in a detector. Dark current imposes an offset signal in light detection and the value of

dark current increases with temperature. Hence, a low dark current is desirable in a detector.

Chapter 7 Experiments on Spectrometer-on-a-chip and the electrical board

55

We will measure the dark currents of the 30 detectors by biasing the MSM detectors with increasing voltage.

The dark current value can also indicate whether the detectors and its connecting paths are functioning.

7.1.1 Experimental result

The 30 photodetectors with defined Ti/Au schottky contacts and the connecting wire bond contact pads are

subjected to a voltage bias. This is achieved by probing two needles onto the two gold contacts on the ceramic

which are bonded to the detector and supplying a voltage bias from the voltage source.

Dark current versus biasing voltage

0

1

2

3

4

5

6

7

0 2 4 6 8

biasing voltage (V)

dark current (nA)

detector 16

Figure 7.1: The measured dark current versus biasing voltage for the detector 16 (1550nm).

Figure 7.1 shows a plot of dark current of detector 16 with biasing voltage from 0V to 6V. The dark current

increases as bias voltage increases. The plot of dark currents of all 30 MSM detectors for a bias voltage at 6V is

shown below in figure 7.2.

Dark current of 30 detectors versus biasing voltage of

6V

1.E-07

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

0 10 20 30

detectors

dark

curr

ent lo

g s

cale

(mA

)

Figure 7.2: The measured dark current at 6V bias for 30 detectors.


56

From figure 7.2, we notice that some detectors exhibit extremely high or low dark current relative to others. As

the dark current expected at 6V bias for a functioning MSM detector is around 6nA to 10nA range, we would

render the detectors with abnormal dark current readings as malfunctioning.

The detectors with extremely high dark current and saturates to 0.1mA are suspected to be short circuited. This

could be due to the shorted contact pads between the detectors. Some detectors also showed nearly no

connection and the recorded dark current is very low at less than 0.6nA. This situation resembles an open

circuit where the bonding contacts might be lifted off and were not connected to the detectors.

From the dark current measurement we concluded that the 9 detectors are short circuited and 5 detectors are

disconnected by the bonding pads. Hence only 16 out of 30 detectors on the chip are functioning and subjected

to measurements.

7.2.2. Defect of detectors

The figure 7.3 below shows the detectors with the corresponding connecting pads.

Figure 7.3: Bonding pads of 30 detectors on a package.

Referring to the figure above, the first detector is connected from the top right first bond pad to the top right

second bond bad. By rotating from top right clockwise to the top left square wire bond pad, we would get 30

detectors.

Detector 3, 4 and detector 29, 30 are not connected to the package due to lift off of the contact pads during

processing. Detectors 5,6,7,8 and detectors 24, 25,26,26,28 are short-circuited.

Detector 2

Detector 1 Detector


57

7.2 Measuring the responsivity of detector

Responsivity, R is one of selecting criteria for a detector where it measures the ratio of detector output to the

input light signal. The external responsivity can be defined as:

)(___

)(

)(

)( detdet

WfibreinputpowerOptical

AI

WP

AIR ecter

fibre

ector

ext ==

where Idetector is the output current from the detector and Pfibre is the optical power of the input fibre.

Responsivity can also be written as 24.1

][ m

hv

qR extextext

µληη == , where ηext is the external quantum efficiency, q

is the coulomb charge, h is the Plank’s constant and v is the frequency of incident light. From the relation we

can see that responsivity is dependent on the incoming light wavelengths and also the external quantum

efficiency of the detector. External quantum efficiency is defined as

fibreinputinphotonsincident

ntphotocurretocontributepairsheext

____

____−=η . ηext of 1 assumes all incident photons contribute to the

photocurrent .

7.2.1 Experiment result

Tunics tunable laser is used as the light source in this experiment. Light is injected onto the grating chip via a

fibre grating coupler from a single mode fibre held at 10° incidence angle. A voltage bias from -6V to 6V is

then applied across the detector bonding pads and the corresponding photocurrent is measured.

Figure 7.4: Experiment set up with spectrometer chip and electrical board.

The current voltage (I-V) curve of detector 23 which corresponds to a wavelength of 1570nm is measured and

shown in figure 7.5.

Parallel port cable

Analogue switches Voltage supply pins and output pins

Input fibre


58

I-V curve of detector 23

-4.E-02

-2.E-02

0.E+00

2.E-02

4.E-02

6.E-02

8.E-02

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

bias voltage (V)

measure

d c

urr

ent

(mA

)

0.2625 mW

0.525 mW

0.7875 mW

1.05 mW

Figure 7.5: The measured photocurrent for detector 16 from -6V to 6V bias.

Figure 7.5 shows I-V curve for detector 23 for voltage bias of -6V to 6V for different input optical power of

fibre ranging from 0.26mW to 1mW. Considering the positive bias region, the photocurrent is observed to

increase with increasing voltage bias less that 3V but reaches constant as the bias increases more than 4V. The

external responsivity of detector 23 (1570nm) at bias voltage 6V is measured to be 0.0627 A/W.

The asymmetrical responsivity for detector 23 (1570nm) is observed where the responsivity in the positive bias

region differs from the negative bias region. We do not expect this as MSM detector exhibits a symmetrical

responsivity. A possible explanation to this could be due to processing error when defining the two schottky

contacts. It is possible that the area of two Ti/Au metal contacts deposited on the detector is not identical and

may be shifted to the left or right. This could produce a preference biasing direction for the detector.

By tuning the laser to the peak response wavelength of each detector, i.e.1570nm for detector 23 and 1566.9nm

for detector 22, the I-V curve (same as figure 7.5) for detectors 9 to 23 with different optical power of input

fibre is measured. The corresponding external responsivity for the photodetectors (detector 9 to detector 23) at

6V bias are measured and plotted in figure 7.6.


0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

detectors

R ext (A/W)

Figure 7.6: The external responsivity of 15 functioning photodetectors (9 to 23) at bias voltage 6V.


59

As each detector records optical power of different wavelength channels, figure 7.6 can be plotted against the

spectrum axis as below in figure 7.7.


0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

R ext (A/W)

Figure 7.7: The external responsivity of 15 functioning photodetectors (9 to 23) plotted against wavelength.

The fibre coupler on-chip has a peak response around 1550nm. However, the peak response will be shifted to

longer wavelengths of around 1580nm taking into account the BCB layer deposited on the SOI chip which

increases the effective refractive index. Figure 7.8 shows the transmission response for fibre coupler (brown),

fibre coupler with BCB top layer (blue), PCG transmission (blue dots) and total response of fibre coupler

(BCB) and PCG (red curve).

Transmission versus wavelength

-22

-20

-18

-16

-14

-12

-10

-8

-6

-4

-2

0

1500 1520 1540 1560 1580

wavelength (nm)

Tra

nsm

issio

n (

dB

)

PCG

fibre coupler

fibre coupler+BCB

f_coupler+BCB+PCG

Internal responsivity of MSM detector

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1520 1530 1540 1550 1560 1570 1580

w avelength (nm)

Inte

rnal r

esponsiv

ity (

A/W

)

Figure 7.8: The fibre coupler response curve (brown), possible shifted response with BCB top layer (blue) [10],

the PCG transmission response (blue dots) and the shifted fibre coupler + PCG response (red). The left figure

shows the internal responsivity of MSM detector from 1520nm to 1580nm [13].

Since the detectors circuit from 1570nm onwards are not functioning, it is difficult to compare the experiment

transmission response to the total transmission response of the system (fibre coupler, PCG and MSM detector).

However, by observing the transmission response trend of fibre coupler and PCG and also taking into account

the internal responsivity of the MSM detectors reported in [13], we can conclude that the signal transmission

could be increasing towards the region of 1580nm. The responsivity (figure 7.7) from 1520nm to 1570nm does

resemble part of the coupling and PCG response with increasing transmission towards 1580nm region.


60

External Responsivity can be expressed as fibreinputP

AntPhotocurreRext

__

)(= whereas Internal Responsivity (internal

quantum efficiency =1) is expressed as waveguideoutputP

AntPhotocurreR

__

)(int = .Hence, Rint is calculated as

waveguideoutputP

fibreinputPRR extInt

__

__*= .

We will calculate the internal responsivity of the MSM detector by doing a calculation at 1570nm and

assuming this is the peak transmission wavelength for the fibre coupler. On chip loss of PCG is approximately

4.6 dB at 1570nm and the fibre coupling loss at 1570nm is taken to be 6dB (peak response). The insertion loss

is thus approximately 10.6dB. For input fibre optical power of 1mW, the output waveguide optical power

would be 0.087mW. The external responsivity measure from the experiment at 1570nm is 0.062 A/W.

Hence, the internal responsivity of MSM detector is 0.71 A/W. This is less than the expected internal

responsivity of 1 A/W [13]. This might be due to the underestimation of fibre coupling losses at 1570nm which

could be higher than 6dB. Another possibility is the layer of BCB deposited on top of the spectrometer chip.

This decreases the refractive index contrast of the etched grating facets. This can result in a higher facet

reflection loss and hence, a higher on-chip loss.

7.3 Measuring the output current and voltage from the printed circuit board

Now we tune the laser to the peak transmission of each detector and supply with a constant input optical power

of 1mW. The electronic board then supply bias voltage of 5V to the detectors and the selection of detectors is

done through the parallel port control pins. The photocurrent from each detector is measured from 1500nm to

1600nm and plotted as in figure 7.9.

Photocurrent versus wavelength plot at 6V

0.E+00

1.E-02

2.E-02

3.E-02

4.E-02

5.E-02

6.E-02

7.E-02

8.E-02

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

current (m

A)

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

Figure 7.9: The photocurrent versus wavelength plot for 15 detector 9 to detector 23.


61

It is observed from figure 7.9 that the photocurrent measured by the detectors shows alternate peaks whereby

detector 23 has high responsivity while detector 22 has lower responsivity and followed by detector 21 with

high responsivity. This again shows that there might be processing error that renders the MSM detectors with

asymmetrical responsivities for different biasing voltage polarity. The read out circuit is designed such that

detectors are biased at alternate voltage polarity, i.e. 5 V for detector 23 and -5V for detector 22 etc.


0.E+00

1.E-02

2.E-02

3.E-02

4.E-02

5.E-02

6.E-02

7.E-02

8.E-02

9.E-02

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

Photocurrent (m

A)

det 23

det 22

det 21

det 20

det 19

det 18

det 17

det 16

det 15

det 14

det 13

det 12

det 11

det 10

det 9

Figure 7.10: Optimised photocurrent versus wavelength plot for detector 9 to detector 23.

Figure 7.10 shows the optimised plot where the bias voltage is reversed to give a higher responsivity and

smooth photocurrent spectrum. The photocurrent recorded by detector 21 (1564.8nm) exhibits very high offset

current (5µA). This detector registered very high dark current in previous measurement (section 7.1.1) of

approximately 1µA. Thus we can conclude this detector has very high offset current due to leakage current and

is not operating in a good condition.

From figure 7.10, we can also conclude that the MSM detectors are measuring the peak transmission at

wavelength which agrees with the PCG diffracted wavelength channels. The peak transmissions recorded by

the detectors are spaced approximately 3 nm apart. The photocurrent trend also agrees well with the fibre

coupler and PCG transmission response where the peak coupling efficiency is approximated to occur around

1580nm and roll off towards 1520nm.


62

7.3.1 Crosstalk

From figure 7.11, we can notice the presence of crosstalk with similar crosstalk profile compared with the PCG

transmission (refer figure 5.3). The photocurrents are plotted in log scale in the figure 7.11 below.


0.0001

0.001

0.01

0.1

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

Logscale Photocurrent (mA)

det 23

det 22

det 21

det 20

det 19

det 18

det 17

det 16

det 15

det 14

det 13

det 12

det 11

det 10

det 9

Figure 7.11: Photocurrent (log scale) versus wavelength plot for detector 9 to detector 23.

From figure 7.11, it is noticed that the crosstalk for detector 23 of 1570nm is -11.23dB. As compared with

grating response before packaging in figure 7.12 below, the crosstalk has increased from -20dB to -11.23dB.

This increase in crosstalk can be introduced during the packaging of the spectrometer chip. The optical signal

losses could increase during integration of MSM detectors and metallization of wire bond contacts onto the

chip. The electronic board might also introduce losses to the optical signal and measure lower photocurrent

readings.

Grating transmission before packaging

-30

-25

-20

-15

-10

-5

0

1520 1530 1540 1550 1560 1570 1580

waveength (nm)

dB

Figure 7.12: PCG transmission before packaging.


63

7.3.2 Voltage reading from the printed circuit board

We tuned the laser to the peak transmission wavelength of the channel/ detector 23, and supply with a constant

input optical power of 1mW. We then read out the voltage reading from detector 9 to detector 23 (15 data

points). The procedure is then repeated for each of the detector. The output voltage from the transimpedance

circuit is plotted in figure 7.13.

transimpedance output voltage

-50

0

50

100

150

200

1520 1530 1540 1550 1560 1570 1580

w avelength (nm)

Vo

ut

(mV

)

23

22

21

20

19

18

17

16

15

14

13

12

11

10

Transimpedance Voltage output

0

50

100

150

200

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

Voltage (mV)

Figure 7.13: Transimpedance output voltage reading, peak voltage output for detector (right).

Figure 7.13 records the voltage output proportional to the photocurrent of the detector with a gain of 100000

(feedback resistor = 100kΩ).

Photocurrent comparison

0.00001

0.0001

0.001

0.01

0.1

1

1520 1530 1540 1550 1560 1570 1580

wavelength (nm)

logscale Current (m

A)

Ipd

Ipd_Vout_conversion

Figure 7.14: Comparison between photocurrent converted from transimpedance voltage output (pink dots) with

photocurrent measured previously (blue dots) with same supply optical power.

The output voltage measured after the transimpedance circuit with an input optical power of 1mW is converted

into photocurrent (pink dots) R

VI = , where R=100000 is the gain of the transimpedance circuit. The value is

compared with photocurrent measure in the previous section (blue dots) and can be seen in figure 7.14.


64

The photocurrent from both measurements is supplied with the same input optical power of 1mW. However,

the photocurrent measurement on the second day differs from the measurement value before by a factor of 100.

This is not expected as same input optical power of the fibre is supplied to the spectrometer chip.

Due to accidental damage done to the spectrometer chip, the transimpedance output voltage cannot be

reproduced and verified. However, possible explanation to this disparity can be due to not optimised alignment

and measurement. The tunable laser might not be tuned to the optimum wavelength of the detector before

conducting the voltage measurement. Furthermore, voltage readings are collected from each of the detector

which has a spectral separation of 3.2nm. Thus the voltage reading points are separated by 3.2nm. Information

is lost in between this separation and possible higher voltage readings might be obtained in this range.

Overall, we have measured the external responsivity of the MSM detectors and also measured the photocurrent

from the electrical board. The transimpedance circuit is measured to have an offset voltage of 4.7mV.

The photocurrents measured from the electrical board have transmission response that agrees with the

transmission response of the fibre coupler and PCG. However the crosstalk after packaging has increased from

-20dB to -11.23dB. Crosstalk of -11dB can corrupt the optical signal information containing spectral

information less than 5nm.

65

CONCLUSION AND PERSPECTIVE

The project has presented a packaged spectrometer on a chip with electrical read out signals. Metallization of

Ti/Au schottky contacts on the detectors and electroplating for added bonding pad thickness is carried out for

wire bonding the detectors to electrical board. The dimension of bonding pads of more than 150µm x 150 µm

and thickness of bond pads of more than 800nm is needed to ensure successful wire bonding. Electrical board

has been designed for the electrical read out of photocurrent with switches and transimpedance circuit.

Two schemes have been designed for MSM and PIN photodetectors respectively. However, only the MSM

detectors integrated on the spectrometer chip has been tested. The experiments measure the external

responsivity of the peak transmission (1570nm) to be 0.062 A/W and calculated internal responsivity is 0.71

A/W.

The electrical board is able to record the photocurrents from the MSM detectors. The spectral resolution of the

detector is spaced approximately 3 nm apart which agrees with the transmission response of the PCG before

packaging. Thus, the spectrometer-on-a chip can be operated with the electrical board. However, the crosstalk

after packaging has increased from -20dB (before packaging) to -11.23dB. This crosstalk value can corrupt

optical signal with spectral information less then 5nm. The increase in crosstalk could be due to losses

introduced during packaging. This required further verification. Overall, the transimpedance circuit shows

reliable current to voltage conversion whereby the offset voltage is 0.47mV for input photocurrent of 1µA to

10µA.

Near infrared absorption experiments have been carried out to study the absorbance bands of water in ethanol

and also blend levels of biodiesel in conventional fuel. Straightforward calibration techniques have been

studied for predictions of analyte concentration. These are among the applications of spectrometer on a chip of

this project. However, we have not tested the absorption measurements with the spectrometer-on-a-chip.

Perspectives

• The increase in crosstalk of the spectrometer-on-a-chip after packaging should be investigated.

• Electrical read out board integrated with amplifiers would be advantageous to measure photocurrents

of detectors. An automated voltage read out with respect to the detectors can be implemented.

• The input single mode fibre can be glued to the chip to present a more robust package.

• It would be advantagoues to measure absorption of liquids with the packaged spectrometer.

66

Appendix A

Ceramic package Pin Grid Array (PGA) layout and connecting pins

Figure A.1: Bottom view of the package pins. Figure A.2: Top view of the PGA 68 package.

Figure A.3: Table of connection pins of the PGA 68 package by Globalchipmaterials.

67

Appendix B

Schematics of electrical read out circuit.

B.1: MSM detectors circuit

Figure B.1: Schematic circuit for MSM detectors.

68

B.2: PIN detectors circuit

Figure B.2: Schematic circuit for PIN detectors.

69

Appendix C

C.1: Analogue switching bits of detectors.

MSM detectors PIN detectors

Figure C.1: Tables of analogue switching pins for MSM detectors (left) and PIN detectors (right).

70

C.2: Labview vi. for switching the MSM detectors

Figure C.2.1: Front panel of Labview vi. for switching MSM detectors.

Figure C.2.2: Subroutine vi. for out port and in port (Sending bits to parallel port).

Figure C.2.3: MSM detector switching vi.

71

C.3: Labview vi. for switching the PIN detectors

Figure C.2.4: Front panel of Labview vi. for switching PIN detectors.

Figure C.2.5: PIN detector switching vi.

72

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22. CMOS analogue switches 4051,4052, 4053 datasheets. Available at www.alldatasheet.com.

23. J. Brouckaert, W. Bogaerts, S. Selvaraja, P. Dumon, R. Baets, and D. V. Thourhout, “Planar Concave

Grating Demultiplexer With High Reflective Bragg Reflector Facets”, IEEE Photonics Technology

Letters,, Vol. 20, No. 4, pp. 309-311, 2008.

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List of Figures

1.1: Diatomic oscillator with masses m1 and m2…………………………………………………… 2

1.2: Energy diagram of an ideal diatomic oscillator and anharmonic diatomic oscillator………… 3

1.3: Transmission through sample contained in a cuvette………………………………………….. 4

2.1: Schematic view of spectrometer on a chip…………………………………………………….. 6

3.1: Basic grating configuration…………………………………………………………………….. 9

3.2: Schematic structure of the aluminium grating spectrometer…………………………………… 9

3.3: Schematic view of compact planar spectrometer………………………………………………. 10

3.4: The experimental set up of compact planar spectrometer……………………………………… 11

3.5: Waveguide concave grating spectrometer……………………………………………………… 11

3.6: Diffraction grating layout for fibre to waveguide coupling……………………………………. 12

3.7: Coupling efficiency for fibre coupler with air interface and 630nm grating pitch……………... 13

3.8: Planar Concave Grating based on Rowland configuration…………………………………….. 13

3.9: Schematic view of waveguide integrated MSM detector………………………………………. 14

4.1: Cuvette holder used in experiment……………………………………………………………... 16

4.2: SLED output spectrum…………………………………………………………………………. 17

4.3: Transmission through different water ethanol mixtures contained in a cuvette………………... 17

4.4: Normalised absorbance curve of water ethanol mixtures (left) and gaussian fit curve (right)…. 18

4.5: Normalised absorbance spectrum of different blends of biodiesel in conventional fuel……….. 19

4.6: Transmission spectrum of different blends of biodiesel and conventional fuel…………………20

4.7: Error free single absorbance band [1]………………………………………………………… 20

4.8: Calibration line in univariate analysis [1]………………………………………………………. 21

4.9: Absorbance band of multivariate case (more than one wavelength) [1]……………………….. 22

4.10: Example of 4 absorbance spectra for a m wavelength points…………………………………... 23

4.11: Principle Component Flow Chart [1]……………………………………………………………25

4.12: Univariate calibration line calculated for water ethanol mixtures at 1450nm………………….. 26

4.13: Prediction versus known water concentration in ethanol mixtures at 1450nm………………… 27

4.14: Eigenvalues of calculated from the sum of cross product matrix………………………………. 27

4.15: Plot of concentration of water in ethanol versus Scores………………………………………... 28

4.16: Prediction versus known water concentration in ethanol mixtures using PCA………………… 29

4.17: Calibration line calculated for biodiesel conventional fuel mixtures at 1664nm………………. 30

4.18: Prediction for biodiesel conventional fuel mixtures at 1664nm……………………………….. 31

4.19: Plot of eigenvalues of PC (left) and plot of scores (right) for biodiesel blend levels………….. 31

4.20: Plot of biodiesel concentration in conventional fuel versus Scores……………………………. 32

75

4.21: Plot of prediction value versus reference value of biodiesel concentration in diesel………….. 32

5.1: Grating transmission spectrum of 30 channels PCG demultiplexer……………………………. 34

5.2: Newly generated grating transmission spectrum of 30 channels PCG demultiplexer…………. 35

5.3: Qualitative spectrum view of the ideal channel response and the real channel response……… 35

5.4: Incoming optical signal (blue) superimpose on the grating transmission profile with -10db

crosstalk………………………………………………………………………………………….36

5.5: Simulated output signals (blue) compared with input signal spectrum (red)……………………36

5.6: Incoming light profile (blue) superimpose on the grating transmission with -20dB crosstalk… 37

5.7: Simulated output signals (blue dots) compared with input signal spectrum (red)………………37

5.8: Incoming light profile (blue) superimpose on the spectrometer grating transmission with better

than -20dB crosstalk……………………………………………………………………………. 38

5.9: Simulated output signals (blue dots) compared with input low transmission (red) spectral information

falling on the centre of channel response (left) and at the edge of channel response (right)……38

5.10: Simulated low transmission falling on the edge of channel response (left) and corresponding output

signal of the 30 channels (right)…………………………………………………………………39

6.1: 30 MSM detectors integrated (vertical straight line) and the Ti/Au contacts on the

detectors [13]…………………………………………………………………………………….40

6.2: The wire bond mask on MSM detectors………………………………………………………... 41

6.3: The bonding mask for defining wire bond pads (blue) and PGA ceramic package top view….. 41

6.4: III-V photodetectors bonded on SOI waveguide circuit [14]…………………………………... 42

6.5: The wire bond mask on PIN detectors………………………………………………………….. 42

6.6: The flow of defining bonding pad contacts…………………………………………………….. 45

6.7: Added thickness on the wire bonding pads (brown)…………………………………………… 45

6.8: Top view of the spectrometer chip glued onto the ceramic package……………………………46

6.9: Lowering the bonding wedge to make the bond……………………………………………….. 46

6.10: Successful bonding (left) and lift off of bonding pad (right)…………………………………... 47

6.11: Complete wire bond chip……………………………………………………………………….. 47

6.12: Schematic of electronic read out circuit with switch and current to voltage read out circuit….. 48

6.13: Schematic of MSM detector biasing circuit……………………………………………………. 49

6.14: Schematic of PIN detector biasing circuit……………………………………………………… 50

6.15: PCB board layout……………………………………………………………………………….. 52

6.16: Schematic of transimpedance circuit with feedback resistance of 100kΩ………………………52

6.17: Plot of I-V gain curve of transimpedance circuit of the board…………………………………. 53

7.1: The measured dark current versus biasing voltage for the detector 16 (1550nm)……………… 55

7.2: The measured dark current at 6V bias for 30 detectors………………………………………… 55

7.3: Bonding pads of 30 detectors on a package……………………………………………………. 56

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7.4: Experiment set up with spectrometer chip and electrical board……………………………….. 57

7.5: The measured photocurrent for detector 16 from -6V to 6V bias……………………………… 58

7.6: The external responsivity of 15 functioning photodetectors (9 to 23) at bias voltage 6V……… 58

7.7: The external responsivity of 15 functioning photodetectors (9 to 23) plotted against

wavelength……………………………………………………………………………………… 59

7.8: The fibre coupler response curve (brown), possible shifted response with BCB top layer (blue)

[10], the PCG transmission response (blue dots) and the shifted fibre coupler + PCG response

(red). The left figure shows the internal responsivity of MSM detector from 1520nm to

1580nm [13]……………………………………………………………………………………. 59

7.9: The photocurrent versus wavelength plot for 15 detector 9 to detector 23…………………….. 60

7.10: Optimised photocurrent versus wavelength plot for detector 9 to detector 23…………………. 61

7.11: Photocurrent (log scale) versus wavelength plot for detector 9 to detector 23………………… 62

7.12: PCG transmission before packaging……………………………………………………………. 62

7.13: Transimpedance output voltage reading, peak voltage output for detector (right)…………….. 63

7.14: Comparison between photocurrent converted from transimpedance voltage output (pink dots) with

photocurrent measured previously (blue dots) with same supply optical power……………….. 63

A.1: Bottom view of the package pins………………………………………………………………. 66

A.2: Top view of the PGA 68 package……………………………………………………………… 66

A.3: Table of connection pins of the PGA 68 package by Globalchipmaterials…………………….. 66

B.1: Schematic circuit for MSM detectors………………………………………………………… 67

B.2: Schematic circuit for PIN detectors…………………………………………………………….. 68

C.1: Tables of analogue switching pins for MSM detectors (left) and PIN detectors (right)……….. 69

C.2.1: Front panel of Labview vi. for switching MSM detectors…………………………………….. 70

C.2.2: Subroutine vi. for out port and in port (Sending bits to parallel port)…………………………. 70

C.2.3: MSM detector switching vi…………………………………………………………………….. 70

C.2.4: Front panel of Labview vi. for switching PIN detectors………………………………………. 71

C.2.5: PIN detector switching vi………………………………………………………………………. 71

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List of Tables

3.1: Comparison of grating spectrometers. ……………………………………………………………… 15

4.1: The univariate prediction table of water ethanol mixtures………………………………………...... 26

4.2: The PCA prediction table of water ethanol mixtures…………………………………………………. 29

4.3: The univariate prediction table of biodiesel blend levels…………………………………………… 30

4.4: The PCA prediction table of biodiesel blend levels………………………………………………….. 32

6.1: Expected photocurrent versus output voltage………………………………………………………… 53

design and fabrication of a near-infrared spectroscopy

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