Section 4-1, the sensing techniques and working principle of the sensor

Chapter 4

Polarization Shift Keying (PolSK) Fiber-Optic System Measured DNA Sensor

In chapter 3, we successful fabricated optical high sensitivity silicon nanopillars array sensor. In this chapter, the sensor is biosensing because of the peculiar properties of the sensor such as the capability of enhance electromagnetic waves interaction and control Polarization Shift Keying (PolSK) fiber-optic system to measure polarization states to the impairments in the sensor. The content of chapter 4 is arranged as follows:

Section 4-1, the sensing techniques and working principle of the sensor

using Si-Nanopillar array based on PolSK fiber-optic system. In Section

4-2, measure bio-molecular samples are introduced. We will show the

experimentation results in 4-3. Finally, we also give the summary in

section 4-4.

4-1 Sensing Techniques and Working Principle of the Sensor Using Si-Nanopillar Array Based on PolSK Fiber-Optic System

The presence of bio-molecules again contributes to a slight change of refractive index, leading to an alteration of the optical transmission through the Si nanopillars array sensor. The Si nanopillars array sensor is very attractive for sensing applications because their properties are highly sensitive to changes in the refractive index in the nanopillars array. In this kind of the Si nanopillars array sensor, the characteristic of the electromagnetic wave including amplitude, phase place, leaning towards polarized direction and wavelength can get enormously different results by controlling the light frequency spectrum, group velocity chromatic dispersion and phase matching. The Si nanopillars array sensor is biosensing because of the peculiar properties of the Si nanopillars array sensor such as the capability of enhance electromagnetic waves interaction and control Polarization Shift Keying (PolSK) fiber-optic system to measure polarization states to the impairments in the sensor.

The electric field can be localized in the slight refractive index region,

which makes the sensors extremely sensitive to the refractive index slight

change resulting from the infiltration of bio-molecules. The focus for our research is to detect the strongly polarization sensitivity of the Si nanopillars array sensor. We judge the bio-molecules from the slight different changes of refractive index, which caused sensor strongly polarization sensitivity, and observe signal constellation by Poincaré sphere based on Polarization Shift Keying (PolSK) fiber-optic system. By the infiltration of bio-molecules Si nanopillars array sensor structure caused by different group velocities of the polarization eigenmodes.

Therefore, in order to know the impairments of the variation state of polarization in the silicon nanopillars array. We use the instruments of the Polarization Shift Keying (PolSK) fiber-optic system to measure polarization states to the impairments in the sensor.

4-1-1 Introduction of PolSK Fiber-Optic System

Polarization modulation schemes have long been of interest to the

communications community. PolSK fiber-optic system encodes

information on a constellation of signal points in the space of the Stokes

parameters. In general, each signal point corresponds to a given state of

polarization and a given optical power. If only the polarization of the

lightwave, and not its power, is modulated, all the signal points lie on the Poincaré sphere. When a polarized lightwave is sent through the sensor, it is well-known that the state of polarization of the lightwave is altered due to the sensor using silicon nanopillars array and samples. However, if we look at a whole PolSK signal constellation, sensor polarization only causes a rigid rotation of the constellation over the Poincaré sphere. In other words, each of the signal points is displaced, but the spatial relationship between the points is preserved. As a result, we judge the bio-molecules from the slight different changes of refractive index, which caused sensor strongly polarization sensitivity, and observe signal constellation by Poincaré sphere.

All so far proposed PolSK systems make use of a binary modulation

scheme (2-PolSK) which information is sent by switching the

polarization of the transmitted lightwave between two linear orthogonal

SOPs. For binary systems, polarization modulation offers a 3 dB better

power sensitivity than intensity modulation and a reduced sensitivity to

self- and cross-phase modulation. Modulations based on the state of

polarization (SOP) are made possible by the fact that depolarization

phenomenon are of little importance even after relatively sensor spans.

Moreover, previous measurements [71] have shown that the rate of polarization changes due to the transit along the sensor is very low, and no significant variation can take place within a time span comparable with the symbol time. In the three-dimensional space defined by the Stokes parameters, two orthogonal SOPs map onto opposite points with respect to the origin. Thus, detection of binary modulation schemes is simply accomplished by looking at the sign of the scalar product of the received state of polarization (SOP) vector in the Stokes space with a reference vector representing one of the received SOPs in the absence of noise. This reference vector depends on the sensor induced changes on the transmitted SOPs, and for this reason, all 2-PolSK systems must somehow keep track of it. As to the effect of the laser phase noise, a general analytical treatment in coherent optical heterodyne receivers is not available. However, numerical analyses and experimental results have proved the considerable insensitivity to phase noise of receivers based on non-linear memory less processing of the signal, provided that the IF filter bandwidth is large enough to avoid phase-to-amplitude noise conversion [72].

Initially PolSK was both theoretically analyzed and experimentally

demonstrated only in conjunction with coherent detection [73-74]. This early work on coherent detection PolSK has established some important facts: sensor polarization effect does not corrupt polarization-encoded information and in particular the bit error probability is ideally unaffected;

sensor polarization effect compensation at the receiver is necessary but can be performed at the decision stage after photodetection; binary PolSK has a 40 photons/b quantum-limited sensitivity, whereas coherent ASK requires 80 photons/b (peak); binary and multilevel PolSK systems are largely insensitive to phase noise; multilevel PolSK quantum limited performance is better than DPSK if 3 b/symbol or more are transmitted.

4-1-2 The State of Polarization (SOP), Stokes Parameters and Poincare ' Sphere

There are three axes S

1

, S

2

and S

3

, and moves on the surface of a

sphere that we call the Poincare' sphere which is shown in Fig.4-1. The

polarization vector will be traced out a curve on the surface of the

Poincare' sphere by the different wavelength. If the device under test

(DUT) possession of the stable PMD the curve on the Poincare' sphere is

a circle. When the vector goes from the center of this circle through the

center of the Poincare' sphere that represents the principal axis of the device under test (DUT). The rate at the angle of the curve changes, divided by the rate at which the optical frequency changes, is the PMD.

Before introduce the definition of the Poincare' sphere, we have to describe the simple theoretics for the Stokes vector transformed from the Jones-matrix.

The polarized light can be described by using Jones-matrix as a complex vector symbolizing the x- and y- components of the electric field at a point in space which is shown in equation (4-1) [75-76]. When the light travels through a device that its own state of polarization (SOP) will undergo a transformation by the complex 2x2 Jones- matrix. The Jones-matrix is determined by measuring the output Jones vectors in response to any three-unique input vectors. The difference of the phase between x-axis and y-axis that define the δ(delta) in equation (4-2).

And, when the scope of theδ(delta) to lie in -π<δ< 0

^o

that we call the left circle polarization. The scope of theδ(delta) to lie in 0

^o

<δ<

180

^o

that we call the right circle polarization. It would describe the any

state of polarization with adjusting the magnitude and phase relationships

of the Ex(t) and Ey(t) components in a light wave signal. In 1852, Mr.

Stokes used the four parameters S

0

, S

1

, S

2

and S

3

to outright express the state of polarization (SOP) of the light wave in vector form, which is shown in equation (4-4) and (4-5). Since there are only three independent variables, the four Stokes parameters are verified as the following equation (4-3). And the Poincare' sphere uses the normalized S parameters (S

1

= S

1

/S

0

, S

2

= S

2

/S

0

, S

3

= S

3

/S

0

) by the total optical power as a co-ordinate system to represent any possible state of polarization (SOP). The range of the normalized Stokes parameters is –1 to +1. An alternative expression for the SOPs is the Stokes vector as shown in equation (4-6).

⎟ ⎟

⎠

⎞

⎜ ⎜

⎝

⎛

+ ω

⋅

+ ω

= ⋅

⎟ ⎟

⎠

⎞

⎜ ⎜

⎝

= ⎛

) P t cos(

E

) P t cos(

E )

t ( E

) t ( ) E

t ( E

y y

0

x x

0 y

r

x

r r

^(4-1)

x y

def

= P − P

δ ^{( - 180}

^o

< δ ≤ 180

^o

) ^(4-2)

2 3 2 2 2 1 2

0

S S S

S = + + ^(4-3)

The linear horizontal and vertical SOPs are represented respectively

as (1,0,0) and (-1,0,0). Similarly, the right hand circular polarization

(RHC) is represented as (0,0,1) while the left hand circular polarization

(LHC) is (0,0,-1). The remaining axis shows the linear +45

^o

and

linear –45

^o

states. The magnitude of the Stokes vector is the sum of

squares of S

1

, S

2

, and S

3

. The use of the Stokes vector parameters is best illustrated via the use of the Poincare' sphere that shown detailed in Fig.4-2

S=

⎟ ⎟

⎟ ⎟

⎟

⎠

⎞

⎜ ⎜

⎜ ⎜

⎜

⎝

⎛

=

±

=

=

=

=

⎟⎟

⎟ ⎟

⎟

⎠

⎞

⎜⎜

⎜ ⎜

⎜

⎝

⎛

SOP (LHC)

&

(RHC) between

difference Power

S

SOP 45 Linear between

difference Power

S

SOP Horizontal

&

Vertical between

difference Power

S

states) d

unpolarise and

polarised (in

Power Total

S

S S S S

3

0 2

1 0

3 2 1 0

(4-4)

S=

⎟⎟

⎟ ⎟

⎟

⎠

⎞

⎜⎜

⎜ ⎜

⎜

⎝

⎛

−

−

⇒ −

⎟⎟

⎟ ⎟

⎟ ⎟

⎠

⎞

⎜⎜

⎜ ⎜

⎜ ⎜

⎝

⎛

⋅

⋅

⋅

⋅

⋅

⋅

− +

=

⎟⎟

⎟ ⎟

⎟

⎠

⎞

⎜⎜

⎜ ⎜

⎜

⎝

⎛

− LCP RCP

total

oy ox

oy ox

oy ox

oy ox

I I

I I

I I

I

E E

E E

E E

E E

S S S S

ο ο

ο ο

δ

δ

45 45

90 0 2

2

2 2

3 2 1 0

sin 2

cos

2 ^(4-5)

S= _⎟⎟ ^⎟

⎟ ⎟

⎠

⎞

⎜⎜

⎜ ⎜

⎜

⎝

⎛

⋅

= ⋅

⎟ ⎟

⎟ ⎟

⎟ ⎟

⎟ ⎟

⎟ ⎟

⎠

⎞

⎜ ⎜

⎜ ⎜

⎜ ⎜

⎜ ⎜

⎜ ⎜

⎝

⎛

⋅

⋅

⋅

⋅

⋅

⋅

− +

=

⎟ ⎟

⎟ ⎟

⎟ ⎟

⎟ ⎟

⎠

⎞

⎜ ⎜

⎜ ⎜

⎜ ⎜

⎜ ⎜

⎝

⎛

ε θ ε

θ ε

δ δ

2 sin

2 sin 2 cos

2 cos 2

cos 1

sin 2

cos 2

2 2

2 2

3 0 2 1

o oy ox

o oy ox

o oy ox

o oy ox

o o o o

S E E

S E E

S E E

S E E

S S

S S

S S

S S

(4-6)

The relationships between the β, ellipticityεand azimuthθ

which is sketch the map in the Fig. 4-3 [77]. Furthermore, the

relationships of the parameters definitions is listed as following:

Phase Angle -180

^o

<δ< 180

^o

= tan δ S

S

2 3

Ellipticity - 45

^o

<ε< + 45

^o

= sin 2 ε S

S

0 3

Azimuth 0

^o

<θ< 180

^o

= tan 2 θ S

S

1 2

Direction 90

^o

<β< -90

^o

= tan β E

E

ox oy

4-2 Introduction of Measure Bio-molecular Samples

In this section, we will test the virus, DNA and germ which are discussed extensively. We hope that our sensor can diagnosis virus and the innovation technique will be contributed for the medical field. The discussed sample in this section as following:

I. Plasmid

Plasmids are (typically) circular double-stranded DNA molecules separate from the chromosomal DNA and capable of autonomous replication. They usually occur in bacteria, sometimes in eukaryotic organisms (e.g., the 2-micrometre-ring in Escherichia coli). Their size varies from 1 to over 400 kilobase pairs (kbp). There are anywhere from one copy, for large plasmids, to hundreds of copies of the same plasmid present in a single cell, or even to thousands of copies for certain artificial plasmids selected for high copy number (such as the pUC series of plasmids) [78].

II. Herpes Simplex Virus Type-1 (HSV-1)

The herpes simplex virus (HSV) is a double-stranded DNA virus

with an enveloped, icosahedral capsid. There are two distinct types of the

virus, herpes simplex virus type-1 (HSV-1) and herpes simplex virus

type-2 (HSV-2), both of which are closely related α-herpesviruses (having a broad host range). Here we focus on herpes simplex virus type-1 (HSV-1) to study. It is a common cause of infections of the skin and mucous membranes, manifesting itself as tiny, clear, fluid-filled blisters usually around the mouth. Upon entering the body through oral transmission, HSV-1 penetrates the nerve cells (primary sensory neurons) in the lower layers of human skin tissue and replicates itself in the cell nuclei, thus destroying host cells. HSV-1 has a great impact on human health globally due to its high prevalence in particular children [79].

III. Glucose

Diabetes is now a serious global problem that has attracted continuous interest for the development of an efficient glucose sensor.

Because insulin is the principal hormone that regulates uptake of glucose into most cells from the blood (primarily muscle and fat cells, but not central nervous system cells), deficiency of insulin or the insensitivity of its receptors plays a central role in all forms of diabetes mellitus. Much of the carbohydrate in food is converted within a few hours to the monosaccharide glucose, the principal carbohydrate found in blood.

Some carbohydrates are not converted. Insulin is released into the blood

by beta cells (β-cells) in the pancreas in response to rising levels of blood

glucose (e.g., after a meal). Insulin enables most body cells (about 2/3 is

the usual estimate, including muscle cells and adipose tissue) to absorb

glucose from the blood for use as fuel, for conversion to other needed

molecules, or for storage. Insulin is also the principal control signal for

conversion of glucose (the basic sugar used for fuel) to glycogen for

internal storage in liver and muscle cells. Reduced glucose levels result

both in the reduced release of insulin from the beta cells and in the

reverse conversion of glycogen to glucose when glucose levels fall,

although only glucose thus recovered by the liver re-enters the

bloodstream as muscle cells lack the necessary export mechanism. Higher

insulin levels increase many anabolic ("building up") processes such as

cell growth and duplication, protein synthesis, and fat storage. Insulin is

the principal signal in converting many of the bidirectional processes of

metabolism from a catabolic to an anabolic direction, and vice versa. In

particular, it is the trigger for entering or leaving ketosis (i.e., the fat

burning metabolic phase). If the amount of insulin available is

insufficient, if cells respond poorly to the effects of insulin (insulin

insensitivity or resistance), or if the insulin itself is defective, glucose will

not be handled properly by body cells (about ⅔ require it) or stored appropriately in the liver and muscles. The net effect is persistent high levels of blood glucose, poor protein synthesis, and other metabolic derangements, such as acidosis [80].

VI. Saccharomyces cerevisiae

A species of yeast which is an important mode organism for

biological study, particularly for genetics and molecular biology. The

entire genome of this species has been base sequenced and it is used to do

research on basic cellular mechanics of replication, recombination, cell

division and metabolism. Saccharomyces cerevisiae is also economically

important in the food industry, where it is used to ferment grain sugars to

make beer and as baker’s yeast for baking bread or making other food

which requires rising by gas bubbles of carbon dioxide. It is also

sometimes taken as a vitamin supplement for protein, the B vitamins, and

folic acid [81].

4-3 Experimental Results of PolSK Communication with theDNA

In this section, we will test the virus, DNA and germ which are discussed extensively. The discussed sample in this section as following:

I. Plasmid II. Herpes Simplex Virus Type-1 (HSV-1) III. Saccharomyces VI. Glucose as Fig. 4-4 shows.

The experimental setups for measuring polarization states from the

silicon nanopillars array sensor are shown in Fig. 4-5. An HP8168

tunable laser, with a tunability range of 1440-1590 nm, is used as our

source. In order to optimize the intensity of the TE polarized-light, a fiber

polarization controller is inserted between the laser and the input tapered

lensed fiber as shows Fig. 4-9. To improve the signal to noise ratio, a

polarizer that transmits only TE-polarized light is inserted between the

device and the detector. The Si nanopillars array sensor is biosensing

because of the peculiar properties of the Si nanopillars array sensor such

as the capability of enhance electromagnetic waves interaction and

control Polarization Shift Keying (PolSK) fiber-optic system to measure

polarization states to the impairments in the sensor. The picture of the

experiment frame with measuring polarization states from the silicon

nanopillars array sensor is shown in Fig. 4-6 and Fig.4-7. Fig. 4-8

explains we use the sensor to soak in the solution of sample and come to

do the experimentation and analysis. We judge the bio-molecules from

the slight different changes of refractive index, which caused sensor

strongly polarization sensitivity, and observe signal constellation by

Poincaré sphere. Average result of the state of polarization measurement

of air which has no liquid to sensor is shown Fig. 4-10 at TE mode. From

the result we can obviously observe the trajectory of the polarization

states, Azimuth 2.124

^o

±0.1

^o

and Ellipticity 0.585

^o

±0.15

^o

. We find the

polarization state of our measurement result is very stable and it has a

unique polarization states. Average result of the state of polarization

measurement of water is shown Fig. 4-11 at TE mode. From the result we

can obviously observe the trajectory of the polarization states, Azimuth

5.434

^o

±1

^o

and Ellipticity 2.3825

^o

±0.5

^o

. We find the polarization state of

our measurement result is very stable and it has a unique polarization

states. The rotated orientation variation is as shown in Fig. 4-11, which

makes the sensors extremely sensitive to the refractive index slight

change resulting from the infiltration of water-molecules. Then we will

test the virus, DNA and germ. In case I, average result of the state of

polarization measurement of Plasmid is shown Fig. 4-12 at TE mode.

From the result we can obviously observe the trajectory of the polarization states, Azimuth 7.041

^o

±1.1

^o

and Ellipticity 3.763

^o

±0.65

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states. The rotated orientation variation is as shown in Fig. 4-12, which makes the sensors extremely sensitive to the refractive index slight change resulting from the infiltration of Plasmid-molecules. In case II, average result of the state of polarization measurement of Herpes Simplex Virus Type-1 (HSV-1) is shown Fig.

4-13 at TE mode. From the result we can obviously observe the trajectory

of the polarization states, Azimuth -73.483

^o

±0.5

^o

and Ellipticity

2.093

^o

±1.41

^o

. We find the polarization state of our measurement result is

very stable and it has a unique polarization states. The rotated orientation

variation is as shown in Fig. 4-13, which makes the sensors extremely

sensitive to the refractive index slight change resulting from the

infiltration of Herpes Simplex Virus Type-1-molecules. In case III,

average result of the state of polarization measurement of Glucose is

shown Fig. 4-14 at TE mode. From the result we can obviously observe

the trajectory of the polarization states, Azimuth -69.673

^o

±0.268

^o

and

Ellipticity 6.573

^o

±0.73

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states.

The rotated orientation variation is as shown in Fig. 4-14, which makes the sensors extremely sensitive to the refractive index slight change resulting from the infiltration of Glucose-molecules. In case VI, average result of the state of polarization measurement of Saccharomyces is shown Fig. 4-15 at TE mode. From the result we can obviously observe the trajectory of the polarization states, Azimuth -68.555

^o

±0.707

^o

and Ellipticity 8.213

^o

±0.562

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states.

The rotated orientation variation is as shown in Fig. 4-15, which makes the sensors extremely sensitive to the refractive index slight change resulting from the infiltration of Saccharomyces -molecules.

In order to optimize the intensity of the TM polarized-light, a fiber

polarization controller is inserted between the laser and the input tapered

lensed fiber as shown Fig. 4-16. Average result of the state of polarization

measurement of air which has no liquid to sensor is shown Fig. 4-17 at

TM mode. From the result we can obviously observe the trajectory of the

polarization states, Azimuth -88.467

^o

±0.1

^o

and Ellipticity 1.425

^o

±0.15

^o

.

We find the polarization state of our measurement result is very stable and it has a unique polarization states. Average result of the state of polarization measurement of water is shown Fig. 4-18 at TM mode. From the result we can obviously observe the trajectory of the polarization states, Azimuth -87.934

^o

±0.289

^o

and Ellipticity 4.093

^o

±1.25

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states. The rotated orientation variation is as shown in Fig. 4-18, which makes the sensors extremely sensitive to the refractive

index slight change resulting from the infiltration of water-molecules.

Then we will test the virus, DNA and germ at TM mode. In case I, average result of the state of polarization measurement of Plasmid is shown Fig. 4-19 at TM mode. From the result we can obviously observe the trajectory of the polarization states, Azimuth 89.927

^o

±1.1

^o

and Ellipticity 5.341

^o

±0.233

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states.

The rotated orientation variation is as shown in Fig. 4-19, which makes

the sensors extremely sensitive to the refractive index slight change

resulting from the infiltration of Plasmid-molecules. In case II, average

result of the state of polarization measurement of Herpes Simplex Virus

Type-1 (HSV-1) is shown Fig. 4-20 at TM mode. From the result we can obviously observe the trajectory of the polarization states, Azimuth 88.178

^o

±1.364

^o

and Ellipticity 2.169

^o

±0.632

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states. The rotated orientation variation is as shown in Fig.

4-20, which makes the sensors extremely sensitive to the refractive index

slight change resulting from the infiltration of Herpes Simplex Virus Type-1-molecules. In case III, average result of the state of polarization measurement of Glucose is shown Fig. 4-21 at TM mode. From the result we can obviously observe the trajectory of the polarization states, Azimuth -88.588

^o

±0.486

^o

and Ellipticity 3.5217

^o

±0.95

^o

. We find the polarization state of our measurement result is very stable and it has a unique polarization states. The rotated orientation variation is as shown in Fig. 4-21, which makes the sensors extremely sensitive to the refractive

index slight change resulting from the infiltration of Glucose-molecules.

In case VI, average result of the state of polarization measurement of

Saccharomyces is shown Fig. 4-22 at TM mode. From the result we can

obviously observe the trajectory of the polarization states, Azimuth

-87.996

^o

±0.876

^o

and Ellipticity 1.971

^o

±1.1

^o

. We find the polarization

state of our measurement result is very stable and it has a unique polarization states. The rotated orientation variation is as shown in Fig.

4-22, which makes the sensors extremely sensitive to the refractive index

slight change resulting from the infiltration of Saccharomyces

-molecules.

4-4 Summary

Si nanopillars array sensor can be used to judge biomolecules

attached to the device surfaces. In the demonstration of the

experimentation, small molecules (Plasmid, HVS-1, Glucose,

Saccharomyces cerevisiae) can be judged by monitoring the polarize

variation. In this chapter, the experiment not only judges sensing of

biomolecules, but also shows that such silicon nanopillars array sensor

are capable of detecting both DNA and germ without using fluorescent

labels. This is a very promising value from this preliminary experiment in

comparison with other planar optical biosensors. The sensor based on

Polarization Shift Keying (PolSK) fiber-optic system can have a higher

sensitivity compared to other label-free detection methods, such as

surface plasma resonance, quartz microbalance, and microcantilever

sensors. With these capabilities, silicon nanopillars array sensors can

potentially be used in many areas such as drug discovery, disease

diagnostics, chemical analysis and environmental monitoring. We believe

this technology can bring revolutionary medical treatment to the

mankind.

S1 S2 S3

Fig. 4-1 The principal axis of the Poincar'e sphere

S ₁

S ₂

( 1 0 0

( -1,0,0 ( 0,-1,0

( 0,1,0

( 0,0,-1 ) ( 0,0,1 )

δ=0°

δ=90°

δ

δ= -90°

δ=45°

δ=135°

δ= - 45°

2Θ

2ε δ

δ=135°

Poincaré Sphere S3

x y

δ

y

2Eox

2Eoy

a

b O

Fig.4-4 The discussed sample in this section as following: I. Plasmid II.

Herpes Simplex Virus Type-1 (HSV-1) III. Saccharomyces VI. Glucose.

Fig. 4-3 The relationships among the β, ellipticity ε and azimuth θ

Θ β ε

x

Phase Angle

Ellipticity

Azimuth

Direction

-90 < <90 ^oy tan

ox

E

β E β

° ° =

2 1

2 0 < <180 S tan

θ S θ

° ° =

3 0

2 -45 < <+45 S sin

ε S ε

° ° =

3 2

-180 < <180 S tan

θ S δ

° ° =

I II III VI

Polarimeter

Sample

Polarization Controller Laser

Source

PC

Fig.4-5 Experimental setups for measuring polarization states from the silicon nanopillars array sensor.

Fig.4-6 The picture of the experiment frame.

Fig.4-7 The picture of the experiment frame with measuring polarization states from the silicon nanopillars array sensor.

Fig.4-8 Utilize the sensor to soak in the solution of sample.

TE

S

₁

S

₂

S

₃

Fig.4-9 Set up, the experiment of TE mode light.

Air Molecule

S

₁

S

₂

S

₃

Fig.4-10 Average result of the state of polarization measurement of air

S

₁

S

₂

S

₃

Water Molecule

Fig. 4-11 Average result of the state of polarization measurement of water for TE mode.

S

₁

S

₂

S

₃

Plasmid

Fig. 4-12 Average result of the state of polarization measurement of

Plasmid for TE mode.

HSV-1

S

₁

S

₂

S

₃

Fig. 4-13 Average result of the state of polarization measurement of Herpes Simplex Virus Type-1 (HSV-1) for TE mode.

S

₁

S

₂

S

₃

Glucose

Fig. 4-14 Average result of the state of polarization measurement of

Saccharomyces

S

₁

S

₂

S

₃

Fig. 4-15 Average result of the state of polarization measurement of Saccharomyces for TE mode.

TM

S

₁

S

₂

S

₃

Fig. 4-16 Set up, the experiment of TM mode light.

Air Molecule

S

₁

S

₂

S

₃

Fig. 4-17 Average result of the state of polarization measurement of air which has no liquid to sensor for TM mode.

S

₁

S

₂

S

₃

Water Molecule

Fig. 4-18 Average result of the state of polarization measurement of

Plasmid

S

₁

S

₂

S

₃

Fig. 4-19 Average result of the state of polarization measurement of Plasmid for TM mode.

S

₁

S

₂

S

₃

HSV-1

Fig. 4-20 Average result of the state of polarization measurement

ofHerpes Simplex Virus Type-1 (HSV-1) for TM mode.

Glucose

S

₁

S

₂

S

₃

Fig. 4-21 Average result of the state of polarization measurement of Glucose for TM mode.

S

₁

S

₂

S

₃

Saccharomyces

Fig. 4-22 Average result of the state of polarization measurement of