ALUMINUM NITRIDE MEMS

RESONANT THERMAL BIOSENSORS

A Thesis Presented

by

Raul Vyas

to

The Department of Electrical and Computer Engineering

in partial fulfillment of the requirements

for the degree of Master of Science

in

Electrical Engineering

in the field of

Microsystems, Materials and Devices

Northeastern University, Boston, MA

August 2014

© Copyright 2014 by Raul Vyas

All Rights Reserved

To my family

Acknowledgements

First I would like to express my most sincere gratitude to my advisor Prof. Matteo Rinaldi

for providing me such a precious opportunity to work in the field of MEMS/NEMS design and his

unwavering support towards my research, and belief in my efforts. His practical and hands-on

approach to tackle important research problems set an example for me of what a truly dynamic

and successful engineer should be.

I also wish to thank my colleagues and group members, especially Yu Hui and Zhenyun

Qian, who shared many helpful experiences and knowledge with me, and whose response to my

queries would always be positive and readily available. They always set an example, a benchmark

that I and others in our research group would try to emulate.

I am very grateful to the staff of the George J. Kostas Nanoscale Technology and

Manufacturing Research Center at Northeastern University, especially Scott Mcnamara, where the

devices reported in this thesis were fabricated.

Most of all, I would like to express immense gratitude to my family who, even if living far

away, made me feel their unconditional love and support always present and helped me overcome

many professional and personal issues that I encountered on this fantastic journey.

ABSTRACT

Calorimetry is a very effective technique employed for analyzing biochemical reactions

(glucose and urea sensing, DNA detection and biodefense). Most of the commercial micro-

calorimetric sensors available in the market don’t have either a simple operational configuration

(amperometric sensors which rely on a detection of ions in a solution based on changes in electric

current), or can only detect temperature changes in the range of 0.1-0.2 K. The most important

performance metrics that ought to be considered for the design and optimization of micro-

calorimetric biochemical sensors are the thermal detection capabilities of the sensing element and

the thermal coupling between the biochemical reaction and the thermal detector. All these

fundamental challenges are addressed in this thesis by taking advantage of advanced material

properties and innovative device engineering, the result of which are high temperature resolution

(994.5 µK/Hz1/2 in a 50 Hz measurement bandwidth and 534.355 µK/Hz1/2 in a 200 Hz

measurement bandwidth) micro-calorimetric sensors based on high frequency (134.5 MHz and

116.67 MHz) Aluminum Nitride (AlN) nano-plate resonators (NPR), overlapped by a freestanding

reaction chamber separated by a micro-scale air gap (~50 m). High sensitivity (~8.66 ppm/K and

~22.2 ppm/K) and low noise performance (~1.16 Hz/Hz1/2 in a 50 Hz bandwidth) are achieved by

scaling the overall volume of the resonant structure and by taking advantage of two high quality

factor, Q (~882 and ~985), resonant systems. Efficient thermal coupling between the biochemical

reaction and the resonant thermal detector is achieved by reducing to ~50 m the air gap between

the resonator and the freestanding reaction chamber. The non – contact measurement also reduces

the degradation of performance metrics like mass loading effects.

The unique thermal detection capabilities of the AlN NPR calorimetric sensors enabled the

monitoring of Urea and Glucose enzymatic reactions, as well as exothermic Acid-base

neutralization reactions using Hydrochloric Acid, Ammonium Hydroxide and Sodium Hydroxide.

The effectiveness of the fabricated micro-calorimetric sensor prototype for monitoring chemical

reactions was characterized by sequentially placing in the reaction chamber different

concentrations of Acid and Base and monitoring the resonator frequency shift induced by the heat

generated by the exothermic reaction at each concentration. As expected, saturation was reached

when the concentration ratio between the two chemicals was 1:1, because maximum heat is

generated at equal concentrations, resulting in a maximum frequency shift. For the biochemical

enzymatic reactions, sensitivities of 9.4815 kHz/M for urea and 2.583 kHz/M for glucose were

obtained. Detection limits for urea and glucose measurement were calculated to be 61.22 M and

535.803 M respectively. The experimental results also demonstrate the great potential of the

proposed technology for the implementation of a new class of high temperature resolution and low

noise AlN NPR thermal detection based biochemical sensors.

Contents

1. INTRODUCTION 1

2. CALORIMETRIC BIO-SENSORS 3

2.1 Parameters of Calorimetric Biosensors 6

3. ALUMINIUM NITRIDE NANO PLATE RESONANT (AlN-NPR)

THERMAL DETECTORS 8

3.1 Motivation 8

3.2 Aluminum nitride nano plate resonators 11

3.3 Important Parameters of an AlN nano plate resonant thermal detector 19

3.4 Initial design of the Thermal detector 23

4. FABRICATION & ASSEMBLY: AlN NPR THERMAL

DETECTOR 26

5. RESULTS 39

5.1 Temperature Sensitivity 39

5.2 Finite Element Method (FEM) Simulation 41

5.3 Acid-Base Neutralization Reaction 45

5.4 Enzymatic Hydrolysis of Urea 49

6. NOISE PERFORMANCE 52

6.1 Peak to Peak Noise 52

6.2 Root Mean Square (RMS) Noise 52

6.3 Noise Spectral Density 53

6.4 Detection Resolution 53

7. PROTOTYPE II – GLUCOSE SENSING 54

8. CONCLUSIONS 59

8.1 Summary 59

8.2 Future Work 61

9. REFERENCES 63

1

1. INTRODUCTION

In recent years, Micro and Nano Electro Mechanical Systems (MEMS/NEMS) resonators

have been widely used for multiple sensing applications thanks to the unique combination of

extremely high sensitivity to external perturbations and ultra-low noise performance. Of all the

MEMS/NEMS resonant sensors that are in the market or under development, the AlN nano plate

resonant sensor (NPR-S) technology [1], which involves exciting high frequency (100 MHz to 10

GHz) bulk acoustic waves in piezoelectric nano plates (thickness < 1 μm) developed using

Aluminum Nitride, can be seen as a frontrunner for realizing highly sensitive, miniaturized and

low power chemical sensors [2], thermal detectors [3], and magnetic field sensors [4]. The reduced

mass and high frequency of operation of the nanomechanical resonant elements combined with

their high Q factor values make the AlN NPR-S capable to achieve unprecedented values of limit

of detection and detection speed [2-5].

The work presented in this thesis explores the potential of using the Aluminum Nitride

Nano Plate resonator technology for the development of high performance micro-calorimetric

biochemical sensors. For the first time, the unique scaling capabilities and the excellent

piezoelectric transduction properties of Aluminum Nitride, characterized by high values of Quality

factor and temperature sensitivity are utilized to construct Thermal Biosensors. By placing the

biochemical reaction chamber out of the resonant body of the device (but suspended over it), the

electromechanical performance of the resonator is unaffected by the chamber and the materials

used to implement it. Efficient heat transfer from the reaction chamber to the resonator is achieved

by scaling the air gap between them.

The thesis is organized in the following chapters:

2

Chapter 2 explores the idea of a biosensor and details the benefits of using calorimetry for

biosensing applications. It further describes the various performance metrics and characteristics of

a biosensor.

In Chapter 3, the motivations behind using an AlN MEMS Resonator for thermal detection

are explored. After reviewing the mechanism and fundamental parameters of the Aluminum

Nitride Nano Plate Resonator (AlN NPR), the analysis and optimization of the thermal detection

capabilities of Aluminum Nitride Nano Plate Resonant Sensor (AlN NPR-S) are introduced. It

further explores the idea of using AlN-NPR as a thermal detector through a Finite Element Method

(FEM) Simulation, and describes the salient features of such a detector.

In Chapter 4, the design and fabrication solutions of the proposed Aluminum Nitride Nano

Plate Resonator (AlN-NPR) thermal detector as well as simulation verification using Finite

Element Method (FEM) are presented. Measured Temperature Coefficient of Frequency (TCF) of

the AlN NPR is reported and discussed. At the end of chapter 3, there is a detailed account of the

thermal detector assembly.

Chapter 5 presents the experimental demonstration of a prototype of AlN-NPR based

thermal detector, and its ultimate utilization as a biosensor. The effectiveness of the fabricated

prototype is verified by monitoring exothermic acid-base neutralization reactions, and is

characterized as a biosensor by monitoring the catalytic hydrolysis of urea in the presence of

urease.

Chapter 6 discusses the Noise performance of the biosensor described in chapter 5.

In Chapter 7, another prototype of AlN-NPR based thermal biosensor is presented and

characterized by monitoring the catalytic oxidation of glucose in the presence of glucose oxidase.

3

2. CALORIMETRIC BIO-SENSORS

An analytical device which functions to analyze a sample for the presence of a specific

compound is known as sensor. A sensor which utilizes biological material to specifically interact

with an analyte is known as biosensor. An analyte refers to the compound which has to be ‘sensed’

or the presence of which has to be determined. The interaction of analyte and biosensor is measured

and converted to signals, which are again amplified and displayed. A biosensor thus involves

converting a chemical flow of information into electrical signals. The biological materials used in

biosensors are mostly enzymes, antibodies, nucleic acids, lectins and even a cell as a whole.

A Biosensor mainly consists of two major components, as shown in figure 1. The

Biological component constitutes of enzymes, antibodies and other biological materials which

mainly interacts with the analyte particles and induces a physical change in these particles. The

Transducer component collects information from the biological part, converts, amplifies and

displays them.

There are several different types of biosensors based on different interpretations of the

results of the analyte – bioreceptor interaction and the transduction principle, as shown in figure

2, like Potentiometry – where an electric potential is produced, Amperometry – where the

analyte/biological material interaction induces a redox reaction resulting in a movement of

4

electrons, Optometry – where light is released, and Calorimetry. A calorimeter is a device used

for calorimetry, the science associated with determining the changes in energy of a system by

measuring the heat exchanged with the surroundings. A calorimetric biosensor uses calorimetry as

the basic transduction principle by measuring the heat of a reaction on the sensor surface.

Calorimetric sensors are perfect as an application of thermal sensors because they can be used to

determine physical properties, including the enthalpy of chemical reaction, biochemical

transformation, and the heat capacity of a material, from measurements of a temperature difference

across a thermal resistance through which heat flows. Calorimetry is a very effective technique

employed for analyzing biochemical reactions, and offers distinctive advantages over other

measurement techniques for biomolecular characterization. Moreover, enzyme-catalyzed

reactions show high selectivity and typically involve an enthalpy change, which makes them

highly suitable for configuring them as thermal biosensors for a broad range of applications. Most

of these enzyme-catalyzed reactions are biological in nature and are exothermic, enabling detection

by calorimetric analysis. Calorimetry allows direct determination of thermodynamic properties,

and is universally applicable to a wide variety of biomolecules in that almost all reactions are

thermally active. Additionally, calorimetric measurements occur in solution phase without

requiring the biomolecule to be attached to solid surfaces. It is label-free in that it does not require

biomolecules to be labeled with a radioactive, enzymatic or fluorescent labeling groups to report

molecular binding or conformational changes.

5

Figure 1: Typical Components of Biosensors

6

1.1 Parameters of Calorimetric Biosensors

There are several static as well as dynamic parameters that can be used to characterize the

performance of calorimetric biosensors. The following list explains these parameters in detail.

Sensitivity: It refers to a change in the measurement signal per concentration

unit/temperature variation of the analyte, depending on whether the sensor is characterized

as a biosensor or a thermal sensor. Essentially, it is the slope of a calibration graph.

Detection Limit: The lowest value which can be detected by the sensor in question, under

definite conditions. Procedures for evaluation of the detection limit depend on the kind of

sensor considered.

Selectivity: An expression of whether a sensor responds selectively to a group of analytes

or even specifically to a single analyte.

Resolution: The lowest concentration/temperature difference which can be distinguished

when the composition is varied continuously.

7

This parameter is important chiefly for detectors in flowing streams/liquid-phase biochemical

reactions.

Response Time: The time required for a sensor to change from a zero value to a step

change. Usually specified as the time to rise to a definite ratio of the final value. The time

which has elapsed until 63 percent of the final value is reached is called the time constant.

Heat Transfer Efficiency: It is defined as the ratio between the temperatures of the detector

element and the source of heat.

Some other parameters like Dynamic Range, Selectivity, Linearity, and stability are also

important for characterizing the performance of a biosensor, but are usually only applicable for

commercial products.

8

3. ALUMINIUM NITRIDE NANO PLATE

RESONATOR (AlN-NPR) THERMAL

DETECTORS

3.1 MOTIVATION

The demand for highly miniaturized sensors capable of detecting minuscule concentrations

of multiple liquid phase and gaseous analytes has grown in recent years, and the necessity to detect

such small concentrations requires reliably measuring extremely small variations in the sensor

output signal like voltage and frequency. In this perspective, optimal sensor performance is

facilitated by synthesizing a transducer that occupies a large area (which, in turn, facilitates

efficient transduction) and is very thin (which allows fabricating low mass devices with ultra-high

sensitivity). Suspended membranes with thickness in the nanometer range are therefore desirable

for sensing applications. Aluminum Nitride Nano Plate Resonators (AlN-NPR), first proposed by

Prof. Matteo Rinaldi are a particularly representative example of high performance bulk mode

acoustic NEMS contour-mode resonant sensors which involve exciting high frequency bulk

acoustic waves in a piezoelectric nano-plate (thickness 50 ~ 500 nm) made of Aluminum Nitride

(AlN). Such AlN Piezoelectric Nano-Plate Resonant Sensor (NPR-S) technology is not only

characterized by high values of sensitivity, due to the reduced mass and high frequency of

operation of the nanomechanical resonant element, but is also associated with low noise

performance, due to the combination of high quality factor, Q, and power handling capability of

9

the bulk acoustic wave NEMS resonators [6]. Concurrently, the device is very well isolated from

the heat sink (high thermal resistance) and has a very small volume (small thermal mass) which

are all desired parameters for a thermal sensor. In addition, the AlN nano-plate composing the

NPR-S can be efficiently actuated and sensed piezoelectrically on-chip solving the fundamental

transduction issues associated with electrostatically transduced NEMS resonators.

For a thermal detector, a vital parameter to consider is the Temperature/Thermal

Sensitivity. In case of a resonator, it is given by the following equation –

𝑇ℎ𝑒𝑟𝑚𝑎𝑙 𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 = Δ𝑓 × 106

𝑓0 × ΔT 𝑝𝑝𝑚/𝐾

Where, Δ𝑓 is the shift in the resonance frequency of the resonator, 𝑓0 is the fundamental resonance

frequency and ΔT is the change in temperature. This sensitivity is characterized by the Temperature

Coefficient of Frequency (TCF), i.e., higher the TCF, higher is the sensitivity. Now,

miniaturization of the AlN-NPRs results in a higher TCF. This is due to the effect of the electrodes,

whose thickness becomes a considerable fraction of the AlN film in the resonator implementation,

where the Young’s modulus of the metal electrodes is considered in the measurement of equivalent

TCF [7]. Nevertheless, the sensitivity cannot be considered the only important parameter for the

design of a high performance resonator based thermal detector. In fact, the detection resolution of

the sensor, described as the smallest change in a parameter (temperature in case of a thermal

detector and concentration in case of a biosensor) in a given measurement bandwidth is given as-

𝐷𝑒𝑡𝑒𝑐𝑡𝑖𝑜𝑛 𝑅𝑒𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛 ∝Δ𝑓

𝑚𝑖𝑛

𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦

Where Δ𝑓𝑚𝑖𝑛 is the minimum noise-induced frequency fluctuation, which is proportional to –

10

Δ𝑓𝑚𝑖𝑛 ∝ √𝑘𝐵𝑇0𝐵

𝑃.𝑓0𝑄

Where kB

is Boltzmann constant, T0

is temperature, B is the measurement bandwidth, P is the

driving power and Q is the quality factor. Δ𝑓𝑚𝑖𝑛 is directly related to the noise performance of the

AlN-NPR, and should be as low as possible. Hence, for a better noise performance, Q has to be

higher, which an important factor behind choosing the AlN Nano Plate Resonator for thermal

sensing.

The potential of using MEMS resonators for the development of high performance IR

thermal detectors has been recently demonstrated through the implementation of highly

temperature sensitive gallium nitride [8] and Y-cut quartz [9] MEMS resonators. Also, MEMS

technology has been currently used in the market by manufacturers like Analog Devices and

Omron for the development of Thermal Sensors. However, most of these sensor technologies are

bulky, costly and suffer from fundamental challenges like mass loading and low thermal

sensitivities. In this thesis, the unique scaling capabilities and the excellent piezoelectric

transduction properties of Aluminum Nitride are exploited for the fabrication of a high frequency

and small volume resonant structure characterized by high values of Quality factor and temperature

sensitivity, which is then developed into a Thermal Biosensor. Furthermore, by placing the

biochemical reaction chamber out of the resonant body of the device (but suspended over it), the

electromechanical performance of the resonator is unaffected by the chamber and the materials

used to implement it. Efficient heat transfer from the reaction chamber to the resonator is achieved

by scaling the air gap between them.

11

3.2 ALUMINUM NITRIDE NANO PLATE

RESONATORS

The Physical properties of AlN are desirable to both MEMS designers and large research

community. An III–V semiconductor, many of its material properties are a result of its close–

packed tetrahedral diamond-like crystal structure. Under ambient conditions, the

thermodynamically–stable structure (Figure 3) of AlN is hexagonal wurtzite (a hexagonal closed

packed structure), and exhibits direct piezoelectric effect.

Figure 3: Wurtzite hexagonal close-packed structure of AlN with Nitrogen atoms in white circles and Al

atoms in black circles.

12

A solid is defined as piezoelectric if it becomes electrically polarized when subjected to a

mechanical stress. When an applied stress creates a strain in the structure of a crystal, there is a

small change in the bond lengths between the atoms, resulting in a shift in the positions or

directions of the individual dipoles. In most crystals, the constituent atoms of the crystal are

distributed such that the sum of the individual dipoles between all of the atoms is zero. However,

in the case of AlN, the stress results in the formation of a nonzero dipole—a manifestation of

piezoelectricity. The piezoelectric effect can be expressed mathematically using equations that

describe the electric and structural behaviors of a material. One of them, the electric displacement

is defined as –

𝐷 = 𝜀𝐸 (1)

Where 𝜀 is the permittivity matrix of the material and 𝐸 is the applied electric field. Similarly,

Hooke’s law for mechanical strain is given by –

𝑆 = 𝑠𝜎 (2)

Where 𝑠 is the elastic compliance tensor of the material and 𝜎 is the stress. However, if we take

into account the electromechanical coupling, the above equations can be written as –

S = 𝑠𝜎 + 𝑑𝜎𝐸 (3)

D = 𝑑𝜎 + 𝜀𝐸 (4)

13

Where 𝑑𝜎 is the transpose of the strain-charge form (d-form) piezoelectric coefficient.

Equation 4 expresses the direct piezoelectric effect, whereas equation 3 expresses converse

piezoelectric effect, where an applied voltage induces a stress in the material. The converse effect

is often used to determine the piezoelectric coefficients. The equations of state corresponding to

Wurzite-type-structure Aluminium Nitride can be expressed in the following matrix form, based

on above equations –

[ 𝑆1𝑆2𝑆3𝑆4𝑆5𝑆6]

=

[ 𝑠11 𝑠12 𝑠13 0 0 0𝑠21 𝑠22 𝑠23 0 0 0𝑠31 𝑠32 𝑠33 0 0 00 0 0 𝑠44 0 00 0 0 0 𝑠44 00 0 0 0 0 2(𝑠11 − 𝑠12)]

.

[ 𝜎1𝜎2𝜎3𝜎4𝜎5𝜎6]

+

[ 0 0 𝑑310 0 𝑑310 0 𝑑330 𝑑15 0𝑑15 0 00 0 0 ]

.[𝐸1𝐸2𝐸3

] (5)

[𝐷1𝐷2𝐷3

] = [

0 0 0 0 𝑑15 00 0 0 𝑑15 0 0𝑑31 𝑑31 𝑑33 0 0 0

].

[ 𝜎1𝜎2𝜎3𝜎4𝜎5𝜎6]

+ [𝜀11 0 00 𝜀11 00 0 𝜀33

]. [𝐸1𝐸2𝐸3

] (6)

The piezoelectric coefficient 𝑑𝑖𝑗is the ratio of the strain in the j-axis to the electric field

applied along i-axis, when all external stresses are held constant. The 𝑑33 coefficient has been

exploited in film bulk acoustic wave resonators (FBARs), which employ thickness-extensional mode

of vibration, for duplexer applications [4-5], but their resonant frequency is set by the thickness of a

thin film piezoelectric material such as AlN, which is not suitable for single chip multi-frequency

operation. A comparison of different modes of vibration in AlN is given in Table 1.

14

Mode of Vibration Frequency Equation Uses

Flexural

𝑓0 ∝ 𝑇

𝐿2√𝐸

𝜌

[10KHz – 10MHz]

Suitable for High Q and low frequency

operations.

Contour-Mode/Lamb-

Wave

𝑓0 ∝ 1

2𝑊√𝐸

𝜌

[10MHz – 10GHz]

Suitable for high frequency operations.

Multiple devices on a single chip can have

different frequencies.

Thickness Extensional

𝑓0 ∝ 1

2𝑇√𝐸

𝜌

[500MHz – 20GHz]

Used in Duplexers.

Shear Mode

𝑓0 ∝ 1

2𝑇√𝐺

𝜌

[800MHz – 2GHz]

Have a high stiffness and can operate at a

high frequency.

Table 1: Shows a comparison between different modes of vibration in AlN resonators.

By using the 𝑑31 piezoelectric coefficient and applying an AC electric field in the direction of

thickness, in-plane displacement or lateral vibration can be excited in the MEMS structure (Figure 4).

Such lateral-extensional mode of vibration is employed for the piezoelectric Contour-mode AlN NPRs

presented in this work.

15

Figure 4: Schematic representation of the dihexagonal structure of AlN. The fundamental X(1), Y(2) and

Z(3) directions are indicated. As shown, the anisotropic nature of the film permits the excitation of contour

mode shapes through the d31 coefficient.

A conventional AlN NPR is composed of an AlN film sandwiched between two metal

electrodes (Figure 5). When an AC voltage is applied to the interdigital electrode a contour-extensional

mode of vibration is excited through the equivalent 𝑑31 piezoelectric coefficient of AlN [6].

Figure 5: Schematic representation of a conventional AlN Nano Plate Resonator. The inset shows a FEM

Simulation of the device mode of vibration.

16

Given the equivalent mass density, ρeq, and Young’s modulus, Eeq

, of the material stack

(AlN and electrodes) that forms the resonator, the center frequency, f0, of this laterally vibrating

mechanical structure, is univocally set by the pitch, W0, of the metal electrode patterned on the

AlN nano plate. The resonance frequency of the device can be expressed as –

𝑓0 = 1

2𝑊0√𝐸𝑒𝑞

𝜌𝑒𝑞

Several of these unitary cells of width, W0 (known as fingers), are arrayed together and

excited in an alternating fashion (two adjacent fingers are excited 180° out of phase with respect

to each other) so as to form an equivalent symmetric lamb wave [12] in the AlN nano plate (Figure

6).

Figure 6: Schematic representation of a three-finger AlN Nano Plate Resonator

17

The other two geometrical dimensions, thickness, T, and length, L, set the equivalent

electrical impedance of the resonator and can be designed independently of the desired resonance

frequency. The number of fingers, n, their length, L, (also known as aperture of the transducer)

and the film thickness, T, are used to set the equivalent resonator electrical capacitance, C0, and its

motional resistance, Rm –

𝑅𝑚 ∝ 𝑇

𝑛𝐿

𝐶0 ∝ 𝑛𝐿𝑊0𝑇

For defining a resonator in terms of its equivalent circuit parameters, a Butterworth-Van

Dyke (BVD) Equivalent Model is used. It is a common lumped element circuit model to simplify

the transcendental functions that completely characterize the resonator. As shown in figure 5, it is

divided into two parts, where the right branch, called the static branch contains capacitances

representing the resonator capacitance and external connection capacitances, and the left branch,

called the motional branch represents the acoustic resonances in AlN and its load. These two

branches of the BVD model interact with each other via piezoelectric transduction. Also, at MEMS

scale (given the reduced size of the device), the external elements that provide for physical support

(i.e. the silicon) and routing of the electrodes need to be taken into account via a parasitic series

Rs, and a parallel resistance R0.

18

Figure 7: Modified Butterworth Van Dyke (BVD) Model of an AlN Resonator

Qualitatively, the R-L-C branch determines the “series” resonance, where the impedance

drops sharply to a minimum value of R at a frequency where the series inductance and capacitance

cancel each other out. At some higher frequency, the loop reactance hits zero and causes a

“parallel” resonance where most of the current will travel around the loop instead of past it. The

only thing preventing the series and parallel resonance impedances from going to zero and infinity,

respectively, is the motional resistance RM.

19

3.3 IMPORTANT PARAMETERS OF AN AlN

NANO-PLATE RESONANT THERMAL

DETECTOR

A thermal sensor is essentially a temperature sensor or a thermometer that has been

characterized to result in maximum temperature change upon exposure to a heat source. An ideal

thermal sensor is schematically illustrated in figure 8. A detector element of thermal resistance H

(J/K) is coupled to a heat sink at a constant temperature T0 (K) by a thermal conductance G (W/K)

[9].

Figure 8: Illustration of a Thermal Sensor

20

Upon absorption of a power Q (W) by the detector element, its temperature T can be

calculated from the equation:

𝑄 = 𝐻 (𝑑(𝑇 − 𝑇0)

𝑑𝑡) + 𝐺(𝑇 − 𝑇0)

Where t (sec) is the time. For a sinusoidal power input, 𝑄 = 𝑄0𝑒𝑖𝜔𝑡, the above equation can be

solved to yield:

𝛥𝑇 = 𝑇 − 𝑇0 = 𝑄0𝑒

𝑖𝜔𝑡

√𝐺2 +𝜔2𝐻2

For a thermal detector to exhibit high sensitivity, 𝛥𝑇 must be adequately large to ensure

that the heat lost to the surroundings is nominal [9], which, according to the above equation, can

be achieved by making G as small as possible and 𝜔 sufficiently low such that 𝐺/𝜔𝐻 ≫ 1. In

other words, both the thermal heat capacity of the detector element and its thermal coupling to the

surroundings should be as small as possible [9].

A major parameter that should be considered for the design and optimization of the

sensitivity of a micro-calorimetric thermal sensor is the thermal coupling between the heat source

and the thermal detector (in this case, the AlN-NPR). For ensuring an efficient thermal coupling,

the thermal resistance between the heat source and the detector should be as small as possible,

21

since the heat flow takes the path of lowest thermal resistance. In other words, the thermal

conductance between the source and the detector should be as high as possible.

For a thermal sensor to exhibit high values of sensitivity, it should not only have effective

thermal coupling, it should also have an efficient thermal detection capability of the sensor

element. In AlN Resonators, it is defined by the Temperature Coefficient of Frequency (TCF) [6].

It is also a measure of their thermal stability. It is generally expressed in ppm/K and is given by–

𝑇𝐶𝐹 = 1

𝑓

𝜕𝑓

𝜕𝑇= −

1

𝑎

𝜕𝑎

𝜕𝑇+

1

2

1

𝐸𝑃

𝜕𝐸𝑃

𝜕𝑇−

1

2

1

𝜌

𝜕𝜌

𝜕𝑇

Where a is the fundamental geometrical parameter that sets the center frequency and T

denotes temperature. In general, for contour-extension mode resonators, this equation can be

written as –

𝑇𝐶𝐹 = −𝛼1 + 1

2

𝜕𝑙𝑛𝐸𝑃𝜕𝑇

− 1

2(2𝛼1 + 𝛼3)

Where 𝛼1and 𝛼3are the linear coefficients of thermal expansion for AlN in the 1 (in the

plane of the film) and 3 (out of plane) directions, respectively; 𝜕𝑙𝑛𝐸𝑃/𝜕𝑇 is a coefficient that

describes the temperature variation of the in-plane modulus of elasticity [3]. For AlN, the largest

contribution to the TCF comes from the equivalent in-plane modulus of elasticity, whereas the

22

contribution of 𝛼1and 𝛼3 is less as compared to the young’s modulus [6]. If temperature stability

of center frequency is desired, lowering the TCF should be the main goal. But, for thermal

detection applications, the primary mode of detection is the change in center frequency, since

frequency is a quantity that can be monitored with the highest level of accuracy. For this purpose,

TCF should be sufficiently large to detect temperature variations.

23

3.4 INITIAL DESIGN OF THE THERMAL

DETECTOR

Taking into account the excellent thermal detection capabilities of an Aluminium Nitride

Nano Plate Resonator as well as a high quality factor, the design of a thermal detector has to allow

for temperature variation experiments in close proximity to the resonator to maintain efficient

thermal coupling. Keeping in mind the important characteristics and parameters of such a sensor,

a prototype thermal detector was conceptualized, as shown in figure 9.

Figure 9: Prototype of a Thermal Detector, with the AlN-NPR and Heat Source separated by an Air Gap.

24

Finite Element Method Simulations

The most common numerical method used for finding approximate solutions to boundary

value problems for differential equations is the Finite element method (FEM). It is a means of

predicting (and optimizing) the behavior of various complex objects or systems that are often

connected - without having to rely on physically existing models, prototypes or measurements.

The FEM is a stiffness based method in which the entire problem domain is divided into

subdomains called elements. It involves numerically dividing the system being analyzed into a

large number of small (finite) volumes, calculating the physical states (stresses, field strengths,

temperatures, etc.) of each individual cell and using an iterative process to approximate the

neighboring cells until a physically practical solution is obtained for the overall system. A variety

of specializations such as aeronautical, biomechanical, and automotive industries commonly use

integrated FEM in design and development of their products. Several modern FEM packages

include specific components such as thermal, electromagnetic, fluid, and structural working

environments.

As a proof of concept, a 3D finite element method (FEM) simulation was performed using

CMOSOL Multiphysics to investigate the temperature variation in a simplified sensor prototype

(without electrodes). The model chosen was heat transfer in solids. COMSOL provides a wide

range of simulation options for controlling the complexity of both modeling and analysis for the

system. The purpose of the simulation was to ensure that there was an effective heat transfer

between the heat source and AlN layer through a micro air gap of 0.2 m. The results of the

simulation are shown in figures 10 and 11. An efficiency of 97.635% was obtained for the micro

air gap, indicating its possible development into an effective thermal detector.

25

Figure 10: Temporal profile of a Thermal Detector. Inset shows the cross-section of the structure with a

0.2 m air gap.

Figure 11: Evolution of temperature with time for different layers of a Thermal Detector, with an air gap

of 0.2 m.

26

4. FABRICATION AND ASSEMBLY: AlN-

NPR THERMAL DETECTOR

In order to properly design the device and optimize its performance, an equivalent thermal

circuit shown in Figure 12 was considered. The power coming from a heat source at the top surface

is dissipated into device increasing both the top surface temperature, TS, and the resonator

temperature TR. This dissipation is through RRC1 (thermal resistance between the heat source and

the heat sink through the length of the top surface, which is the source of heat), and the series

combination of RRC2 (thermal resistance associated with the thickness of the top surface), Rair

(thermal resistance between the heat source and the resonator through the air gap), and RR (thermal

resistance associated with the length of the resonator). To achieve optimal device performance, it

is necessary to have both the source and the detector at almost equivalent temperatures, hence the

thermal resistance of the resonator has to be greater than the combined thermal resistance

associated with the air gap and the top surface thickness [3]. This translates in reducing the

thickness of the top surface (to reduce RS2), the air gap (to reduce Rair) and the thickness of the

AlN resonant plate (to increase RR). Another important factor to consider is that the vertical scaling

of the AlN plate causes an increase of the equivalent thermal resistance of the device, Rth, (hence

the overall sensitivity) and a reduction of its thermal capacitance, Cth, maintaining its thermal time

27

constant, , unchanged ( = Rth.Cth). In any case, lower values of thermal time constant can be

achieved by scaling the overall volume of the device (vertical and lateral dimensions). By reducing

the thickness of the AlN plate (i.e. implementing a nano-plate), the lateral dimensions of the device

can be scaled maintaining high transduction efficiency [17].

Figure 12: Equivalent Thermal Circuit of the micro-calorimetric AlN-NPR thermal detector.

28

The first step in the design of the AlN-NPR thermal detector was the Resonator itself.

According to what is described in chapter 2.3, a prototype of AlN-NPR with enhanced thermal

detection capabilities was designed and fabricated. A three dimensional schematic representation

of such a prototype of AlN-NPR, used as a reference for its fabrication, is shown in figure 13.

Figure 13: 3D schematic representation of the prototype of AlN-NPR.

In this prototype device, a lateral field excitation with floating top electrode (LFE-F) is

employed to excite a higher order contour-extensional mode of vibration in the AlN nano-

structures.

The LFE-F involves depositing the 500 nm AlN film (forming the resonant nano plate) on

top of an interdigital bottom electrode (100 nm) employed to excite the higher order lateral-

29

extensional mode of vibration. The electrically floating top electrode is instead used to confine the

excitation electric field across the thickness of the piezoelectric layer. It is worth noting that

without the electrically conductive top electrode the excitation electric field would not be

effectively confined across the thickness, T, of the device, hence the electromechanical coupling

coefficient, kt

2, of the nanomechanical structure would be approaching ~0 [10] (Figure 14) and it

would not be possible to excite the high frequency contour-extensional mode of vibration in such

ultra-thin (500 nm) AlN nano plate.

Figure 14: A schematic representation of Electric field in AlN Nano Plate.

The effective device area of this first prototype of AlN-NPR was designed to be 75 μm (W)

× 200 μm (L), the pitch, W0, of bottom Platinum (Pt) finger electrode was set to be 20 μm and the

thickness of AlN - nano plate, the top Au and bottom Pt electrode are 500 nm, 100 nm and 100 nm

30

respectively, resulting in a high order contour-extensional mode resonator working at a high

resonance frequency of approximately 135 MHz.

A 2D finite element method (FEM) simulation was performed using COMSOL

Multiphysics to investigate vibration mode, operation frequency and expected sensitivity for the

AlN Nano Plate Resonator. The model chosen was Piezoelectric Devices. Given to the designed

dimensions, the resonant frequency was found to be 133 MHz for AlN-NPR (Figure 15). And the

vibration mode of AlN-NPR was confirmed as contour-extensional mode (Figure 16).

Figure 15: Admittance plot from a 2D finite element method (FEM) simulation of the AlN-NPR.

31

Figure 16: Vibration mode from 2D finite element method (FEM) simulation of AlN-NPR shows in-plane

compression and extension.

32

Figure 17 shows the schematic illustration of the cross section of process flow for the

fabrication of AlN-NPR. As depicted, a 5-mask fabrication technique was used. A high resistivity

(>104

Ω·cm) Silicon (Si) wafer was used as substrate.

Figure 17: Microfabrication process: (a) Sputter deposition and lift-off of Pt bottom electrode; (b)

Sputter deposition of AlN, wet etch to open vias and dry etch to define device lateral dimensions; (c)

Sputter deposition and lift-off of top Au probing pads; (d) sputter deposition and liftoff of top Au

electrode; (e) Device release using XeF2 dry etch.

33

A 100 nm thick Platinum (Pt) film was sputter-deposited and patterned by lift-off on top

of the Si substrate to define the bottom interdigital electrode. Then, the 500 nm AlN film (stress

60 MPa and FWHM 2.2O) was sputter-deposited and then etched by Inductively Coupled Plasma

(ICP) etching in Cl2 based chemistry using photoresist as a mask to define the in-plane dimensions

of the resonant nano plate. Vias to access the bottom electrode were etched by H3PO

4. Optical

lithography was performed for the definition of both the electrode contact pads and the alignment

marks for the subsequent electron-beam lithography step. Then, a 100 nm thick gold (Au) film was

sputter-deposited and patterned by lift-off to form the probing pads. The MEMS die was then

sliced into multiple chips for further miniaturization and accessibility for the subsequent

measurement assembly. In the end, the device was released from the silicon substrate by isotropic

dry etching in XeF2. The fabricated prototype of AlN-NPR is shown in an optical microscope

image below (Figure 18).

Figure 18: An optical microscope image of an AlN-NPR.

34

The fabricated AlN-NPR was tested at room temperature and atmospheric pressure in a RF

probe station and its electrical response was measured by an Agilent E5071C network analyzer

after performing a short–open–load calibration on a reference substrate. The electromechanical

performance of the device was extracted by Butterworth-Van Dyke (BVD) model fitting (Figure

19).

Figure 19: Measured admittance and BVD fitting of the fabricated AlN-NPR. The extracted value of the

device mechanical quality factor, Qm, does not include the losses in the series Resistance, Rs.

35

The Temperature Coefficient of Frequency (TCF) of the fabricated AlN-NPR was

measured and found to be −26.2 ppm/K (Figure 20). This value is comparable to what is typically

measured in the case of conventional AlN-based MEMS resonators [6], in which the TCF is

dominated by the temperature-dependent Young's modulus of AlN.

Figure 20: Temperature coefficient of frequency (TCF) measurement of the AlN-NPR.

36

The first step in the assembly of the thermal sensor was wire bonding the AlN-NPR to a

Printed Circuit Board (PCB). The MEMS chip was attached to a custom designed PCB, designed

using Altium Designer (as shown in Figure 21) and fabricated by Advanced Circuits, Inc. The size

of each component on the PCB and the traces were chosen to maximize performance and cost

effectiveness. Gerber and NC drill files were then generated and submitted for fabrication.

Figure 21: PCB designed using Altium Designer Tool. The two tracks on either sides of the chip connect

to an SMA connector soldered underneath the PCB. Ground and Signal Pads were designed for a larger

wire bonding area and better electrical performance with lower parasitic capacitances.

The resonator was then wire-bonded to the PCB using a K & S 4523 Wire Bonder, and

SMA connector mounted and soldered underneath the PCB using an X-Tronic 9000 series

soldering station.

37

The next step was creating a reaction chamber to facilitate biochemical reactions in close

proximity to the thermal detector. Materials chosen were 140 m thick borosilicate glass and

PDMS, both of which have a high chemical resistance, essential in this application. The PDMS

acts as a sidewall, providing depth to the reaction chamber. An Anatech SP-100 plasma system

was used to attach the PDMS to the glass coverslips. Oxygen plasma converts the hydrophobic

PDMS surface to hydrophilic, which makes it easier to adhere to the glass surface. A schematic

representation of the process is shown in Figure 22.

Figure 22: Reaction chamber comprising of PDMS bonded to Glass using an O2 plasma.

The final step in the process was the entire assembly of the Thermal Sensor, where the

reaction chamber was placed on top of the AlN-NPR - attached PCB. The resonator and the

chamber were separated by a micro-air gap using a stainless steel spacer (Figure 23). The electrical

response of the sensor when tested initially was very poor, which was due to the spacer and the

track connecting the signal pad to the SMA connector touching each other. An incision was made

38

on the spacer along the line of the track which led to a significant improvement in electrical

response. Figure 24 depicts the electromechanical response of the sensor fitted to a BVD model.

Figure 23: Picture of the fabricated sensor. The inset shows a cross-sectional view of the overall

structure.

Figure 24: Measured admittance and BVD fitting of the wire bonded AlN-NPR.

39

5. RESULTS:

5.1 TEMPERATURE SENSITIVITY

The temperature sensitivity of the resonant frequency of fabricated and assembled micro-

calorimetric sensor was characterized by sequentially placing in the reaction chamber 50 μL

samples of deionized water pre-heated at different temperatures and monitoring the induced

resonant frequency shift for each temperature. It was measured for different air-gaps – 50, 200 and

300 µm – made possible by using steel spacers of varying thicknesses. The air gaps were estimated

using a Finn Tools & Instruments micrometer wafer measuring equipment, by placing the needle

at the chip, the reaction chamber and the steel spacers, and measuring the difference between them.

The resonator was excited at a single frequency (134.6788 MHz), where the slope of admittance

curve versus frequency is maximum, and the temperature induced admittance variation was

monitored over time. Figure 25 depicts the various temperature responses for different Air Gaps,

with an expected linear increase in temperature sensitivity with falling air-gap.

40

Figure 25: Temperature Response of the micro-calorimetric sensor for different air gaps. (a), (c) and (e)

depict response of the sensor in terms of an admittance variation for different temperatures for different

air gaps. (b), (d) and (f) show the measured Temperature Sensitivities of the sensor in terms of kHz/0C,

which amount to 8.66 ppm/K, 8.02 ppm/K and 6.32 ppm/K for the air gaps of 50, 200 and 300 µm

respectively, clearly indicating a marked rise in sensitivity with the lowering of air gap.

41

5.2 FINITE ELEMENT METHOD (FEM)

SIMULATION

To verify and optimize the proposed design solutions, a 3-Dimensional Finite Element

Method (3D FEM) simulation using COMOL Multiphysics was performed (Figure 26). The

thermal conductivity of AlN was set to 80 W/m.K [11]. A fixed temperature of 20°C was set as

the boundary condition for the edges of the device. Heat transfer in solids module was used for

generating a temporal profile.

Figure26: 3D finite element method (FEM) simulated temperature profile of the micro-calorimetric

sensor. A 1mW thermal power was applied to the top glass plate in the simulation.

42

The graphs in Figure 27 compares the rise in temperature of the reaction chamber and that

of the resonator for different air gaps.

Figure 27: A comparison of Temperature Rise for the reaction chamber, the air gap and the AlN Nano-

Plate resonator for different air gaps when a 1 mW power is applied over the reaction chamber surface.

43

The effect of air gap dimensions on the device performance was studied in terms of heat transfer

efficiency, which is defined by the ratio between the temperature of AlN resonator TR and one of

the reaction chamber TS. Figure 28 shows that smaller air gaps guarantee significantly more

efficient heat transfer.

Figure 28: Simulated Heat Transfer Efficiency for different Air Gaps.

A comparison between the simulated and actual heat transfer efficiency is given in Table

2. The measured values of the efficiency confirm that effective heat transfer from the reaction

chamber to the thermal detector is achieved by minimizing the air gap between them.

44

Air Gap 50 µm 200 µm 300 µm

Simulated Efficiency 26.66% 17.8% 17.045%

Experimental Efficiency 33% 31.3% 24.15%

Table 2: Simulated and experimental values of heat transfer efficiency for different air gaps. The device

efficiency extracted by FEM simulation was found to be slightly lower than the experimental result. This

is attributed to the fact that only heat conduction was considered for the simulation (heat transfers via

radiation and convection were neglected).

45

5.3 ACID-BASE NEUTRALIZATION

REACTION

To initialize and demonstrate the capability of the thermal sensor as a micro-calorimetric

biosensor, the exothermic reactions of hydrochloric acid with ammonium hydroxide and sodium

hydroxide were chosen to be monitored. The neutralization reactions can be expressed as –

𝐻𝐶𝑙 + 𝑁𝐻4𝑂𝐻 𝐻= −51.5 𝐾𝐽/𝑚𝑜𝑙→ 𝑁𝐻4𝐶𝑙 + 𝐻2𝑂

And

𝐻𝐶𝑙 + 𝑁𝑎𝑂𝐻 𝐻= −57.1 𝐾𝐽/𝑚𝑜𝑙→ 𝑁𝑎𝐶𝑙 + 𝐻2𝑂

The enthalpy of the reaction for the chemical reactions are -51.5 and -57.1 KJ/mol,

respectively. The effectiveness of the fabricated micro-calorimetric sensor prototype for

monitoring chemical reactions was characterized by sequentially placing in the reaction chamber

different concentrations of Hydrochloric Acid and Ammonium Hydroxide for the first reaction

(Figure 29) and Hydrochloric Acid and Sodium Hydroxide for the second reaction (Figure 30) and

monitoring the resonator frequency shift induced by the heat generated by the exothermic reaction

at each concentration. The HCl, NH4OH and NaOH solutions were prepared by diluting stock

46

solutions from the manufacturer (Doe & Ingalls) with DI water in the range of 1 M to 5 M. Prior

to the test, the sensor was connected to a Network Analyzer and allowed to stabilize for 30 minutes.

The reaction chamber was aligned on top of the sensor, with 100 l of the first reactant placed in

it and allowed to stabilize for 5 minutes. A 100 l of the second reactant was thereafter added. The

resonator was excited at a single frequency (134.6788 MHz), where the slope of the admittance

curve versus frequency is maximum, and the reaction induced admittance variation was monitored

over time. As expected, saturation levels were reached when the concentration ratio between the

two reactants for both the reactions was 1:1, because maximum heat is generated at equal

concentrations, resulting in a maximum frequency shift.

47

Figure 29: Response of the AlN NPR to the reactions between NH4OH and HCl. (a) NH4OH with varying

concentrations (1M to 5M) was mixed with 3M HCl in the reaction chamber. (c) HCl with varying

concentrations (1M to 5M) was mixed with 3M NH4OH. (b) & (d) show the corresponding resonance

frequency shifts induced by the reaction for different concentations of the reactants.

48

Figure 30: Response of the AlN NPR to the reactions between NaOH and HCl. (a) NaOH with varying

concentrations (1M to 5M) was mixed with 3M HCl in the reaction chamber. (c) HCl with varying

concentrations (1M to 5M) was mixed with 3M NaOH. (b) & (d) show the corresponding resonance

frequency shifts induced by the reaction for different concentations of the reactants.

An important point here is that the frequency variations shown in figures 29 and 30 (b &

d), which were supposed to be constant beyond the 1:1 concentrations are not exactly constant but

do show some variations because of pipetting errors. This results in a slight inaccuracy in the

volume of the reactants dispensed over the reaction chamber. This issue can be solved by using a

more accurate chemical dispensing mechanism.

Concentration of a reactant in a given acid-base reaction can be determined based on the

linear region of curves in Figures 29 and 30 (b & d). But there are limitations to this approach.

This technique can only be used in cases where the reactant whose concentrations need to be

determined has a concentration that is lower than or equal to the other reactant whose concentration

is known.

49

5.4 ENZYMATIC HYDROLYSIS OF UREA

Urea is widely distributed in nature and its analysis is of considerable interest in clinical

chemistry, agro-food chemistry, and environmental monitoring. The handling of Urea by the

kidneys is a vital part of human metabolism. Many methods of urea determination are based on its

hydrolysis in the presence of the catalyst urease and successive measurement of ions consumed or

produced:

𝐶𝑂(𝑁𝐻2)2 + 2𝐻2𝑂 𝑈𝑟𝑒𝑎𝑠𝑒,−61 𝐾𝐽/𝑚𝑜𝑙→ 2𝑁𝐻4

+ + 𝐶𝑂32+

The enthalpy change of the reaction is -61 kJ/mol. The possibility of electrochemical

detection led to the development of a large number of urea biosensors based on conductometric

[18, 19], potentiometric [20-22] and Amperometric [23, 24] transducers. However, they suffer

from slow responses, vulnerability to the interference of other ions in sample solution and

relatively high detection limits. The micro-calorimetric NPR based biosensor presented in this

work could potentially lead to a better sensitivity and lower detection limits.

For the experiment, 0.1, 0.2 and 0.3 M solutions of urea were prepared in a phosphate

buffer saline (PBS, pH 7.0) solution. Since 1 unit of urease can hydrolyze 0.5 mol of urea,

250U/ml urease solution in PBS was prepared which has sufficient enzymes to react with urea for

all concentrations in the experiment. Initially, 200 l of 0.1 M urea solution was placed into the

50

reaction chamber. Then the reaction chamber was stabilized in air for 5 minutes following which

50 l of urease solution was added into the urea solution in the reaction chamber. The experiment

data for hydrolysis of urea are plotted in Figure 31 for 50, 200 and 300 m air gaps. The data

exhibit a linear dependence of the peak sensor output as a function of the concentration of urea.

Using the data in Figure 31, concentration of Urea in an unknown sample can be determined.

51

Figure 31: Response of the AlN-NPR to the catalytic hydrolysis of urea in the presence of urease. (a), (c)

and (e) depict response of the sensor in terms of an admittance variation for varying concentrations

(0.1 M to 0.3 M) of urea for different air gaps in the presence of urease in the reaction chamber. (b),

(d) and (f) show the corresponding resonance frequency shifts induced by the reaction for different

concentations of the reactants.

The slopes of Figure 31 - (b), (d) and (f) depict Concentration Sensitivities of the sensor in

terms of kHz/M for the air gaps of 50, 200 and 300 µm respectively, clearly indicating a marked

rise in sensitivity with the lowering of air gap.

Given the slope for different air gaps, concentration of urea in an unknown sample can be

determined by dividing the measured variation in frequency with the value of the slope of the

Frequency – concentration curve when the reaction is performed.

52

6. NOISE PERFORMANCE

6.1 PEAK TO PEAK NOISE

Given a temperature induced admittance variation, the peak to peak noise was calculated

and is shown in figure 32.

Figure 32: Peak to Peak noise is calculated for a given temperature induced admittance variation.

6.2 ROOT MEAN SQUARE (RMS) NOISE

The RMS noise is calculated using the following equation –

𝑁𝑅𝑀𝑆 = 𝑁𝑃−𝑃𝜎

=0.004

6.6= 0.00060606 𝑑𝐵

Where σ is the conversion ratio, where percentage of the time Noise exceeding the nominal

Peak-to-Peak value is the lowest. One of the important factors while considering the RMS noise

is Thermomechanical Noise in the sensor system.

53

6.3 NOISE SPECTRAL DENSITY

Noise Spectral Density describes how power of the noise signal is distributed over different

frequencies. It is calculated using the following equation –

𝑁𝑜𝑖𝑠𝑒 𝑆𝑝𝑒𝑐𝑡𝑟𝑎𝑙 𝐷𝑒𝑛𝑠𝑖𝑡𝑦 = 𝑁𝑅𝑀𝑆

√𝐵=0.0006

√50= 8.57 × 10−5 𝑑𝐵/√𝐻𝑧

Where B is the measurement Bandwidth.

6.4 DETECTION RESOLUTION

The temperature resolution of the micro-calorimetric sensor was calculated to be 994.5

µK/Hz1/2 in a 50 Hz measurement bandwidth.

The concentration resolution for the hydrolysis of urea was calculated for different air gaps

in a 200 Hz Bandwidth and is given in Table 3.

Air Gap 50 µm 200 µm 300 µm

Detection Resolution of Concentration

61.22 µM/√𝐻𝑧 209.049 µM/√𝐻𝑧 267.84 µM/√𝐻𝑧

Table 3: Lists the calculated Concentration Resolution of Urea for 50, 200 and 300 µm air gaps.

54

7. PROTOTYPE II – GLUCOSE SENSING

To monitor the effect of miniaturization on Temperature Coefficient of Frequency (TCF)

and temperature sensitivity of the AlN NPR thermal detector, a resonator with thinner Aluminum

Nitride layer (250 nm) was fabricated using the same 4 mask technique, with electrodes (Au and

Pt) of comparable thickness (100 nm and 50 nm respectively). The electromechanical performance

of the device extracted by Butterworth-Van Dyke (BVD) model fitting is given in figure 33.

Figure 33: Measured admittance and BVD fitting of the fabricated AlN-NPR II Prototype.

55

The thermal capability of the device measured through Temperature Coefficient of

Frequency (TCF) of the fabricated AlN-NPR II prototype was evaluated and found to be −51.35

ppm/K (Figure 34), which is an improvement over the previous prototype of the device. The higher

value of the TCF is because of comparable thicknesses of the electrodes (Au and Pt) and AlN

layer. As a result, the Young’s modulus of these electrodes factors into the value of TCF.

Figure 34: Temperature coefficient of frequency (TCF) measurement of the fabricated AlN-NPR II

Prototype.

56

The temperature sensitivity of the resonant frequency of the prototype II - fabricated and

assembled micro-calorimetric sensor was characterized by sequentially placing in the reaction

chamber 50 μL samples of deionized water pre-heated at different temperatures and monitoring

the induced resonant frequency shift for each temperature. It was measured for a 50 µm Air Gap.

The resonator was excited at a single frequency (116.840688 MHz), where the slope of

admittance curve versus frequency is maximum, and the temperature induced admittance variation

was monitored over time. Figure 35 (a) depicts the various temperature responses for an air gap of

50 µm. The high value of TCF results in a higher value of the temperature sensitivity of the device,

shown in Figure 35 (b).

Figure 35: Temperature Response of the micro-calorimetric sensor. (a) Depicts response of the sensor in

terms of an admittance variation for different temperatures. (b) Shows the measured Temperature

Sensitivity of the sensor in terms of kHz/0C, which amounts to 22.199 ppm/K for the air gap of 50 µm.

The increase in TCF and temperature sensitivity indicates an even higher efficiency over

the first prototype of the device, at 43.23%.

57

Glucose is a ubiquitous fuel source in biological systems. It is a simple sugar which is a

permanent and immediate primary source of energy in most organisms, from bacteria to humans.

The ability to monitor the concentration of glucose is of critical importance for sustained biological

operations. One method for quantitative determination of glucose is with the use of enzymatic

methods as outlined below (Figure 36). Glucose oxidase is known to oxidize glucose to gluconic

acid with the concomitant release of hydrogen peroxide.

Figure 36: Catalytic Oxidation of Glucose in the presence of Glucose oxidase.

The enthalpy change of the reaction is -80 kJ/mol. For the experiment, 0.1, 0.2 and 0.3 M

solutions of Glucose were prepared in a phosphate buffer saline (PBS, pH 7.0) solution. Since 1

unit of Glucose Oxidase can catalyze 1 mol of glucose solution at 25 0C, 260 U/ml Glucose

Oxidase solution in PBS was prepared which has sufficient enzymes to react with glucose for all

concentrations in the experiment. Initially, 200 l of 0.1 M Glucose solution was placed into the

reaction chamber. Then the reaction chamber was stabilized in air for 5 minutes following which

50 l of glucose oxidase solution was added into the glucose solution in the reaction chamber. The

experiment data for oxidation of glucose in the presence of oxygen are plotted in Figure 37 for a

50 m air gap.

58

Figure 37: Response of the AlN-NPR to the catalytic oxidation of glucose in the presence of glucose

oxidase (GOD). (a) depicts the response of the sensor in terms of an admittance variation for varying

concentrations (0.1 M to 0.3 M) of glucose for a 50 µm air gap in the presence of GOD in the reaction

chamber. (b) shows the corresponding resonance frequency shifts induced by the reaction for different

concentations of the reactants.

The slope of Figure 37 (b) depicts Concentration Sensitivities of the sensor in terms of

kHz/M for the air gap of 50 µm.

Given the value of the slope, concentration of glucose in an unknown sample can be

determined by dividing the measured variation in frequency with the value of the slope of the

Frequency – concentration curve.

The temperature resolution of the micro-calorimetric sensor and the concentration

resolution for the oxidation of glucose were calculated to be 534.355 µK/Hz1/2 and 535.803

µM/Hz1/2 respectively, in a 200 Hz measurement bandwidth.

59

8. CONCLUSIONS

8.1 SUMMARY

This thesis presents two high temperature resolution (994.5 µK/Hz1/2 in a 50 Hz

measurement bandwidth and 534.355 µK/Hz1/2 in a 200 Hz measurement bandwidth) micro-

calorimetric sensor prototypes based on two different high frequency (134.5 MHz, and 116.67

MHz) Aluminum Nitride (AlN) nano-plate resonators (NPR) overlapped by a freestanding reaction

chamber separated by a micro-scale air gap (~50 m). For the first time, the unique thermal

detection capabilities of the AlN NPR technology are exploited to devise calorimetric sensors with

superior performance. Efficient heat transfer from the reaction chamber to the thermal detector is

achieved by minimizing the air gap between them. By taking advantage of the large thermal

resistance (2.64 × 104 K/W) of the AlN NPR and the reduced air gap, high heat transfer efficiencies

(ratio between the temperature of the resonator and the one of the reaction chamber) of 33% for

Prototype I and 43.23% for Prototype II were achieved. Using a finite element method (FEM)

simulation, a remarkable agreement between the simulated and experimentally measured temporal

evolution profile of the sensor was obtained. The effectiveness of the fabricated prototype is

verified by monitoring exothermic reactions between Hydrochloric Acid and Ammonium

Hydroxide, and between Hydrochloric Acid and Sodium Hydroxide. Prototype I was used as a

micro-calorimetric biosensor for the hydrolysis of urea in presence of urease, and Prototype II was

used for the oxidation of Glucose in the presence of Glucose Oxidase. From the signal to noise

ratio analysis of the urea and glucose sensors, < 61.22 µM urea sensitivity and < 535.803 µM

glucose sensitivity could be obtained, respectively.

60

Table 4 shows the comparison between the performance parameters of the fabricated

micro-calorimetric sensor Prototypes and Y-cut Quartz resonant sensor technology. The sensor

technology described in this thesis is superior in terms of sensitivity and heat transfer efficiency,

two very important parameters for characterizing a sensor for biochemical sensing applications.

AlN-NPR micro-

Calorimetric Biosensor I

Y-cut Quartz Resonator based

biosensor

AlN-NPR micro-Calorimetric Biosensor II

Temperature Sensitivity of the

resonator technology

4.035 kHz/0C 7.32 kHz/0C 5.991 kHz/0C

Temperature Sensitivity of the

sensor 1.165 kHz/0C 1.942 kHz/0C 2.59 kHz/0C

Air Gap 50 µm 200 µm 50 µm

Heat Transfer Efficiency

33% 26.5% 43.23%

Urea Sensitivity 9.8415 kHz/M 5.75 kHz/M

Table 4a: A comparison between performance parameters of sensor technologies.

The reduced mass and volume, the increased frequency of operation, the high temperature

sensitivity, the high heat transfer efficiency, very low detection resolution and superior noise

performance all demonstrate the great potential of the proposed technology for the implementation

of a new class of micro-calorimetric biosensors capable of achieving unprecedented detection

capabilities.

61

8.2 FUTURE WORK

The research work presented in this thesis has set a pathway for the development of a new class

of ultra-sensitive and low noise AlN micro-calorimetric biosensors. The current work presented in this

thesis achieves a high heat transfer efficiency, but even higher efficiency values can be obtained by

further scaling the air gap in 100 s of nm. Figure 37 presents the efficiency curve for the values of air

gap used in this thesis and the future direction of this work. Also, higher values of temperature

sensitivity can be obtained by further scaling the thickness of AlN layer to 10 s of nm.

Figure 37: Heat Transfer Efficiency for different Air Gaps.

62

Such low air gaps can be obtained by system-level implementations of chip-scale sensing

platforms using encapsulation to fabricate the reaction chamber directly on top of the resonator, as

shown in figure 38.

Figure 38: 8 mask fabrication process for encapsulating and constructing a device-level micro-calorimetric

sensor : (a) deposition of bottom Pt electrode, thin AlN layer and top gold electrode; (b) dry etching of

AlN; (c) deposition and patterning of polysilicon sacrificial layer; (d) deposition and patterning of SiO2

capping layer; (e) release holes etching in SiO2; (f ) XeF2 dry etch of sacrificial layer and release of AlN

resonator; (g) deposition and patterning of SiO2 to refill and seal the released holes.

63

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