臺灣博碩士論文加值系統

本論文使用鈀(Palladium, Pd)修飾於閘極之矽奈米帶(silicon nanobelt, SNB)場效型電阻(field-effect resistor, FER)，進行低濃度(1~100 ppm)氫氣感測，並使用類比電路進行訊號過濾與放大以增進訊雜比(signal-to-noise ratio, SNR)，並整合後端演算法快速準確地辨識濃度以達到穿戴式氣體感測應用標準。
在元件設計方面，研究選用鈀為氣體感測材料並沉積為元件的閘極，其功函數約為5.22~5.68 eV，此數值會隨氫氣濃度變化而改變，當氫氣吸附並擴散進入鈀奈米顆粒形成功函數較低(4.7~4.8 eV)之氫化鈀 (PdHx)時，n-型場效型電阻通道之空乏層寬度(depletion width, Wdep)隨著功函數下降而變薄，造成通道電流增加。本研究基於上述功函數模型進行元件摻雜參數最佳化之設計，增加響應與提高系統訊雜比。
由於感測低濃度目標氣體，鈀奈米顆粒結構必須足夠微小(< 3~5 nm)才能產生明顯的功函數變化，且元件表面鈀覆蓋率必須足夠高(> 40%)才能有效調控通道阻值變化。因此本研究控制原子層化學氣象沉積(atomic layer chemical vapor deposition, ALD)的循環數(Cycle)來達到以上需求。為實現焦耳熱(Joule heating, JH)選擇性沉積，施體摻雜濃度由源極、感測通道到汲極的分布分別為高、低及高摻雜(n+ / n- / n+)。因此元件在施加電壓後，偏壓會集中於通道n-區域使元件局部溫度上升，讓n-閘極區域沉積速率快於其他部位，實現選擇性沉積。在元件電性方面，由於摻雜濃度不均，在擬合JH溫度時，容易因汲極引發能障下降(drain-induced barrier lowering, DIBL)造成預估偏差，因此本論文也提出特殊的擬合方式克服此誤差。另外，單晶矽元件在高電場會出現離子衝擊(impact ionization)，造成汲極端溫度不易受控制且破壞通道晶格結構，因此本文討論施加交流電(alternating current, AC)的元件特性，以減低直流(direct current, DC)電場所造成之負面影響。此外，元件再進行感測時會使用聚二甲基矽氧烷(Polydimethylsiloxane, PDMS)製作之腔體覆蓋以避免環境汙染並同時加速氣體反應進行及節省氣體樣本用量。
在電路系統方面，為實現穿戴式裝置，本文使用微控制器(microprocesser, MPU) Arduino®製作類比電路嵌入式系統，系統架構包含惠斯通電橋(Wheatstone Bridge)、脈衝寬度調變(pulse width modulation, PWM)、整流器(rectifier)、儀表放大器(instrumental amplifier, IA)以及高階數主動式低通濾波器(high-order active low-pass filter, HOALPF)。差動感測訊號經由儀表放大器放大輸入訊號以符合MPU電壓讀取精度，並以高共模拒斥比(common-mode rejection ratio, CMRR)的放大特性以及濾波器消除系統雜訊提高訊雜比實現高精度穿戴式裝置讀取系統，透過印刷電路板(PCB)布局製作出公分級嵌入式電路系統。
在後端演算法方面，本研究提出計算感測訊號斜率，來鑑別不同目標氣體濃度；感測訊號經過濾波放大後以最小平方法進行線性回歸計算區間斜率(回歸區間約30秒)，並記錄區間最大值按照鈀-氫滲透理論換算成對應濃度，並將濃度資料經藍芽協定傳至智慧型手機APP顯示，完成穿戴式無線傳輸系統架構。斜率鑑別法可有效克服傳統電流對照法無法消除之基線飄移(Baseline Drift)以及晶格膨脹造成之電流飄移等，消除量測誤差的不利因素以提高感測準確度，同時大幅縮短感測時間並減少所需氣體樣本數量。
本研究整合奈米感測器、電路系統和演算法完成可攜式氣體感測系統，並實現1~100 ppm氫氣感測，奠定人體呼氣檢測小腸菌叢增生(Small Intestinal Bacteria Overgrowth, SIBO)的基礎。本非侵入式(non-invasive)系統實現定點照護(point of care)和物聯網(Internet of Things, IoT)等應用，並可透過陣列式多材料結構結合機器學習進行多樣本之複雜檢測，滿足未來智慧醫療的需求。

In this research, a silicon nanobelt (SNB) device based field-effect resistor (FER) with palladium (Pd) decorated gate is utilized to detect low concentration (1~100 ppm) hydrogen. To realize portable device sensing, an analog readout circuit is fabricated for both signal and signal-to-noise ratio amplification, and an algorithm is established to identify different target concentrations efficiently and precisely.
Regarding device design, the original work function of Pd (5.22~5.68 eV) can be modulated by different hydrogen concentrations, as hydrogen molecules are adsorbed and diffused into Pd nanoparticles, Pd is transformed into palladium hydride (PdHx), which have a lower work function (4.7~4.8 eV). The energy band bending of n- channel’s depletion width (Wdep) is decreased by lowering work function during hydrogen sensing and causes the resistance variation of the FER. Based on the Wdep model mentioned above, dopant density of n- channel is optimized to enhance the response and increase the signal-to-noise ratio (SNR) of the sensing device.
To form a high-coverage (> 40%) Pd nanoparticle thin (< 3~5 nm) film without aggregation for highly hydrogen sensitive in low target concentration ambient, atomic layer deposition (ALD) process is utilized and the amount of cycles in ALD recipe has been optimized. Comparative dopant nano-belt channel, which has high, low, and high (n+ / n- / n+) donor dopant density distribution from source, sensing channel, to drain, is designed for selective Joule heating (JH) deposition since the voltage bias concentrates on the high resistive n- channel and induces higher temperature which increases the growth rate of ALD. In consideration of the electrical characteristics of the device, a thermal fitting method for precise JH temperature estimation is established to compensate the temperature deviation caused by drain-induced barrier lowering (DIBL). Furthermore, the frequency response of polysilicon and single-crystal silicon device with different n- channel length under high-frequency alternating current (AC) is discussed because AC electrical field can reduce disadvantages under direct current (DC) like impact ionization, which might cause dramatic incontrollable increase of temperature and destruction of Pd lattice structure. Besides, a Polydimethylsiloxane (PDMS) chamber is covered on sensing chip to separate the device from ambient pollution, accelerate the hydrogen reaction with Pd, and reduce the requirement of the target gas.
Concerning the embedded circuit system, an Arduino® microprocessor (MPU) is embedded into the analog circuit to realize a prototype of a portable device. System structure includes Wheatstone bridge, pulse width modulation (PWM), rectifier, instrumental amplifier (IA), and a high-order active low-pass filter (HOALPF). The noise of the differential input signal is eliminated by a high common-mode rejection ratio (CMRR) of IA and amplified to suit the voltage precision of MPU, and the output noise from device sensing is eliminated by HOALPF.
Last but not least, the algorithm to determine different target concentrations is based on the slope of the sensing response which is sampled under the 10 Hz sample rate, and the response slope is linearly regressed after a while (~30 seconds) by the least-square method. The local maximum of the slope is transformed into concentration (ppm) by Pd-H permeation theory and the result is transported to APP on the smartphone by Bluetooth protocol. The model based on the slope response overcomes the disadvantages of traditional response current like baseline drift and saturation current variation caused by lattice expansion, and substantially reduces sensing time and requirement of the target amount.
In summary, this thesis integrates nano-sensor, circuitry, and algorithm for realizing a portable gas-sensing system that can define hydrogen concentration between 1 to 100 ppm. The integrated gas sensing system establishes the foundation of Small Intestinal Bacteria Overgrowth (SIBO) diagnosis by human breathe analysis. This non-invasive system corresponds to the smart medical tendency for the future and the idea of wireless communication protocol, internet of things (IoT), machine learning (ML) and the sensor array with multiple materials can realize complex multiple-gas sensing for non-invasive point-of-care test (POCT) diagnosis of diseases.

摘要 i
Abstract iii
Acknowledgements v
Contents vi
List of Figures ix
List of Tables xvii
Chapter 1 Introduction 1
1.1 Research background 1
1.2 Small intestine bacterial overgrowth (SIBO) 3
1.3 Gas sensing types and mechanisms 6
1.3.1 Hydrogen sensing and analysis techniques 6
1.3.2 MOS-based nanodevice characteristics 9
1.3.3 Characteristics of palladium nanoparticle 11
1.4 Research motivation and goal 11
Chapter 2 Device Fabrication and Characteristics 13
2.1 Device fabrication flow and structure 13
2.2 Sensing layer characteristics and deposition 16
2.2.1 Palladium phase diagram 16
2.2.2 Work function variation and dipole generation 17
2.2.3 Atomic layer deposition (ALD) 18
2.3 Target gas and sensing mechanisms 20
2.3.1 Hydrogen molecule characteristics and adhesion 20
2.3.2 Debye length, depletion width, and response estimation 21
2.4 Energy band structure and device characteristics 26
2.4.1 Energy band diagram of n+/n-/n+ double junction device 26
2.4.2 Energy band diagrams at various drain voltages 27
2.5 Joule-heating in nano-belt device 29
2.5.1 Temperature to power simulation 30
2.5.2 Temperature to power fitting and estimation 31
Chapter 3 System Architecture 36
3.1 Analog readout circuit 36
3.1.1 Wheatstone bridge 36
3.1.2 Pulse width modulation 37
3.1.3 Low-pass filter and rectifier 38
3.1.4 Instrumentation amplifier 43
3.1.5 Embedded system design 46
3.2 Determination algorithm 52
3.2.1 Linear regression 52
3.2.2 Regression period 54
Chapter 4 Results and Discussion 56
4.1 The sensing mechanisms vs. current responses 56
4.1.1 The physical mechanisms of slope and current response 57
4.1.2 Determination of gas concentration 60
4.1.3 Temperature effect 63
4.1.4 Pd lattice extraction vs. sensing baseline drift 65
4.1.5 Current vs. slope response 68
4.2 System demonstration and PCB layout 69
4.3 Limit of detection 74
Chapter 5 Conclusions and Future Works 76
5.1 Conclusion 76
5.2 Future work 77
5.2.1 Device operation and dopant optimization 77
5.2.2 Circuit and algorithm optimization 77
5.2.3 Medical application 78
5.2.4 Electronic nose 79
Appendix Ⅰ. High-Frequency Response 80
Appendix Ⅱ. Sensing Chamber Design 85
A.2.1 Chamber design and simulation 85
A.2.2 Chamber Fabrication 89
References 92

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