臺灣博碩士論文加值系統

生物晶片的檢測時間和檢測極限對其實際應用至關重要．檢測時間是生物晶片能夠從待測物中分辨出目標生物分子的最短時間；而檢測極限是能夠從待測物中測量出生物分子的最低濃度．為了增加生物晶片的效率，我們必須研究影響檢測時間以及檢測極限的機制．因此，我們在交通大學進行理論分析以及數值模擬．並進一步在筑波大學醫學院進行初步實驗．
電子生物感測器涵蓋了電解質樣本中的流體力學、生物感測元件中的半導體物理以及元件表面的生物化學反應．因此，我們自行開發了多物理數值模擬器，其包含流體力學、飄移擴散模型、布朗運動以及蒙地卡羅法，以模擬完整的生物晶片系統．
在飄移擴散模型的元件特性模擬中，模擬結果顯示奈米線的結構對於其靈敏度提升非常關鍵．我們發現將奈米線埋入平面氧化層中比起用薄氧化層包覆奈米線，其靈敏度可以提升高達兩倍之多．此外，我們也發現因為雙電層造成的電場屏蔽效應，導致奈米線的靈敏度下降的現象．
在蒙地卡羅法和流體力學的模擬中, 我們證明了ACEO可以促進流體循環，並有效的移除被空乏的流體層．被捕獲的生物分子在生物晶片表面上的清楚圖形顯示出ACEO可以用有效地控制生物分子分布．模擬結果表示，此方法可以提升生物分子的捕獲效率4.4倍以及檢測速度24.8倍.
另外，我們定義了暫態檢測極限並且提出新的生物晶片控制方法．不同以往假設熱平衡的靜態檢測極限，暫態檢測極限更加貼近實際應用的情況．基於暫態檢測極限的假設，我們使用蒙地卡羅法證明提出的控制方可大幅降低生物晶片的檢測極限、檢測時間以及免除背景雜訊的困擾．

Critically important for potentiometric biosensing is to reduce detection time and Limit of Detection (LoD). The detection time is the shortest time required for a biosensor to detect target biomolecules in a electrolyte specimen. The LoD is the lowest concentration of target biomolecules, which is necessary for the biosensor to reliably judge if there are the target biomolecules in the electrolyte specimen, with a stated guarantee. Accordingly, in order to improve the characteristics of potentiometric biosensors, we should investigate the mechanisms what prolongs or shorten the detection time and what increases or decreases the LoD. For this purpose, we have performed theoretical and numerical researches in National Chia Tung University. Furthermore, we have performed a preliminary experiment in the Faculty of Medicine at University of Tsukuba under the academic exchange program.
The potentiometric biosensing is a composite technology of the fluid dynamics inside electrolyte specimen, the semiconductor technologies inside semiconductor parts, and biochemistry for biomedical reactions occurring between the electrolyte specimen and the semiconductor parts. Therefore, we have developed a device simulator of potentiometric biosensor, which comprises Poisson’s equation covering the entire space of the biosensor to obtain the potential profile, the fluidic dynamic modeling in electrolyte specimen, and the drift-diffusion model in semiconductor parts by assuming the interface condition which may reflect the biochemical reaction between the semiconductor parts and the electrolyte specimen within a predetermined approximation. The fluid-dynamic equations and the drift diffusion model are combined going through the Poisson equation. We have adopted an exemplary simulation sample of potentiometric biosensor which comprises an array of silicon nanowires covered by an oxide film which faces to electrolyte specimen under AC electroosmosis (ACEO). Specific biochemical reactions may occur at the surface of this oxide film between the electrolyte specimen and the nanowires. The receptors immobilized on the oxide surface may capture target biomolecules floating fluid-dynamically in the electrolyte specimen as a result of biochemical reactions. If those captured biomolecules have sufficient charge, they can change the transconductance of nanowires. The biosensor may sense this electronic change.
As a result of Monte-Carlo simulation, we have found that the electronic sensitivity of the nanowires can be more improved when the oxide film has a planar surface. It is further shown that a depleted fluid layer obstructs receptors to capture target biomolecules on the oxide surface and ACEO can exclude the depleted fluid layer from the oxide surface by circulating the electrolyte specimen. The distribution pattern of captured biomolecules on the oxide surface clearly reveals that ACEO is of practical use in collecting target biomolecules in an effective area for biosensing. This technique improves the capture efficiency by 4.4-times and then the detection speed by 24.8-times.
In addition, we have successfully defined the transient LoD and found that the detection time should be redefined by using the transient LoD, while the conventional LoD was defined at equilibrium state. By using this new concept of LoD, we have successfully proposed a controlling method to characterize a nanowire array biosensor with Monte-Carlo simulation. This controlling method is also necessary to improve the transient LoD beyond the common drain method.

摘 要 i
摘 要 i
Abstract ii
Preface iv
List of Publication v
Contents vi
List of Figures vii
List of Tables ix
1. Introduction 1
1.1. Theory and Operation Mechanism of Potentiometric Biosensor 2
1.2. Specific Binding Reactions 4
1.3. Challenges of Potentiometric Biosensor 7
1.3.1. Diffusion Limit 8
1.3.2. Limit of Detection 10
1.3.3. Screening Effect 11
1.4. Outline of this thesis 15
2. Simulation Method 17
2.1. Drift-Diffusion Model 21
2.2. Fluid Dynamic in Microfluidic 22
2.3. AC Electroosmosis 23
2.4. Monte-Carlo Simulation of Brownian Motion 25
3. Demonstration-1: Scaling effect on Sensitivity of SiNWFET 26
4. Demonstration-2: Monte Carlo Simulation of Nanowires Array Biosensor with AC Electroosmosis 29
4.1 Nanowire Array Biosensor 29
4.2 Simulation Result 32
5. Demonstration-3: Transient Device Simulation of Nanowire Array Biosensor using Monte-Carlo Method 36
5.1 Transient LoD 36
5.2 Simulation Result 38
6. Summary and Outlook 44
6.1. Outlook 45
Bibliographies 46

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