原子力顯微鏡(AFM)具有奈米等級解析能力，而雷射共軛焦掃描顯微鏡(CLSM)則可獲得次微米級的掃瞄解析度表現，自發明以來已被廣泛地運用在生物以及工業領域的檢測與量測。
原子力顯微鏡雖然能獲得高精確度的三維樣本表面輪廓，但卻存在兩個掃描時的劣勢。首先受限於傳統小移動行程的壓電致動器，通常只能獲得一個小的掃瞄影像。 其次由於掃描時探針的動態行為問題，如要獲得一張高品質的掃描影像，其成像的速度將非常緩慢。雷射共軛焦掃描顯微鏡因為採用光學掃描方式，所以可以快速獲得一張掃描影像，但因為受到光學繞射極限的問題，使其解析度無法到達奈米等級，另外也受限於光學反射原理的影響，造成樣本側邊的成像會高度失真。
本論文中，我們結合上述兩種顯微鏡技術，並利用長行程的定位平台以及新穎的掃描演算法，開發出一新型複合式顯微鏡系統，藉此達到高速且高精度之影像品質。此複合式顯微鏡系統具備80奈米(nm)的掃描誤差與2.5 × 2.5釐米(cm)大範圍的掃描能力，透過雷射共軛焦顯微鏡的大範圍高速掃描，並基於樣本表面的熵（Entropy）強度來找尋出感興趣的掃描區域，並規劃長行程原子力顯微鏡之路徑，最後，透過樣本表面特徵比對方式來建構出一張兼具快速、大範圍以及高解析度之三維掃描影像。從一系列的實驗結果能證實本研究所提出的方法，可以節省65%的AFM掃描時間，而解析度僅略遜於原子力顯微鏡，同時更可以掃出釐米等級的大範圍影像，並可以有效解決傳統光學掃描方式，所造成樣本側面資訊失真的問題。

Atomic force microscope (AFM) and confocal laser scanning microscope (CLSM) can obtain the sample’s three-dimensional (3D) surface profile with the nanometer and sub-micron resolution, respectively. These two types of scanning instrument have been widely used in the biological and industrial fields. Despite that the AFM can get a high- resolution 3D image, it has two long-standing disadvantages. First, it suffers from a smaller travel range due to the piezoelectric actuator as the XY-scanner. Second is the dynamic behavior of the scanning probe which leads to low imaging speed. On the other hand, without increasing the same kind of dynamics problem, the CLSM employs laser as the sensing device which benefits in significant increase of the imaging speed. However, there is also a problem that CLSM due to the optical diffraction such that the imaging result cannot reach the nanometer resolution. Besides, the optical reflection principle causes severe distortion on the sidewall of the scanned sample.
In this thesis, we develop a novel hybrid microscope system, which combines two kinds of microscope technology, namely; one by AFM and another by CLSM to simultaneously achieve high-speed and high-resolution 3D scanning image. In order to achieve the above imaging demand, a long travel range positioning stage (LTRPS) and a novel scanning algorithm are also integrated into the hybrid microscope system. The proposed system is capable of providing 2.5 × 2.5 cm^2 large-scale scanning image with 50 nm resolution. Through the use of our method, first the CLSM is used to acquire a large-scale and high-speed 3D scanning image, and then the regions of interest (ROI) based on height entropy H of CLSM image is determined for the AFM path planning. Next, the AFM is called for to scan in particular the ROI to obtain finer scanning image over there. Finally, a merging method is proposed for stitching the scanning images respectively produced by the CLSM and AFM. A series of experimental results validate the proposed system and method as follows: It can save approximately 65% of scanning time compared with that obtained purely by traditional AFM, while keeping the resolution up to 80 nm slightly inferior to that of. Let is also quite worthwhile to mention that the proposed hybrid system is capable of generating centimeter level 3D images and without inducing the sidewall distortion of scanned sample.

致謝 i
摘要 ii
Abstract iii
Table of content v
List of Acronyms vii
List of Figures viii
List of Tables x
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Literature Survey 3
1.2.1 LMR-AFM system 3
1.2.2 Hybrid measuring system 6
1.3 Contribution 10
1.4 Thesis Organization 11
Chapter 2 Preliminary 12
2.1 Fundamentals of Piezoelectric Actuation 12
2.1.1 Piezoelectric effect 13
2.1.2 Hysteresis phenomenon 14
2.2 Fundamentals of Piezoelectric Legs Actuation 15
2.2.1 Piezoelectric legs driving principle 16
2.2.2 Piezoelectric legs driving waveform 18
2.3 Operation Principle of AFM 20
2.3.1 Tip-sample interaction modes 21
2.3.2 AFM scanning schemes 24
2.4 Operation Principle of CLSM 26
2.4.1 Confocal Laser Scanning Microscope 27
Chapter 3 Hardware Design 30
3.1 AFM Subsystem 31
3.1.1 AFM scanning subsystem 33
3.1.2 AFM measuring subsystem 35
3.2 CLSM Subsystem 36
3.2.1 CLSM scanning subsystem 36
3.2.2 CLSM measuring subsystem 39
3.3 Piezoelectric Legs LTRPS subsystem 42
3.4 Hardware Equipment 45
Chapter 4 Novel Hybrid Scanning Algorithm 47
4.1 System Calibration 48
4.2 Cooperative Strategy 51
4.3 Scanning Trajectory 58
4.4 The Integration Method for Scanning Results 61
Chapter 5 Experiments 63
5.1 Experimental Setup 63
5.2 System Controller 66
5.3 Scanning Application 68
5.3.1 CLSM scanning results 69
5.3.2 AFM scanning results 71
5.3.3 Hybrid scanning results 72
Chapter 6 Conclusions 73
Reference 75

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