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研究生：	黃怡碩 Huang, I-Shou
論文名稱：	為非線性自適應力批配演算法打下基礎：具效益、系統化且從第一原理延伸的簡單水模型重參數化 Laying the Foundations of a Non-Linear Adaptive Force Matching Algorithm: An Economic,Systematic, & Ab Initio Derived Re-Parameterization of a Simple Water
指導教授：	蔡明剛 Tsai, Ming-Kang
學位類別：	碩士 Master
系所名稱：	化學系 Department of Chemistry
論文出版年：	2016
畢業學年度：	104
語文別：	英文
論文頁數：	37
中文關鍵詞：	力批配、第一原理、分子模擬、液態水
英文關鍵詞：	Force Matching, Ab Initio, Molecular Dynamics Simulation, Liquid Water
DOI URL：	https://doi.org/10.6345/NTNU202203904
論文種類：	學術論文
相關次數：	點閱：103 下載：10
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非線性的力參數在參數化是目前計算化學的重大難題，由於非線性的最佳化方法可以產生的錯誤極多。雖然我們可以選擇用線性的最佳化方法，但是如果用在非線性的力參數上，會有系統上的誤差。本文希望提供一個升級過的
自適應力批配演算法(Adaptive Force Matching Method,AFMM)來處理此問題，並以液態水的分子模擬計算作為驗證。初步測驗，包含徑向分布函數以及平均力勢計算實驗，顯示結果有部分地被改良。本文產生的簡單點電荷模組力參數，提供更正確的第一溶劑殼，以及更準確地描述成對力。然而，這些優勢也帶來了一些缺點，本文產生的力參數無法提供正確的第二溶劑殼，也同時完全放棄多體效應。目前已有文獻提出簡單點電荷模組無法完整的描述
液態水的性質，例如第一溶劑殼及第二溶劑殼，本研究試圖在此方面提供更徹底的探討。

On the subject of force field re-parameterization, the Annual Reports in Computational Chemistry, Volume 10 stated that “Non-linear optimization is a grand challenge.” Indeed, the complication and errors of such a non-linear method is not easily fixed. Although linear methods can be used instead, this is at the cost of less precise results. To tackle this issue,an upgraded Adaptive Force Matching Method (AFMM) is proposed based on testing with liquid water model. Preliminary results from radial distribution functions and potential of mean force calculations suggest a partially improved result from previous experiments.It would seem that the generated simple point charge water force field from AFMM, has a better first solvation shell, and a better pair-wise force description. This, however, came at the cost of a poorer second solvation shell fit, and a forfeit of many-body effects. It has been shown that a simple point charge model of water cannot effectively cover both solvation shell, and this work may provide additional insight on the matter.

Table of Figures                        3
中文摘要                                     4
Abstract                                5
Chapter 1 Introduction                        6
Chapter 2 Methodology                        9
2-1. The Adaptive Force-Matching Method        9
2-1-1. Step 1: Force Field Validation        9
2-1-2. Step 2: Molecular Dynamic Simulation 10
2-1-3. Step 3: Snapshot Sampling.        11
2-1-4. Step 4: QM/MM Force Calculations     12
2-1-5. Step 5: Data Weighting                12
2-1-6. Step 6: Force Matching                13
2-2. Radial Distribution Function           14
2-3. Potential of Mean Force                15
Chapter 3 Results & Discussion                17
3-1. The Generated Force Fields                17
3-2. Radial Distribution Function           23
3-2-1. Oxygen-Oxygen RDF                23
3-2-2. Hydrogen- Hydrogen RDF                25
3-2-3. Oxygen-Hydrogen RDF                  26
3-3. Cluster Energy Calculation             27
3-3-1. Energy Component Analysis        28
3-4. Potential of Mean Force                29
3-5. Slab Integrity                        33
Chapter 4 Conclusion                        35
Chapter 5 References                        36
                                

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