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研究生: 陳祺
Chen, Chi
論文名稱: 水泥材料之分子動力學模擬初探
Studies of cementitious materials with molecular dynamics simulations
指導教授: 王雲哲
Wang, Yun-Che
學位類別: 碩士
Master
系所名稱: 工學院 - 土木工程學系
Department of Civil Engineering
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 85
中文關鍵詞: 水泥質材料C-S-H膠體分子動力學
外文關鍵詞: Cementitious materials, C-S-H gel, molecular dynamics
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  • 在本研究中,我們嘗試以分子動力學來模擬數種水泥質相關的材料性質,像是矽酸鈣水化物、矽酸三鈣、矽酸二鈣、鋁酸三鈣、11和14埃的雪矽鈣石,以及以鎂取代雪矽鈣石的中鈣的模擬且可以穩定存在。本研究之分子模型以LAMMPS,配合經驗勢能使其達到到平衡,並計算其應力-應變關係。而量子分子動力學(SIESTA)來分析它們的結構,另用埃爾德法(Ewald)來計算庫倫電場勢能,計算其熱膨脹係數及體容積模數。利用徑向分布函數、結構因子、X光繞射分析對其原子結構進行分析,並討論其力學性質。研究結果中14埃雪矽鈣石的剪力模數約為15.8 GPa到37.5 GPa間、體膨脹係數為70.20 (10^6K^-1)、常壓下體容積模數為46.0 GPa,其中14埃雪矽鈣石在8 GPa的環境下可能發生相變化。

    In this study, we perform molecular dynamics (MD) simulation on several cementitious-related materials, such as CSH, C3S, C3A, as well as 11 and 14 °A tobermorite. A magnesium-substituted tobermorite model is studied, and can be stabilized. Our molecular models are equilibrated and stabilized with empirical interatomic potentials through LAMMPS for stress-strain relationships. In addition, quantum molecular dynamics (QMD) simulation, with SIESTA, was performed on the minerals to verify their structures, as well as thermal expansion coefficients and bulk modulus. The Ewald method was adopted to calculate Coulomb electric potentials. Atomic structural analysis, such as radial distribution function (RDF), structure factor (SF), X-ray diffraction (XRD), of the materials are conducted. Vibration spectra are calculated from velocity autocorrelation functions. Mechanical properties of the materials are discussed from calculated quantities. In the result of 14 °A tobermorite, the shear modulus is around 15.8 GPa ~ 37.5 GPa, thermal expansion coefficient is (10^6K^-1) and bulk modulus is 46.0 GPa in atmospheric. In addition, 14 °A tobermorite may undergo a phase change around 8 GPa at room temperature, according to a change in bulk modulus and atomic configuration.

    CHINESE ABSTRACT . . . . . . . . . . . . . . . . . . . . . i ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . .ii ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . .iii LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . .vi LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . .vii NOMENCLATURE . . . . . . . . . . . . . . . . . . . . . . xii 1 Introduction . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Goals and motivation . . . . . . . . . . . . . . . . . 1 1.2 Literature review . . . . . . . . . . . . . . . . . . .2 1.2.1 Cementitious materials . . . . . . . . . . . . . . . 2 1.2.2 Our MD related research . . . . . . . . . . . . . . .9 1.3 Outline of this thesis . . . . . . . . . . . . . . . .11 2 Theoretical foundations . . . . . . . . . . . . . . . . 15 2.1 Modelling and Simulations . . . . . . . . . . . . . . 15 2.2 Molecular Dynamics . . . . . . . . . . . . . . . . . .16 2.3 Statistical ensembles . . . . . . . . . . . . . . . . 17 2.3.1 Canonical ensemble (NVT) . . . . . . . . . . . . . .17 2.3.2 Isothermal-isobaric ensemble (NPT) . . . . . . . . .18 2.4 The Ewald method . . . . . . . . . . . . . . . . . . .18 2.4.1 The Ewald sum for the Coulomb energy . . . . . . . .18 2.5 Time correlation functions . . . . . . . . . . . . . .19 2.5.1 Time-dependent correlation functions . . . . . . . .20 2.5.2 Power spectra . . . . . . . . . . . . . . . . . . . 20 2.6 Infrared and Raman spectroscopy . . . . . . . . . . . 21 2.7 Radial distribution function . . . . . . . . . . . . .22 2.8 X-ray diffraction . . . . . . . . . . . . . . . . . . 23 3 Computational quantum mechanics . . . . . . . . . . . . 24 3.1 SIESTA . . . . . . . . . . . . . . . . . . . . . . . .24 3.2 LAMMPS . . . . . . . . . . . . . . . . . . . . . . . .24 3.3 CrystalMaker . . . . . . . . . . . . . . . . . . . . .25 4 Results and Discussion . . . . . . . . . . . . . . . . .26 4.1 C3S Model . . . . . . . . . . . . . . . . . . . . . . 27 4.2 C3A Model . . . . . . . . . . . . . . . . . . . . . . 31 4.3 Two Tobermorite Models . . . . . . . . . . . . . . . .35 4.4 C-S-H gel Model . . . . . . . . . . . . . . . . . . . 44 4.5 MSH . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.6 SiO2 Model . . . . . . . . . . . . . . . . . . . . . .44 4.7 Parameter comparison and discussion . . . . . . . . . 51 5 Conclusions and Future Work . . . . . . . . . . . . . . 53 5.1 Conclusions . . . . . . . . . . . . . . . . . . . . . 53 5.2 Future Work . . . . . . . . . . . . . . . . . . . . . 53 LIST OF REFERENCES . . . . . . . . . . . . . . . . . . . .55 APPENDICES Appendix A: Presentation slide . . . . . . . . . . . . . .58 VITA . . . . . . . . . . . . . . . . . . . . . . . . . . .84 Index . . . . . . . . . . . . . . . . . . . . . . . . . . 85

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