本研究主要以第一原理分子動力學計算結合量子力學及分子動力學，進行研究於高溫作用下熔融鹽電解質熱電池之熱/質傳輸計算，以評估熱電池在不同操作溫度下對電池性能之影響；後續參考國外文獻所提供之實驗結果，以驗證本研究模型之正確性與可行性，進而建立一套具多尺度且完整的模擬工具，期能達到開發新式熔融鹽電解質熱電池之性能預測與優化目的。
熱電池又稱之為熱啟動電池，主要特徵為使用之電解質由共晶混合鹽類所組成，當電池外部熱源或點火器啟動時，透過各單電池的上下熱片傳遞大量的熱，迅速使電解質呈熔融態；並啟動熱電池開始作電化學反應。在本研究模擬計算方法，首先對所建構之第一原理分子動力學模擬系統進行粒子數收斂測試，確認在計算效率及精準度上取得最佳平衡，以減少計算資源。接著針對模擬計算之徑向分布函數、擴散係數、離子傳導率、比熱及熱傳導率等重要熱傳與質傳性質，參考國外文獻實驗結果作比較與分析，探究不同操作溫度下各種傳輸性質對熱電池之影響機制。
本論文進而提出新型之電解質材料，進行熱質傳的性質預測，作為往後設計新型電解質的參考依據。最後，利用微觀模擬所得到的性質及物理特性，初步建立熱電池之巨觀尺度模型與模擬計算熱傳分佈情形，並針對熱電池失效模式作預測，以供未來使用壽命分析。

The main propose of this research is to simulate heat and mass transfer properties and performance prediction of molten-salt electrolytes of thermal batteries using the integration of first-principles molecular dynamics (FPMD). It is followed by predicting heat and mass transfer properties in order to analyze how temperature effect on the performance of thermal batteries. Furthermore, we compare simulation results with experimental data to verify our simulation model to construct a series of multi-scale simulation tools. Thermal batteries are also called thermally activated batteries, which employ eutectic salts as their electrolytes. They are activated by electrical ignition on heat pellets, and then exhaust heat to melt the electrolyte and start the electrochemical reaction. In our simulation, we calculate specific heat and ionic conductivity to test convergence of atom numbers. Then we evaluate heat and mass transfer properties of binary system and compare them with experimental literatures to verify our simulation models. This is for investigation of how heat and mass transfer properties affect at different operating temperatures in the realistic cases.
Finally, we predict all the properties of ternary and quaternary systems from our FPMD simulations. Then we employ computational fluid dynamics (CFD) technique to predict the temperature distribution of a unit cell at the macro scale. All these simulation techniques provide a low cost alternative to experiments and is able to optimize the battery design at the realistic operating co

[1]R.A. Guidotti, and P. Masset, Thermally activated (“thermal”) battery technology: Part I: An overview. Journal of Power Sources, 161(2): p. 1443-1449, 2006.
[2]S. Fujiwara, Osaka, Molten Salt and Thermal Battery. United States Patent, US8,221,912 B2, 2012.
[3]D. Carfi, The Pointwise Hellmann-Feynman Theorem. AAPP, 1004(14), 2010.
[4]K. Fukasawa, A. Uehara, T. Nagai, N. Sato, T. Fujii, and H. Yamana, Thermodynamic Properties of Trivalent Lanthanide and Actinide Ions in Molten Mixtures of LiCl and KCl. J. Nucl. Mater., 424, 17, 2012.
[5]P. Masset, and R. A. Guidotti, Thermally activated (thermal) battery technology Part II. Molten salt electrolytes. J. Power Sources, 164, 397, 2007.
[6]N. Galamba, C.A.N. de Castro, and J.F. Ely, Thermal conductivity of molten alkali halides from equilibrium molecular dynamics simulations. Journal of Chemical Physics, 120(18): p. 8676-8682, 2004.
[7]F. Müller-Plathe, A simple nonequilibrium molecular dynamics method for calculating the thermal conductivity. The Journal of Chemical Physics, 106(14): p. 6082-6085, 1997.
[8]L. Zheng, S.N. Luo, and D.L. Thompson, Molecular dynamics simulations of melting and the glass transition of nitromethane. Journal of Chemical Physics, 124(10), 2006.
[9]N. Ohtori, T. Oono, and K. Takase, Thermal conductivity of molten alkali halides: Temperature and density dependence. Journal of Chemical Physics, 130(4), 2009.
[10]M. A. Ratner and G. C. Schatz. , Introduction to Quantum Mechanics in Chemistry.Prentice Hall, 2000.
[11]W. Kohn and L. J. Sham, Self-Consistent Equation including Exchange and correlation Effects. Phys. Rev. 140, A1133, 1965.
[12]J.P. Perdew, K. Burke, and M. Ernzerhof, Generalized Gradient Approximation Made Simple. Physical Review Letters, 77(18): p. 3865-3868, 1996.
[13]M.C. Payne, M.P. Teter, D.C. Allan, T.A. Arias, and J.D. Joannopoulos, Iterative Minimization Techniques for Abinitio Total-Energy Calculations - Molecular-Dynamics and Conjugate Gradients. Reviews of Modern Physics, 64(4): p. 1045-1097, 1992.
[14]C. Woodward, M. Asta, D. R. Trinkle, J. Lill, and S. Angioletti-Uberti, Ab initio simulations of molten Ni alloys. J. Appl. Phys., 107, 113522, 2010.
[15]M. Parrinello, M. Sprik, and J. VandeVondele, The influence of temperature and density functional models in ab initio molecular dynamics simulation of liquid water.Journal of Chemical Physics, 122, (10), 2005.
[16]F. Mȕller-Plathe, A simple nonequilibrium molecular dynamics method for calculating the thermal conditivity. The Journal of Chemical Physics, 106(14): p. 6802-6805, 1997.
[17]R. L. Rowley, Statistal Mechanics for Thermophysical Property Calculations. 1994.
[18]P. Masset, Ionic conductivity measurements of molten iodide-based electrolytes. The Journal of Power Source, 160 (14): p.752-757, 2006.
[19]M. P. Allen, D. J. Tildesley, Computer Simulation of liquids.Oxford, 1987.
[20]S. Nose, A unified formulation of the constant temperature molecular dynamics methods. The Journal of Chemical Physics, 81(1): p. 511-519, 1984.
[21]W.G. Hoover, Canonical dynamics: Equilibrium phase-space distributions. Physical Review A, 31(3): p. 1695-1697, 1985.
[22]D. Frenkel and B. Smit, Understanding Molecular Simulation From Algorithms to Applications.2nd edition, 2001.
[23]J. Wang, Z. Sun, G. Lu, and T. Yu, Molecular Dynamics Simulations of the Local Strucures and Transport Coefficients of Molten Alkali Chlorides.J. Phys. Chem. B 118, 10196-10206, 2014.
[24]N. Haimovich, D. R. Dekel, and S. Brandon, A Simulator for System-Level Analysis of Heat Transfer and Phase Change in Thermal Batteries. I. J. of The Electrochemical Society, 156(6), A442-A453, 2009.