Larentzos James P, Rice Betsy M
U.S. Army Research Laboratory , Aberdeen Proving Ground, Maryland 21005, United States.
J Phys Chem A. 2017 Mar 9;121(9):2001-2013. doi: 10.1021/acs.jpca.6b11761. Epub 2017 Feb 22.
Transferable ReaxFF-lg models of nitromethane that predict a variety of material properties over a wide range of thermodynamic states are obtained by screening a library of ∼6600 potentials that were previously optimized through the Multiple Objective Evolutionary Strategies (MOES) approach using a training set that included information for other energetic materials composed of carbon, hydrogen, nitrogen, and oxygen. Models that best match experimental nitromethane lattice constants at 4.2 K and 1 atm are evaluated for transferability to high-pressure states at room temperature and are shown to better predict various liquid- and solid-phase structural, thermodynamic, and transport properties as compared to the existing ReaxFF and ReaxFF-lg parametrizations. Although demonstrated for an energetic material, the library of ReaxFF-lg models is supplied to the scientific community to enable new research explorations of complex reactive phenomena in a variety of materials research applications.
通过筛选约6600个势函数库获得了可转移的硝基甲烷ReaxFF-lg模型，该模型能在广泛的热力学状态下预测多种材料特性。这些势函数先前通过多目标进化策略（MOES）方法进行了优化，使用的训练集包含了由碳、氢、氮和氧组成的其他含能材料的信息。评估了在4.2 K和1 atm下与实验硝基甲烷晶格常数最匹配的模型向室温高压状态的可转移性，结果表明，与现有的ReaxFF和ReaxFF-lg参数化相比，该模型能更好地预测各种液相和固相的结构、热力学及输运性质。尽管是针对一种含能材料进行展示，但ReaxFF-lg模型库已提供给科学界，以便在各种材料研究应用中对复杂的反应现象进行新的研究探索。
