Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model
Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model
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DOI：
10.1021/acs.jpca.0c09168
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发表时间：
2021-02-11
影响因子：
2.9
通讯作者：
Martinez, Todd J.
中科院分区：
文献类型：
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作者：
Ford, Jason;Seritan, Stefan;Martinez, Todd J.
我们探索根据硝基甲烷分解的计算机反应数据系统构建动力学模型。我们的模型是通过使用 ReaxFF 反作用力场加速分子动力学模拟发现的反应，以计算上可承受的方式构建的。然后优化反应路径以确定反应速率参数。我们引入了一种反应势垒校正方案，该方案将密度泛函理论中的准确热化学数据与 ReaxFF 最小能量路径相结合。我们在不同的热力学状态下验证了我们的模型，显示了与实验数据相似的气相 CO 和 NO 浓度以及高压感应时间的预测。分析动力学模型以发现不同热力学状态下的基本分解反应。
We explore the systematic construction of kinetic models from in silico reaction data for the decomposition of nitromethane. Our models are constructed in a computationally affordable manner by using reactions discovered through accelerated molecular dynamics simulations using the ReaxFF reactive force field. The reaction paths are then optimized to determine reaction rate parameters. We introduce a reaction barrier correction scheme that combines accurate thermochemical data from density functional theory with ReaxFF minimal energy paths. We validate our models across different thermodynamic regimes, showing predictions of gas phase CO and NO concentrations and high-pressure induction times that are similar to experimental data. The kinetic models are analyzed to find fundamental decomposition reactions in different thermodynamic regimes.