Wang Qingqing, He Qi, Xiao Bin, Zhai Dong, Shen Yiheng, Liu Yi, Goddard William A
Materials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai 200444, China.
Materials and Process Simulation Center (MSC), California Institute of Technology, Pasadena, California 91125, United States.
J Phys Chem A. 2024 Jun 27;128(25):5065-5076. doi: 10.1021/acs.jpca.4c01924. Epub 2024 Jun 13.
Efficient and accurate reactive force fields (e.g., ReaxFF) are pivotal for large-scale atomistic simulations to comprehend microscopic combustion processes. ReaxFF has been extensively utilized to describe chemical reactions in condensed phases, but most existing ReaxFF models rely on quantum mechanical (QM) data nearly two decades old, particularly in hydrocarbon systems, constraining their accuracy and applicability. Addressing this gap, we introduce a reparametrized ReaxFF-S22 for C/H/O systems, tailored for studying the pyrolysis and combustion of hydrocarbon fuel. Our approach involves high-level QM benchmarks and large database construction for C/H/O systems, global ReaxFF parameter optimization, and molecular dynamics simulations of typical hydrocarbon fuels. Density functional theory (DFT) computations utilized the M06-2X functional at the meta-generalized gradient approximation (meta-GGA) level with a large basis set (6-311++G**). Our new ReaxFF-S22 model exhibits a minimum 10% enhancement in accuracy compared to the previous ReaxFF models for a large variety of hydrocarbon molecules. This advanced ReaxFF-S22 not only enables efficient large-scale studies on the microscopic chemical reactions of more complex hydrocarbon fuel but also can extend to biofuels, energetic materials, polymers, and other pertinent systems, thus serving as a valuable tool for studying chemical reaction dynamics of the large-scale hydrocarbon condensed phase at an atomistic level.
高效且准确的反应力场(例如ReaxFF)对于理解微观燃烧过程的大规模原子模拟至关重要。ReaxFF已被广泛用于描述凝聚相中的化学反应,但大多数现有的ReaxFF模型依赖于近二十年前的量子力学(QM)数据,特别是在碳氢化合物系统中,这限制了它们的准确性和适用性。为了填补这一空白,我们针对碳/氢/氧系统引入了重新参数化的ReaxFF-S22,专门用于研究碳氢燃料的热解和燃烧。我们的方法包括针对碳/氢/氧系统的高级QM基准测试和大型数据库构建、全局ReaxFF参数优化以及典型碳氢燃料的分子动力学模拟。密度泛函理论(DFT)计算在元广义梯度近似(meta-GGA)水平上使用M06-2X泛函和大基组(6-311++G**)。与之前的ReaxFF模型相比,我们新的ReaxFF-S22模型对于多种碳氢化合物分子的准确性至少提高了10%。这种先进的ReaxFF-S22不仅能够对更复杂的碳氢燃料的微观化学反应进行高效的大规模研究,还可以扩展到生物燃料、含能材料、聚合物和其他相关系统,从而成为在原子水平上研究大规模碳氢凝聚相化学反应动力学的宝贵工具。