A combined DFTB nanoreactor and reaction network generator approach for the mechanism of hydrocarbon combustion.
Jiawei BaiXiaoqiang LiuTingyu LeiBotao TengXiao-Dong WenPublished in: Chemical communications (Cambridge, England) (2021)
We explored the mechanism of ethylene combustion by combining a density functional tight-binding based nanoreactor molecular dynamic method (DFTB-NMD) and a hidden Markov model (HMM) based reaction network generator approach. The results demonstrate that the DFTB-NMD is a promising method to predict the mechanism of complicated combustion reactions.