Literature DB >> 33569957

Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model.

Jason Ford1,2, Stefan Seritan1,2, Xiaolei Zhu1,2, Michael N Sakano3, Md Mahbub Islam3,4, Alejandro Strachan3, Todd J Martínez1,2.   

Abstract

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.

Entities:  

Year:  2021        PMID: 33569957     DOI: 10.1021/acs.jpca.0c09168

Source DB:  PubMed          Journal:  J Phys Chem A        ISSN: 1089-5639            Impact factor:   2.781


  1 in total

Review 1.  Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities.

Authors:  Idil Ismail; Raphael Chantreau Majerus; Scott Habershon
Journal:  J Phys Chem A       Date:  2022-10-03       Impact factor: 2.944

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.