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

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.

The Middle Science: Traversing Scale In Complex Many-Body Systems

“…Recent results that first enumerate a reaction network and then calculate rate parameters have been able to capture important features but not completely match atomistic simulations. 200 Aside from the assumptions inherent to transition state theory, it is also not certain that reaction barriers calculated by looking at isolated reactions still hold when looking at the potential energy surface of the whole system. For high-temperature, high-pressure systems, it has also been shown that, in addition to reactions involving stable states, transient species may play a critical role in reaction dynamics.…”

“…Coarse-Graining to Macroscales. In recent years, automatic learning of large chemical reaction networks from atomistic simulation data has been explored, 195,200,201 enabling these reaction networks to then be simulated using kinetic models, either through stochastic simulation or rate equations. This enables orders of magnitude faster propagation in both space and time.…”

Temperature Extrapolation of Molecular Dynamics Simulations of Complex Chemistry to Microsecond Timescales using Kinetic Models: Applications to Hydrocarbon Pyrolysis

“…10, we can observe that at 2,800 K the system needs around 1-10 ns to come to equilibrium with a system starting with CH 4 or with C 4 H 10 , which is the same order of magnitude as the experiments run by Kraus et al Therefore, our model points out that Kraus et al's experiments are on timescales close to the time needed for equilibrium to be reached. It is important to notice that our model is fit on the ReaxFF potential, but ReaxFF has been shown to sometimes fail to reproduce ab initio energies [8] and some common reactions are not observed in ReaxFF simulations [38,39].…”

“…Several methods have been used to investigate the evolution of complex systems in conditions where atomistic simulations cannot be performed in reasonable time. Ford et al [8] developed a method based on a nanoreactor [9] that pushes molecules together so they react more often. With this method, reactions are sampled faster; nonetheless, no information about the rate coefficients can be extracted because pressure and temperature are not well-defined.…”

“…With this method, reactions are sampled faster; nonetheless, no information about the rate coefficients can be extracted because pressure and temperature are not well-defined. In this work [8], Ford et al then use a newly developed algorithm, the quickest diffusion path, to obtain the transition path and then the reaction rate coefficients. With the kinetic model obtained they solve the chemical master equation using an ordinary differential equation (ODE) solver.…”