ChemDyME: Kinetically Steered, Automated Mechanism Generation through Combined Molecular Dynamics and Master Equation Calculations

Abstract

In many scientific fields, there is an interest in understanding the way in which complex chemical networks evolve. The chemical networks which researchers focus upon, have become increasingly complex and this has motivated the development of automated methods for exploring chemical reactivity or conformational change in a "black-box" manner, harnessing modern computing resources to automate mechanism discovery. In this work we present a new approach to automated mechanism generation implemented which couples molecular dynamics and statistical rate theory to automatically find kinetically important reactions and then solve the time evolution of the species in the evolving network.Key to this ChemDyME approach is the novel concept of "kinetic convergence" whereby the search for new reactions is constrained to those species which are kinetically favorable at the conditions of interest.We demonstrate the capability of the new approach for two systems, a well-studied combustion system, and a multiple oxygen addition system relevant to atmospheric aerosol formation.

New Tools for Taming Complex Reaction Networks: The Unimolecular Decomposition of Indole Revisited

“…These methods range from saddle points search algorithms − to automated protocols for chemical reaction space exploration. − The vast majority of automated methods leverage chemical heuristics and/or reactive molecular dynamics (MD) simulations to reveal complex reaction networks (RXNets). Some of these ideas have been implemented in computer programs like autodE , AutoMeKin , ChemDyME , ChemTraYzer , GRRM , KinBot , and RMG . These methods are particularly effective with chemical systems of small to medium size, depending on the computational resources that are available.…”

CARNOT: a Fragment-Based Direct Molecular Dynamics and Virtual–Reality Simulation Package for Reactive Systems

“…10−15,17,23,48−53 Glowacki and collaborators developed a series of interactive molecular dynamics methods and software for user-guided VR and automated reaction discovery. 18,19,22,23,29,53 Zimmerman and co-workers used bond-breaking and formation rules to locate the chemical reaction steps. 54,55 The reaction mechanism generator (RMG) program 51,56 makes use of reaction rules and optimization algorithms to generate chemical reaction mechanisms automatically.…”

“…The number of chemical species and reactions in processes such as combustion, interstellar processes, and atmospheric chemistry can be enormous, which constitute a complex chemical reaction network . The reliability of kinetic modeling based on such reaction networks and the prediction of the overall reaction flux depend on both the completeness of the chemical composition and the accuracy of the phenomenological rate constants. − Consequently, there have been continuing efforts, either relying on experimental databases of known reactions or following computational strategies, aimed at developing theories and algorithms to explore the vast dimension and possibilities of the so-called chemical reaction space. ,− Advances in quantum chemistry and data-driven techniques such as machine learning further stimulated recent progress. ,,,− The main goal is to find all possible intermediates and transition states (TS’s) as well as elementary reaction steps. ,− However, a common theme of traditional approaches is to perform the search based on individual reaction steps through the optimization of TS structures and minimum-energy paths (MEPs). − The process is effective, but laborious and slow, and, critically, unconventional and important mechanisms and reaction dynamics could be missed . Furthermore, it is even questionable if the rate constants determined through geometry optimizations, corresponding to zero Kelvin, are adequate to model phenomenological processes at high temperature and pressure conditions by solving rate law equations.…”

Community Reaction Network Reduction for Constructing a Coarse-Grained Representation of Combustion Reaction Mechanisms

“…Recently, Blau et al developed a chemical reaction network for a Li-ion solid electrolyte interphase consisting of more than 6000 species, , and the database generated by this technique was analyzed by species filters, Monte Carlo trajectories, and heuristic analysis of average trajectories to reduce to 18 network species . There have been a number of alternatives for automatic mechanism generation − and fragment-based, virtual-reality direct-molecular-dynamics simulations along with network analysis of mechanisms of combustion reactions. − However, in many situations, the reduced models are still too large to meet the requirement of CFD simulations . Furthermore, processes that play rate-limiting roles or driving reactions may not be the most reactive or least reactive ones, and the interconversion, that is, coupling of reactive species, can be highly temperature-dependent, making it a challenging task in the identification of representative species and reaction steps. , Therefore, mechanism reduction continues to be an active research field, and it is of interest to develop methods that integrate reaction rates and species composition across size and temporal scales.…”