Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

Abstract

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters.Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. One important change is that RMG v3.0 is now Python 3 compatible, which supports the most up-to-date versions of cheminformatics and machine learning packages that RMG depends on. Additionally, RMG can now generate heterogeneous catalysis models, in addition to the previously available gas-and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release also includes parallelization for reaction generation and on-the-fly quantum calculations, and a new molecule isomorphism approach to improve computational performance. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111)

“…RMG includes several libraries of rate constants, which have been taken from values reported in the literature or computed via DFT. 47 However, for the purpose of the present work, all of the rate constants were estimated using BEP relations, with one exception, the dissociation of CO 2 * . Due to the comparatively unique structure of CO 2 * , the activation energy for CO 2 * dissociation is not well described by the general BEP relation for cleavage a C=O bond on a surface and was, therefore, included as a specific reaction in a library based on previous work.…”

“… 39 − 46 One such approach is the automatic Reaction Mechanism Generator (RMG) of Green and co-workers. 43 , 47 , 48 Originally developed for gas-phase pyrolysis, RMG has been expanded to include reactions on surfaces. 44 − 47 …”

“… 43 , 47 , 48 Originally developed for gas-phase pyrolysis, RMG has been expanded to include reactions on surfaces. 44 − 47 …”

Automated Exploration of Prebiotic Chemical Reaction Space: Progress and Perspectives

“…Interactive frameworks for exploring chemical reaction space have been developed, for example Molpher software [56]. Bespoke automated computational approaches for generating CRNRs can be constructed modularly, for example by integrating graph grammar operations such as those used in MØD [41], reactive molecular dynamics tools such as ReacNetGenerator [57] and Python (programming language frameworks) such as Reaction Mechanism Generator (RMG) [58,59], CGRtools (Condensed Graph of Reaction) [60], and Rule Input Network Generator (RING) for generating CRNRs from complex reactive systems [61], among others. Other tools potentially useful for constructing such pipelines include pReSt [62] to discover novel chemistries in automated CRNRs, and CERENA (ChEmical REaction Network Analyzer) [63] to model stochastic chemical kinetics in chemical reaction networks.…”

Extensive High-Accuracy Thermochemistry and Group Additivity Values for Halocarbon Combustion Modeling

“…using a database of reaction templates, thermokinetic data, and estimation methods. 5,6 These chemical properties are first sought in a database of known parameters, but are more commonly estimated using hierarchical decision trees. Thermochemical parameters…”