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

Title:
Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation.
Authors:
Liu M; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Grinberg Dana A; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.; Wolfson Department of Chemical Engineering, Technion-Israel Institute of Technology, Haifa 3200003, Israel., Johnson MS; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Goldman MJ; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Jocher A; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Payne AM; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Grambow CA; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Han K; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Yee NW; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States., Mazeau EJ; Department of Chemical Engineering, Northeastern University, Boston, Massachusetts 02115, United States., Blondal K; School of Engineering, Brown University, Providence, Rhode Island 02912, United States., West RH; Department of Chemical Engineering, Northeastern University, Boston, Massachusetts 02115, United States., Goldsmith CF; School of Engineering, Brown University, Providence, Rhode Island 02912, United States., Green WH; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Source:
Journal of chemical information and modeling [J Chem Inf Model] 2021 Jun 28; Vol. 61 (6), pp. 2686-2696. Date of Electronic Publication: 2021 May 28.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.
Language:
English
Journal Info:
Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Imprint Name(s):
Original Publication: Washington, D.C. : American Chemical Society, c2005-
MeSH Terms:
Cheminformatics* , Software*, Kinetics ; Machine Learning
Entry Date(s):
Date Created: 20210528 Date Completed: 20210809 Latest Revision: 20210809
Update Code:
20250114
DOI:
10.1021/acs.jcim.0c01480
PMID:
34048230
Database:
MEDLINE

Weitere Informationen

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. Most notably, 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 includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. 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.