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RCARM: Reaction classification using automated reaction mapping
Author(s) -
Kouri Tina M.,
Crabtree John D.,
Huynh Lam,
Dean Anthony M.,
Mehta Dinesh P.
Publication year - 2013
Publication title -
international journal of chemical kinetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.341
H-Index - 68
eISSN - 1097-4601
pISSN - 0538-8066
DOI - 10.1002/kin.20749
Subject(s) - chemistry , abstraction , chemical reaction , hydrogen atom abstraction , identification (biology) , task (project management) , reaction mechanism , computer science , simple (philosophy) , mechanism (biology) , artificial intelligence , data mining , biological system , hydrogen , organic chemistry , catalysis , philosophy , botany , epistemology , economics , biology , management
Detailed chemical kinetic modeling of gas‐phase reactions can result in automatically generated mechanisms that contain thousands of reactions. In this paper, we describe the development of a rule‐based expert system tool that organizes these reactions into classes such as hydrogen abstraction and beta scission. We have developed 29 simple classification rules, 20 complex (well‐skipping) classification rules, and four second‐stage classification rules. This greatly simplifies the task of the chemical kineticist who wishes to verify, analyze, and gain insights into the reactions comprising the mechanism. This system, which is based on the automated identification of the bonds that break and form in a chemical reaction (the reaction mapping problem), is used to classify reactions in three different mechanisms. © 2012 Wiley Periodicals, Inc. Int J Chem Kinet 45: 125–139, 2013