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Automatic Mechanism and Kinetic Model Generation for Gas‐ and Solution‐Phase Processes: A Perspective on Best Practices, Recent Advances, and Future Challenges
Author(s) -
Van de Vijver Ruben,
Vandewiele Nick M.,
Bhoorasingh Pierre L.,
Slakman Belinda L.,
Seyedzadeh Khanshan Fariba,
Carstensen HansHeinrich,
Reyniers MarieFrançoise,
Marin Guy B.,
West Richard H.,
Van Geem Kevin M.
Publication year - 2015
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.20902
Subject(s) - mechanism (biology) , biochemical engineering , chemistry , field (mathematics) , production (economics) , representation (politics) , process engineering , computer science , nanotechnology , physics , engineering , materials science , mathematics , quantum mechanics , politics , political science , law , pure mathematics , economics , macroeconomics
Completely automated mechanism generation of detailed kinetic models is within reach in the coming decade. The recent developments in this field of chemical reaction engineering are anticipated to lead to some groundbreaking discoveries in the future, extending our fundamental understanding and resolving many of today's society problems such as energy production and conversion, emission reduction, greener chemical production processes, etc. In the present review, the focus is on the core of these automated mechanism generation for gas‐phase and solution‐phase processes that is on how the reaction kinetics and thermodynamic and transport properties of species are estimated and calculated starting from the fundamental elements of the software. With tasks such as the definition of reaction rules and reaction families, the unambiguous representation of species, and the choice of different termination criteria, generating a good reaction mechanism is still not as simple as pressing a “run” button. One of the main challenges that still needs to be overcome is how to deal with data scarcity and the combination with affordable computational chemistry calculations seems the logical step forward. The best practices are illustrated in a butane pyrolysis case study, which also exposes the challenges in the field of automatic kinetic model generation.