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Strategy to improve catalytic trend predictions for methane oxidation and reforming
Author(s) -
Baek Byeongjin,
Aboiralor Abraham,
Wang Shengguang,
Kharidehal Purnima,
Grabow Lars C.,
Massa Jacob D.
Publication year - 2017
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.15404
Subject(s) - catalysis , methane , bond cleavage , chemistry , scaling , reaction mechanism , parameterized complexity , anaerobic oxidation of methane , density functional theory , computational chemistry , thermodynamics , nanotechnology , chemical engineering , materials science , computer science , organic chemistry , engineering , mathematics , physics , algorithm , geometry
Computational catalysts screening is an increasingly popular technique, in which the mechanism from a known good catalyst is commonly adopted, parameterized from linear scaling relationships, and then used in a microkinetic model to identify other metal alloys with incrementally improved activity. This strategy, however, fails to identify truly novel catalysts that operate under nontraditional reaction conditions and exhibit alternative dominant reaction pathways. Using methane oxidation and reforming we investigated a series of O* and OH*‐assisted C‐H scission and C‐O bond formation pathways. Notably, for methane oxidation we discovered a second local optimum for O*‐assisted C‐H bond activation near Ag, which is inactive if only the direct C‐H scission route is considered. In light of the significant qualitative difference in the predicted catalytic trends when parallel mechanisms are allowed, we propose a minimum barrier assumption to rapidly screen for potentially important alternative pathways without the need for costly density functional theory simulations. © 2016 American Institute of Chemical Engineers AIChE J , 63: 66–77, 2017