Site-averaged kinetics for catalysts on amorphous supports: an importance learning algorithm

Vandervelden, Craig A.; Khan, Salman A.; Scott, Susannah L.; Peters, Baron

doi:10.1039/c9re00356h

Site-averaged kinetics for catalysts on amorphous supports: an importance learning algorithm

Journal Article · Thu Oct 31 00:00:00 EDT 2019 · Reaction Chemistry & Engineering

DOI:https://doi.org/10.1039/c9re00356h· OSTI ID:1800092

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Univ. of California, Santa Barbara, CA (United States). Dept. of Chemical Engineering; OSTI
Univ. of California, Santa Barbara, CA (United States). Dept. of Chemical Engineering
Univ. of California, Santa Barbara, CA (United States). Dept. of Chemical Engineering. Dept. of Chemistry
Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Chemical and Biomolecular Engineering. Dept. of Chemistry

Ab initio calculations have greatly advanced our understanding of homogeneous catalysts and crystalline heterogeneous catalysts. In contrast, amorphous heterogeneous catalysts remain poorly understood. The principal difficulties include (i) the nature of the disorder is quenched and unknown; (ii) each active site has a different local environment and activity; (iii) active sites are rare, often less than ~20% of potential sites, depending on the catalyst and its preparation method. Few (if any) studies of amorphous heterogeneous catalysts have ever attempted to compute site-averaged kinetics, because the exponential dependence on variable activation energy requires an intractable number of ab initio calculations to converge. We present a new algorithm using machine learning techniques (metric learning kernel regression) and importance sampling to efficiently learn the distribution of activation energies. We demonstrate the algorithm by computing the site-averaged activity for a model amorphous catalyst with quenched disorder.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of California, Santa Barbara, CA (United States); Univ. of Kansas, Lawrence, KS (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: FG02-03ER15467; SC0019488

OSTI ID:: 1800092

Journal Information:: Reaction Chemistry & Engineering, Journal Name: Reaction Chemistry & Engineering Journal Issue: 1 Vol. 5; ISSN 2058-9883

Publisher:: Royal Society of ChemistryCopyright Statement

Country of Publication:: United States

Language:: English

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Grafting metal complexes onto amorphous supports: from elementary steps to catalyst site populations via kernel regression Khan, Salman A.; Vandervelden, Craig A.; Scott, Susannah L. Reaction Chemistry & Engineering https://doi.org/10.1039/c9re00357f	journal	January 2020

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