Deep reaction network exploration at a heterogeneous catalytic interface

Qiyuan Zhao, Yinan Xu, Jeffrey Greeley () and Brett M. Savoie ()
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Qiyuan Zhao: Purdue University
Yinan Xu: Purdue University
Jeffrey Greeley: Purdue University
Brett M. Savoie: Purdue University

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract Characterizing the reaction energies and barriers of reaction networks is central to catalyst development. However, heterogeneous catalytic surfaces pose several unique challenges to automatic reaction network characterization, including large sizes and open-ended reactant sets, that make ad hoc network construction the current state-of-the-art. Here, we show how automated network exploration algorithms can be adapted to the constraints of heterogeneous systems using ethylene oligomerization on silica-supported single-site Ga3+ as a model system. Using only graph-based rules for exploring the network and elementary constraints based on activation energy and size for identifying network terminations, a comprehensive reaction network is generated and validated against standard methods. The algorithm (re)discovers the Ga-alkyl-centered Cossee-Arlman mechanism that is hypothesized to drive major product formation while also predicting several new pathways for producing alkanes and coke precursors. These results demonstrate that automated reaction exploration algorithms are rapidly maturing towards general purpose capability for exploratory catalytic applications.

Date: 2022
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DOI: 10.1038/s41467-022-32514-7

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