An Efficient Discovery of Active, Selective and Stable Catalysts for Electrochemical H2O2 Synthesis Through Active Motif Screening

Abstract

<div> <div> <div> <p>Electrochemical reduction of O2 provides a clean and decentralized pathway to produce H2O2 compared to the current energy-intensive anthraquinone process. As the electrochemical reduction of O2 proceeds via either two-electron or four-electron path- way, it is thus essential to control the selectivity as well as to maximize the catalytic activity. Siahrostami et al. demonstrated a novel approach to control the reaction pathway by optimizing an adsorption ensemble to tune adsorption sites of reaction intermediates, and identified Pt-Hg catalysts from density functional theory (DFT) calculations and experimentally validated this catalyst (Nat. Mater. 2013, 12, 1137). Inspired by this concept, in this work, we apply a state-of-the-art high-throughput screening to develop O2 reduction catalyst for selective H2O2 production. Starting from Materials Project database, we evaluate activity, selectivity and electrochemical stability. To efficiently perform the screening, we introduce an active motif based approach which pre-screens unpromising materials and only performs DFT calculations for promising materials, which significantly reduce the number of the required calculations. We not only provide a list of promising candidates identified by DFT calculations, but also suggest element species to achieve high catalytic activity or H2O2 selectivity for future experimental attempts. Finally, we discuss a strategy for efficient future high-throughput screening using a machine learning pipeline consisting of a non-linear dimension reduction and a density-based clustering. </p> </div> </div> </div>

Direction-Based Graph Representation to Accelerate Stable Catalyst Discovery

“…Motivated by our previous work on high-throughput screening of active, selective, and stable two electron oxygen reduction reaction (2e-ORR) catalysts, we constructed binary alloy structures by the elemental substitution. 26,27 We note that one substituted element should interact with oxygen strongly, while the other should not. Further details can be found in Supplementary Note 1.…”

Selective hydrogen peroxide conversion tailored by surface, interface, and device engineering

“…The cooperation of the atomistic model, machine learning and multi-scale modeling should help screen and discover active site motifs. 166,167 (3) Comprehensive modification and in situ characterizations of catalysts environment Surface of hydrophobicity/hydrophilicity, electronics, electrochemical potential, and interface of local pH distribution and product concentrations, all influence the binding energies of key intermediates OH* or OOH* for two-electron WOR and ORR, as well as the transport and stability issues of H 2 O 2 . Developing in situ characterizations, including FTIR, Raman spectroscopy, and X-ray spectroscopy, can help reveal the dynamic change of catalysts, identify the surface intermediates under operational conditions, and map the local pH distribution around the active sites.…”