TY - JOUR
T1 - Efficient Discovery of Active, Selective, and Stable Catalysts for Electrochemical H2O2Synthesis through Active Motif Screening
AU - Back, Seoin
AU - Na, Jonggeol
AU - Ulissi, Zachary W.
N1 - Funding Information:
S.B. acknowledges the support from NRF funded by the Ministry of Science and ICT (NRF-2020R1F1A1048324, 2015M3D3A1A01064929) and the Sogang University Research Grant of 202010002.01. This research used resources of Korea Institute of Science and Technology Information (KSC-2020-CRE-0116) and the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract no. DE-AC02-05CH11231.
Publisher Copyright:
© 2021 American Chemical Society. All rights reserved.
PY - 2021/3/5
Y1 - 2021/3/5
N2 - 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 a two-electron or a four-electron pathway, it is thus essential to control the selectivity as well as to maximize the catalytic activity. Siahrostami et al. [ Nat. Mater. 2013, 12, 1137 ] demonstrated a novel approach to control the reaction pathway by optimizing an adsorption ensemble to tune adsorption sites of reaction intermediates, identified Pt-Hg catalysts from density functional theory (DFT) calculations, and experimentally validated this catalyst. Inspired by this concept, in this work, we apply a state-of-the-art high-throughput screening to develop an O2 reduction catalyst for selective H2O2 production. Starting from the 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 performs DFT calculations only for promising materials, which significantly reduces the number of the required calculations. Finally, we discuss a strategy for efficient future high-throughput screening using a machine learning pipeline consisting of a nonlinear dimension reduction and a density-based clustering.
AB - 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 a two-electron or a four-electron pathway, it is thus essential to control the selectivity as well as to maximize the catalytic activity. Siahrostami et al. [ Nat. Mater. 2013, 12, 1137 ] demonstrated a novel approach to control the reaction pathway by optimizing an adsorption ensemble to tune adsorption sites of reaction intermediates, identified Pt-Hg catalysts from density functional theory (DFT) calculations, and experimentally validated this catalyst. Inspired by this concept, in this work, we apply a state-of-the-art high-throughput screening to develop an O2 reduction catalyst for selective H2O2 production. Starting from the 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 performs DFT calculations only for promising materials, which significantly reduces the number of the required calculations. Finally, we discuss a strategy for efficient future high-throughput screening using a machine learning pipeline consisting of a nonlinear dimension reduction and a density-based clustering.
KW - active motif screening
KW - density functional theory calculations
KW - ensemble effect
KW - high-throughput screening
KW - hydrogen peroxide
KW - intermetallic alloys
KW - ligand effect
UR - http://www.scopus.com/inward/record.url?scp=85101697577&partnerID=8YFLogxK
U2 - 10.1021/acscatal.0c05494
DO - 10.1021/acscatal.0c05494
M3 - Article
AN - SCOPUS:85101697577
SN - 2155-5435
VL - 11
SP - 2483
EP - 2491
JO - ACS Catalysis
JF - ACS Catalysis
IS - 5
ER -