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High-Throughput Computational Screening of Perovskites for Thermochemical Water Splitting Applications
Author(s) -
Antoine Emery,
James E. Saal,
Scott Kirklin,
Vinay I. Hegde,
Chris Wolverton
Publication year - 2016
Publication title -
chemistry of materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.741
H-Index - 375
eISSN - 1520-5002
pISSN - 0897-4756
DOI - 10.1021/acs.chemmater.6b01182
Subject(s) - ternary operation , density functional theory , water splitting , perovskite (structure) , ionic bonding , materials science , work (physics) , chemical stability , hydrogen , hydrogen fuel , phase (matter) , chemical physics , stability (learning theory) , thermodynamics , chemistry , nanotechnology , computational chemistry , catalysis , ion , physics , crystallography , computer science , biochemistry , photocatalysis , organic chemistry , machine learning , programming language
The use of hydrogen as fuel is a promising avenue to aid in the reduction of greenhouse effect gases released in the atmosphere. In this work, we present a high-throughput density functional theory (HT-DFT) study of 5,329 cubic and distorted perovskite ABO3 compounds to screen for thermodynamically favorable two-step thermochemical water splitting (TWS) materials. From a data set of more than 11,000 calculations, we screened materials based on the following: (a) thermodynamic stability and (b) oxygen vacancy formation energy that allow favorable TWS. From our screening strategy, we identify 139 materials as potential new candidates for TWS application. Several of these compounds, such as CeCoO3 and BiVO3, have not been experimentally explored yet for TWS and present promising avenues for further research. We show that taking into consideration all phases present in the A–B–O ternary phase, as opposed to only calculating the formation energy of a compound, is crucial to assess correctly the stability of a ...

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