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Title: A Computational Framework to Accelerate the Discovery of Perovskites for Solar Thermochemical Hydrogen Production: Identification of Gd Perovskite Oxide Redox Mediators
Abstract A high‐throughput computational framework to identify novel multinary perovskite redox mediators is presented, and this framework is applied to discover the Gd‐containing perovskite oxide compositions Gd2BB′O6,GdA′B2O6, and GdA′BB′O6that split water. The computational scheme uses a sequence of empirical approaches to evaluate the stabilities, electronic properties, and oxygen vacancy thermodynamics of these materials, including contributions to the enthalpies and entropies of reduction, ΔHTRand ΔSTR. This scheme uses the machine‐learned descriptor τ to identify compositions that are likely stable as perovskites, the bond valence method to estimate the magnitude and phase of BO6octahedral tilting and provide accurate initial estimates of perovskite geometries, and density functional theory including magnetic‐ and defect‐sampling to predict STCH‐relevant properties. Eighty‐three promising STCH candidate perovskite oxides down‐selected from 4392 Gd‐containing compositions are reported, three of which are referred to experimental collaborators for characterization and exhibit STCH activity. The results demonstrate that the high‐throughput computational scheme described herein—which is used to evaluate Gd‐containing compositions but can be applied to any multinary perovskite oxide compositional space(s) of interest—accelerates the discovery of novel STCH active redox mediators with reasonable computational expense.  more » « less
Award ID(s):
2016225
PAR ID:
10491216
Author(s) / Creator(s):
; ;
Publisher / Repository:
Wiley
Date Published:
Journal Name:
Advanced Functional Materials
Volume:
32
Issue:
25
ISSN:
1616-301X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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