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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.
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Accelerated Perovskite Oxide Development for Thermochemical Energy Storage by a High‐Throughput Combinatorial Approach
Abstract The structural and compositional flexibility of perovskite oxides and their complex yet tunable redox properties offer unique optimization opportunities for thermochemical energy storage (TCES). To improve the relatively inefficient and empirical‐based approaches, a high‐throughput combinatorial approach for accelerated development and optimization of perovskite oxides for TCES is reported here. Specifically, thermodynamic‐based screening criteria are applied to the high‐throughput density functional theory (DFT) simulation results of over 2000 A/B‐site doped SrFeO3−δ. 61 promising TCES candidates are selected based on the DFT prediction. Of these, 45 materials with pure perovskite phases are thoroughly evaluated. The experimental results support the effectiveness of the high‐throughput approach in determining both the oxygen capacity and the oxidation enthalpy of the perovskite oxides. Many of the screened materials exhibit promising performance under practical operating conditions: Sr0.875Ba0.125FeO3−δexhibits a chemical energy storage density of 85 kJ kgABO3−1under an isobaric condition (with air) between 400 and 800 °C whereas Sr0.125Ca0.875Fe0.25Mn0.75O3−δdemonstrates an energy density of 157 kJ kgABO3−1between 400 °C/0.2 atm O2and 1100 °C/0.01 atm O2. An improved set of optimization criteria is also developed, based on a combination of DFT and experimental results, to improve the effectiveness for accelerated development of redox‐active perovskite oxides.
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- PAR ID:
- 10402875
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Energy Materials
- Volume:
- 13
- Issue:
- 18
- ISSN:
- 1614-6832
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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