4.8 Article

High-Throughput Computational Screening of Perovskites for Thermochemical Water Splitting Applications

Journal

CHEMISTRY OF MATERIALS
Volume 28, Issue 16, Pages 5621-5634

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.chemmater.6b01182

Keywords

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Funding

  1. Institute for Sustainability and Energy at Northwestern (ISEN)
  2. U.S. Department of Energy, Office of Science, Basic Energy Sciences [DE-FG02-07ER46433]
  3. Center for Electrochemical Energy Science (GEES), an Energy Frontier Research Center - U.S. Department of Energy, Office of Science and Office of Basic Sciences
  4. National Science Foundation [DMR-1309957]
  5. Office of the Provost
  6. Office for Research
  7. Northwestern University Information Technology
  8. National Energy Research Scientific Computing Center, a DOE Office of Science User Facility - Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231]
  9. Direct For Mathematical & Physical Scien
  10. Division Of Materials Research [1309957] Funding Source: National Science Foundation

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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 ABO(3) 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 compound as it reduces the number of potential candidates from 5,329 to 383. Finally, our large data set of compounds containing stabilites, oxidation states, and ionic sizes allowed us to revisit the structural maps for perovskites by showing stable and unstable compounds simultaneously.

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