4.8 Article

A Computational Framework to Accelerate the Discovery of Perovskites for Solar Thermochemical Hydrogen Production: Identification of Gd Perovskite Oxide Redox Mediators

Journal

ADVANCED FUNCTIONAL MATERIALS
Volume 32, Issue 25, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202200201

Keywords

concentrated solar energy; density functional theory; hydrogen; perovskite; thermochemical water splitting

Funding

  1. U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Hydrogen and Fuel Cell Technologies Office (HFTO)
  2. HydroGEN Advanced Water Splitting Materials Consortium as part of the Energy Materials Network under U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Hydrogen and Fuel Cell Technologies Office (HFTO) [DE-EE0008088]
  3. National Science Foundation [NSF CHEM-1800592, CBET-2016225]
  4. University of Colorado-Boulder's Graduate Assistance in Areas of National Need, GAANN, Materials for Energy Conversion and Sustainability grant [P200A180012]

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A high-throughput computational framework is used to identify novel multinary perovskite redox mediators, specifically Gd-containing perovskite oxide compositions that split water. The framework employs empirical approaches to evaluate material stabilities, electronic properties, and oxygen vacancy thermodynamics. By applying this computational scheme, 83 promising Gd-containing perovskite oxides are discovered, with three exhibiting catalytic activity in splitting water.
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 ' O-6,O- GdA ' B2O6, and GdA ' BB ' O-6 that 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, Delta H-TR and Delta S-TR. This scheme uses the machine-learned descriptor tau to identify compositions that are likely stable as perovskites, the bond valence method to estimate the magnitude and phase of BO6 octahedral 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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