Computational Screening of All Stoichiometric Inorganic Materials

Daniel W. Davies, Keith T. Butler, Adam J. Jackson, Andrew Morris, Jarvist M. Frost, Jonathan M. Skelton, Aron Walsh

Research output: Contribution to journalArticlepeer-review

122 Scopus citations


Forming a four-component compound from the first 103 elements of the periodic table results in more than 1012 combinations. Such a materials space is intractable to high-throughput experiment or first-principle computation. We introduce a framework to address this problem and quantify how many materials can exist. We apply principles of valency and electronegativity to filter chemically implausible compositions, which reduces the inorganic quaternary space to 1010 combinations. We demonstrate that estimates of band gaps and absolute electron energies can be made simply on the basis of the chemical composition and apply this to the search for new semiconducting materials to support the photoelectrochemical splitting of water. We show the applicability to predicting crystal structure by analogy with known compounds, including exploration of the phase space for ternary combinations that form a perovskite lattice. Computer screening reproduces known perovskite materials and predicts the feasibility of thousands more. Given the simplicity of the approach, large-scale searches can be performed on a single workstation.

Original languageEnglish
Pages (from-to)617-627
Number of pages11
Issue number4
StatePublished - 13 Oct 2016

Bibliographical note

Funding Information:
We acknowledge the contributions of T. Gauntlett and J. Evans to the addition of Shannon radii and sustainability data in SMACT. This research was supported by the Royal Society, European Research Council (grant no. 277757), and the EPSRC (EP/J017361/1, EP/K004956/1, EP/K016288/1, EP/L017792/1, EP/M009580/1, and EP/G03768X/1).

Publisher Copyright:
© 2016 The Author(s)


  • computational chemistry
  • functional materials
  • high-throughput screening
  • materials design
  • perovskites
  • solar energy
  • structure prediction
  • water splitting


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