Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Antoniuk, Evan R.; Cheon, Gowoon; Wang, George; Bernstein, Daniel; Cai, William; Reed, Evan J.

doi:10.1038/s41524-023-01114-4

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Journal Article · Fri Aug 25 00:00:00 EDT 2023 · npj Computational Materials

DOI:https://doi.org/10.1038/s41524-023-01114-4· OSTI ID:1996869

; ; ; Bernstein, Daniel; Cai, William; Reed, Evan J.

Abstract

Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model ( SynthNN ) that leverages the entire space of synthesized inorganic chemical compositions. By reformulating material discovery as a synthesizability classification task, SynthNN identifies synthesizable materials with 7× higher precision than with DFT-calculated formation energies. In a head-to-head material discovery comparison against 20 expert material scientists, SynthNN outperforms all experts, achieves 1.5× higher precision and completes the task five orders of magnitude faster than the best human expert. Remarkably, without any prior chemical knowledge, our experiments indicate that SynthNN learns the chemical principles of charge-balancing, chemical family relationships and ionicity, and utilizes these principles to generate synthesizability predictions. The development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1996869

Alternate ID(s):: OSTI ID: 2223022

Journal Information:: npj Computational Materials, Journal Name: npj Computational Materials Journal Issue: 1 Vol. 9; ISSN 2057-3960

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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