Revealing the Spectrum of Unknown Layered Materials with Superhuman Predictive Abilities

We discover the chemical composition of over 1000 materials that are likely to exhibit layered and 2D phases but have yet to be synthesized. This includes two materials our calculations indicate can exist in distinct structures with different band gaps, expanding the short list of 2D phase-change ma...

Full description

Saved in:
Bibliographic Details
Published in:The journal of physical chemistry letters 2018-12, Vol.9 (24), p.6967-6972
Main Authors: Cheon, Gowoon, Cubuk, Ekin D, Antoniuk, Evan R, Blumberg, Lavi, Goldberger, Joshua E, Reed, Evan J
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We discover the chemical composition of over 1000 materials that are likely to exhibit layered and 2D phases but have yet to be synthesized. This includes two materials our calculations indicate can exist in distinct structures with different band gaps, expanding the short list of 2D phase-change materials. Whereas databases of over 1000 layered materials have been reported, we provide the first full database of materials that are likely layered but are yet to be synthesized, providing a roadmap for the synthesis community. We accomplish this by combining physics with machine learning on experimentally obtained data and verify a subset of candidates using density functional theory. We find that our model performs five times better than practitioners in the field at identifying layered materials and is comparable to or better than professional solid-state chemists. Finally, we find that semisupervised learning can offer benefits for materials design where labels for some of the materials are unknown.
ISSN:1948-7185
1948-7185
DOI:10.1021/acs.jpclett.8b03187