Revealing the Spectrum of Unknown Layered Materials with Superhuman Predictive Abilities

被引:24
作者
Cheon, Gowoon [1 ]
Cubuk, Ekin D. [2 ]
Antoniuk, Evan R. [3 ]
Blumberg, Lavi [1 ]
Goldberger, Joshua E. [4 ]
Reed, Evan J. [5 ]
机构
[1] Stanford Univ, Dept Appl Phys, Stanford, CA 94305 USA
[2] Google Brain, Mountain View, CA 94043 USA
[3] Stanford Univ, Dept Chem, Stanford, CA 94305 USA
[4] Ohio State Univ, Dept Chem & Biochem, Columbus, OH 43210 USA
[5] Stanford Univ, Dept Mat Sci & Engn, Stanford, CA 94304 USA
来源
JOURNAL OF PHYSICAL CHEMISTRY LETTERS | 2018年 / 9卷 / 24期
关键词
STRUCTURAL PHASE-TRANSITIONS; CHLORIDE CARBIDES; ZIRCONIUM; SCANDIUM; M2CL2C;
D O I
10.1021/acs.jpclett.8b03187
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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.
引用
收藏
页码:6967 / 6972
页数:11
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