From Organized High-throughput Data to Phenomenological Theory using Machine Learning

Chem. Mater., Just Accepted Manuscript DOI: 10.1021/acs.chemmater.5b04109 Publication Date (Web): February 2, 2016 Copyright © 2016 American Chemical Society Abstract Understanding the behavior (and failure) of dielectric insulators experiencing extreme electric fields is critical to the operation of present and emerging electrical and electronic devices. Despite its importance, the development of a predictive theory of dielectric breakdown has remained a challenge, owing to the complex multiscale nature of this process. Here, we focus on the intrinsic dielectric breakdown field of insulators – the theoretical limit of breakdown determined purely by the chemistry of the material, i.e., the elements the material is composed of, the atomic-level structure, and the bonding. Starting from a benchmark dataset (generated from laborious first principles computations) of the intrinsic dielectric breakdown field of a variety of…


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