Exploring the high-pressure materials genome
Maximilian Amsler, Vinay I. Hegde, Steven D. Jacobsen, Chris Wolverton

TL;DR
This paper introduces a hybrid computational framework that combines data-driven databases with simple enthalpy approximations to predict high-pressure phases and guide materials discovery under extreme conditions.
Contribution
It presents a novel approach integrating large materials databases with a linear enthalpy approximation to efficiently explore high-pressure material phases.
Findings
Explains occurrence of natural phases not stable at ambient conditions.
Estimates pressures for metastable phases to become stable.
Guides discovery of new high-pressure stable phases.
Abstract
A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab initio calculations are widely used to guide experiments by predicting the composition, structure, and properties of high-pressure compounds. However, such techniques are usually computationally expensive and not suitable for large-scale combinatorial exploration. On the other hand, data-driven computational approaches using large materials databases are useful for the analysis of energetics and stability of hundreds of thousands of compounds, but their utility for materials discovery is largely limited to idealized conditions of zero temperature and pressure. Here, we present a novel framework combining the two computational approaches, using a simple linear approximation to the enthalpy of a compound in…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
