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 conjunction with ambient-conditions data currently available in high-throughput databases of calculated materials properties. We demonstrate its utility by explaining the occurrence of phases in nature that are not ground states at ambient conditions and by estimating the pressures at which such ambient-metastable phases become thermodynamically accessible, as well as guiding the exploration of ambient-immiscible binary systems via sophisticated structural search methods to discover new high-pressure phases.
| Original language | English (US) |
|---|---|
| Article number | 041021 |
| Journal | Physical Review X |
| Volume | 8 |
| Issue number | 4 |
| DOIs | |
| State | Published - Nov 9 2018 |
Funding
M.A. (construction of linear model, crystal structure prediction) acknowledges support from the Novartis UniversitÃt Basel Excellence Scholarship for Life Sciences and the Swiss National Science Foundation (Projects No. P300P2-158407 and No. P300P2-174475). V.I.H. (model implementation, high-throughput calculations) and C.W. acknowledge support from the Department of Energy, Office of Science, Basic Energy Sciences under Grant No. DE-SC0015106. S.D.J. acknowledges support from NSF Grant No. DMR-1508577 and the Carnegie/DOE Alliance Center (CDAC). The authors acknowledge support from the Data Science Initiative at Northwestern University. The computational resources from the Swiss National Supercomputing Center in Lugano (Projects No. s499, No. s621, and No. s700), the Extreme Science and Engineering Discovery Environment (XSEDE) (which is supported by National Science Foundation Grant No. OCI-1053575), the Bridges System at the Pittsburgh Supercomputing Center (PSC) (which is supported by NSF Grant No. ACI-1445606), the Quest High Performance Computing Facility at Northwestern University, and the National Energy Research Scientific Computing Center (DOE: DE-AC02-05CH11231) are gratefully acknowledged. M. A. and V. I. H. conceived and carried out the project, and contributed equally to this work. S. D. J. and C. W. supervised the project, and all authors contributed to writing the manuscript. M. A. (construction of linear model, crystal structure prediction) acknowledges support from the Novartis Universität Basel Excellence Scholarship for Life Sciences and the Swiss National Science Foundation (Projects No. P300P2-158407 and No. P300P2-174475). V. I. H. (model implementation, high-throughput calculations) and C. W. acknowledge support from the Department of Energy, Office of Science, Basic Energy Sciences under Grant No. DE-SC0015106. S. D. J. acknowledges support from NSF Grant No. DMR-1508577 and the Carnegie/DOE Alliance Center (CDAC). The authors acknowledge support from the Data Science Initiative at Northwestern University. The computational resources from the Swiss National Supercomputing Center in Lugano (Projects No. s499, No. s621, and No. s700), the Extreme Science and Engineering Discovery Environment (XSEDE) (which is supported by National Science Foundation Grant No. OCI-1053575), the Bridges System at the Pittsburgh Supercomputing Center (PSC) (which is supported by NSF Grant No. ACI-1445606), the Quest High Performance Computing Facility at Northwestern University, and the National Energy Research Scientific Computing Center (DOE: DE-AC02-05CH11231) are gratefully acknowledged. We thank Professor C. Umrigar, Professor R. Hoffmann, and Professor F. DiSalvo at Cornell University for valuable expert discussions.
ASJC Scopus subject areas
- General Physics and Astronomy