finding unprecedentedly low-thermal-conductivity half-heusler semiconductors via high-throughput materials modeling
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2014
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Abstract
The lattice thermal conductivity (κ_{ω}) is a key property for many potential applications of compounds. Discovery of materials with very low or high κ_{ω} remains an experimental challenge due to high costs and time-consuming synthesis procedures. High-throughput computational prescreening is a valuable approach for significantly reducing the set of candidate compounds. In this article, we introduce efficient methods for reliably estimating the bulk κ_{ω} for a large number of compounds. The algorithms are based on a combination of machine-learning algorithms, physical insights, and automatic ab initio calculations. We scanned approximately 79,000 half-Heusler entries in the AFLOWLIB.org database. Among the 450 mechanically stable ordered semiconductors identified, we find that κ_{ω} spans more than 2 orders of magnitude—a much larger range than that previously thought. κ_{ω} is lowest for compounds whose elements in equivalent positions have large atomic radii. We then perform a thorough screening of thermodynamical stability that allows us to reduce the list to 75 systems. We then provide a quantitative estimate of κ_{ω} for this selected range of systems. Three semiconductors having κ_{ω}<5 Wm^{−1} K^{−1} are proposed for further experimental study.
| Reference Key |
carrete2014physicalfinding
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| Authors | ;Jesús Carrete;Wu Li;Natalio Mingo;Shidong Wang;Stefano Curtarolo |
| Journal | american journal of transplantation |
| Year | 2014 |
| DOI |
10.1103/PhysRevX.4.011019
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