Zhu T, He R, Gong S, Xie T, Gorai P, Nielsch K, Grossman JC (2021)
Publication Type: Journal article
Publication year: 2021
Book Volume: 14
Pages Range: 3559-3566
Journal Issue: 6
DOI: 10.1039/d1ee00442e
Thermoelectric power generation represents a promising approach to utilize waste heat. The most effective thermoelectric materials exhibit low thermal conductivityκ. However, less than 5% out of about 105synthesized inorganic materials are documented with theirκvalues, while for the remaining 95%κvalues are missing and challenging to predict. In this work, by combining graph neural networks and random forest approaches, we predict the thermal conductivity of all known inorganic materials in the Inorganic Crystal Structure Database, and chart the structural chemistry ofκinto extended van-Arkel triangles. Together with the newly developedκmap and our theoretical tool, we identify rare-earth chalcogenides as promising candidates, of which we measuredZTexceeding 1.0. We note that theκchart can be further explored, and our computational and analytical tools are applicable generally for materials informatics.
APA:
Zhu, T., He, R., Gong, S., Xie, T., Gorai, P., Nielsch, K., & Grossman, J.C. (2021). Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics. Energy and Environmental Science, 14(6), 3559-3566. https://doi.org/10.1039/d1ee00442e
MLA:
Zhu, Taishan, et al. "Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics." Energy and Environmental Science 14.6 (2021): 3559-3566.
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