Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics
Thermoelectric power generation represents a promising approach to utilize waste heat. The most effective thermoelectric materials exhibit low thermal conductivity κ. However, less than 5% out of about 105 synthesized inorganic materials are documented with their κ values, while for the remaining 95% κ values 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 of κ into extended van-Arkel triangles. Together with the newly developed κ map and our theoretical tool, we identify rare-earth chalcogenides as promising candidates, of which we measured ZT exceeding 1.0. We note that the κ chart can be further explored, and our computational and analytical tools are applicable generally for materials informatics.
Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics
Thermoelectric power generation represents a promising approach to utilize waste heat. The most effective thermoelectric materials exhibit low thermal conductivity κ. However, less than 5% out of about 105 synthesized inorganic materials are documented with their κ values, while for the remaining 95% κ values 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 of κ into extended van-Arkel triangles. Together with the newly developed κ map and our theoretical tool, we identify rare-earth chalcogenides as promising candidates, of which we measured ZT exceeding 1.0. We note that the κ chart can be further explored, and our computational and analytical tools are applicable generally for materials informatics.
Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics
Zhu, Taishan (Autor:in) / He, Ran (Autor:in) / Gong, Sheng (Autor:in) / Xie, Tian (Autor:in) / Gorai, Prashun (Autor:in) / Nielsch, Kornelius (Autor:in) / Grossman, Jeffrey C. (Autor:in) / Technische Informationsbibliothek (TIB) (Gastgebende Institution)
2021
Sonstige
Elektronische Ressource
Unbekannt
Thermoelectricity , power generation , Thermoelectric energy conversion , Graph neural networks , Inorganic materials , Materials informatics , Chalcogenides , rare earth element , Structural chemistry , Crystal structure , inorganic compound , lattice dynamics , Waste heat , Decision trees , Inorganic crystal structure database , Rare earths , Thermo-Electric materials , Lattice thermal conductivity , Thermal conductivity
DDC:
690
Copper-based ternary chalcogenides thin films fabricated by PLD as potential thermoelectrics
| British Library Online Contents | 2019
Rare-earth chalcogenides-an emerging class of optical materials
| British Library Online Contents | 1994
| British Library Online Contents | 1994
| British Library Online Contents | 2016
| British Library Online Contents | 2016