Lattice Thermal Conductivity: An Accelerated Discovery Guided by Machine Learning
Author:
Affiliation:
1. School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon 16419, South Korea
2. School of Applied Data Science, Sungkyunkwan University, Suwon 16419, South Korea
Funder
National Research Foundation of Korea
Publisher
American Chemical Society (ACS)
Subject
General Materials Science
Link
https://pubs.acs.org/doi/pdf/10.1021/acsami.1c17378
Reference34 articles.
1. Ultralow lattice thermal conductivity and anisotropic thermoelectric performance of AA stacked SnSe bilayer
2. Realization of Both n- and p-Type GeTe Thermoelectrics: Electronic Structure Modulation by AgBiSe2 Alloying
3. Two-channel model for ultralow thermal conductivity of crystalline Tl 3 VSe 4
4. The panoscopic approach to high performance thermoelectrics
5. Low lattice thermal conductivity in Pb5Bi6Se14, Pb3Bi2S6, and PbBi2S4: promising thermoelectric materials in the cannizzarite, lillianite, and galenobismuthite homologous series
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