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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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Descriptors of intrinsic hydrodynamic thermal transport: screening a phonon database in a machine learning approach

Pol Torres1,2,3, Stephen Wu4, Shenghong Ju1,5

  • 1Department of Mechanical Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, 113-8656, Japan.

Journal of Physics. Condensed Matter : an Institute of Physics Journal
|January 10, 2022
PubMed

Keywords:
first principlesmachine learningphonon hydrodynamicssemiconductorsthermal transportthermoelectricity

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