190 citations · 749 across the 19 of their papers we have counts for
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cond-mat.mtrl-sci2019★ 53 cited
Exploring diamond-like lattice thermal conductivity crystals via feature-based transfer learning
Shenghong Ju, Ryo Yoshida, Chang Liu +3
Ultrahigh lattice thermal conductivity materials hold great importance since they play a critical role in the thermal management of electronic and optical devices. Models using mac…
physics.app-ph2019★ 190 cited
Expanding the horizon of automated metamaterials discovery via quantum annealing
Koki Kitai, Jiang Guo, Shenghong Ju +4
Complexity of materials designed by machine learning is currently limited by the inefficiency of classical computers. We show how quantum annealing can be incorporated into automat…
physics.app-ph2019★ 64 cited
Materials Informatics for Heat Transfer: Recent Progresses and Perspectives
Shenghong Ju, Junichiro Shiomi
With the advances in materials and integration of electronics and thermoelectrics, the demand for novel crystalline materials with ultimate high/low thermal conductivity is increas…