450 citations · 532 across the 9 of their papers we have counts for
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cond-mat.mtrl-sci2021★ 450 cited
Towards Universal Neural Network Potential for Material Discovery Applicable to Arbitrary Combination of 45 Elements
So Takamoto, Chikashi Shinagawa, Daisuke Motoki +19
Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be p…
cond-mat.mtrl-sci2018★ 2 cited
Machine-learning guided discovery of a high-performance spin-driven thermoelectric material
Yuma Iwasaki, Ichiro Takeuchi, Valentin Stanev +10
Thermoelectric conversion using Seebeck effect for generation of electricity is becoming an indispensable technology for energy harvesting and smart thermal management. Recently, t…