activity
20012022
most citedTransfer learning for materials informatics using crystal graph convolutional neural network

99 citations · 164 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2022★ 3 cited

Doping effect and Li-ion conduction mechanism of ALi6XO6 (A = K or Rb, and X = pentavalent): A first-principles study

Joohwi Lee, Ryoji Asahi

Recent theoretical and experimental evaluations demonstrated that KLi6TaO6 is a good Li-ion conductor. In this study, the energetics and detailed mechanism of Li-ion migration, rel…

cond-mat.mtrl-sci2020★ 99 cited

Transfer learning for materials informatics using crystal graph convolutional neural network

Joohwi Lee, Ryoji Asahi

For successful applications of machine learning in materials informatics, it is necessary to overcome the inaccuracy of predictions ascribed to insufficient amount of data. In this…

cond-mat.mes-hall2018★ 24 cited

Water Facilitated Electrochemical Reduction of CO2 on Cobalt-Porphyrin Catalysts

Kaito Miyamoto, Ryoji Asahi

Cobalt-porphyrin catalyzed reductive decomposition of CO2 to CO is investigated based on Koper's water facilitated CO2 reduction mechanism using a simple but accurate protocol base…

cond-mat.mtrl-sci2002★ 24 cited

Accurate first principles detailed balance determination of Auger recombination and impact ionization rates in semiconductors

S. Picozzi, R. Asahi, C. B. Geller +1

The technologically important problem of predicting Auger recombination lifetimes in semiconductors is addressed by means of a fully first--principles formalism. The calculations e…

cond-mat.mtrl-sci2001★ 14 cited

Impact ionization in GaAs: a screened exchange density functional approach

S. Picozzi, R. Asahi, C. B. Geller +2

Results are presented of a fully ab-initio calculation of impact ionization rates in GaAs within the density functional theory framework, using a screened-exchange formalism and th…