474 citations · 2.3k across the 36 of their papers we have counts for
4 papers · 1 filter
A machine learning-based selective sampling procedure for identifying the low energy region in a potential energy surface: a case study on proton conduction in oxides
Kazuaki Toyoura, Daisuke Hirano, Atsuto Seko +5
In this paper, we propose a selective sampling procedure to preferentially evaluate a potential energy surface (PES) in a part of the configuration space governing a physical prope…
Prediction model of band-gap for AX binary compounds by combination of density functional theory calculations and machine learning techniques
Joohwi Lee, Atsuto Seko, Kazuki Shitara +1
Machine learning techniques are applied to make prediction models of the G0W0 band-gaps for 156 AX binary compounds using Kohn-Sham band-gaps and other fundamental information of c…
Discovery of low thermal conductivity compounds with first-principles anharmonic lattice dynamics calculations and Bayesian optimization
Atsuto Seko, Atsushi Togo, Hiroyuki Hayashi +3
Compounds of low lattice thermal conductivity (LTC) are essential for seeking thermoelectric materials with high conversion efficiency. Some strategies have been used to decrease L…
First-principles interatomic potentials for ten elemental metals via compressed sensing
Atsuto Seko, Akira Takahashi, Isao Tanaka
Interatomic potentials have been widely used in atomistic simulations such as molecular dynamics. Recently, frameworks to construct accurate interatomic potentials that combine a s…