activity
20062025
most citedDiscovery of low thermal conductivity compounds with first-principles anharmonic lattice dynamics calculations and Bayesian optimization

474 citations · 961 across the 9 of their papers we have counts for

collaborators

9 papers

physics.soc-ph2025

AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions

Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price +65

Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, p…

cond-mat.mtrl-sci2022★ 11 cited

LO-mode phonon of KCl and NaCl at 300 K by inelastic X ray scattering measurements and first principles calculations

Atsushi Togo, Hiroyuki Hayashi, Terumasa Tadano +2

Longitudinal-optical (LO) mode phonon branches of KCl and NaCl were measured using inelastic X-ray scattering (IXS) at 300 K and calculated by the first-principles phonon calculati…

cond-mat.mtrl-sci2017★ 47 cited

Compositional descriptor-based recommender system accelerating the materials discovery

Atsuto Seko, Hiroyuki Hayashi, Isao Tanaka

Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies t…

cond-mat.mtrl-sci2017★ 58 cited

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

Atsuto Seko, Hiroyuki Hayashi, Hisashi Kashima +1

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine-learning is a unique ap…

cond-mat.mtrl-sci2017★ 34 cited

Thermoelectric phase diagram of the SrTiO3-SrNbO3 solid solution system

Yuqiao Zhang, Bin Feng, Hiroyuki Hayashi +4

Thermoelectric energy conversion - the exploitation of the Seebeck effect to convert waste heat into electricity - has attracted an increasing amount of research attention for ener…

cond-mat.mtrl-sci2016★ 318 cited

Representation of compounds for machine-learning prediction of physical properties

Atsuto Seko, Hiroyuki Hayashi, Keita Nakayama +2

The representations of a compound, called "descriptors" or "features", play an essential role in constructing a machine-learning model of its physical properties. In this study, we…

cond-mat.mtrl-sci2015★ 474 cited

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…

cond-mat.mtrl-sci2015★ 2 cited

Choice of basis vectors for conventional unit cells revisited

Yoyo Hinuma, Atsushi Togo, Hiroyuki Hayashi +1

Band diagrams often pass through special -vector points with "irrational" fractional coordinates such as some Brillouin zone vertices and centers of edges. Use of "stan…

cond-mat.mtrl-sci2006★ 17 cited

Awaking of ferromagnetism in GaMnN through control of Mn valence

Saki Sonoda, Isao Tanaka, Fumiyasu Oba +10

Room temperature ferromagnetism of GaMnN thin films is awaked by a mild hydrogenation treatment of samples synthesized by molecular beam epitaxy. Local environment of Mn atoms is m…