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20052020
most citedDistribution of phonon lifetime in Brillouin zone

1.5k citations · 5.8k across the 40 of their papers we have counts for

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cond-mat.mtrl-sci2020★ 4 cited

Phonon structure of titanium under shear deformation along twinning mode

Atsushi Togo, Yuta Inoue, Isao Tanaka

We investigated phonon behavior of hexagonal close packed titanium under homogeneous shear deformation corresponding to the twinning mode using first-principles ca…

cond-mat.mtrl-sci2019★ 19 cited

Vibrational Effects in X-ray Absorption Spectra of 2D Layered Materials

Weine Olovsson, Teruyasu Mizoguchi, Martin Magnuson +4

With the examples of the C -edge in graphite and the B -edge in hexagonal BN, we demonstrate the impact of vibrational coupling and lattice distortions on the X-ray absorptio…

cond-mat.mtrl-sci2018★ 104 cited

: a software library for crystal symmetry search

Atsushi Togo, Kohei Shinohara, Isao Tanaka

A computer algorithm to search symmetries of crystal structures as implemented in the \texttt{spglib} code is described. An iterative algorithm is employed to robustly identify spa…

cond-mat.mtrl-sci2018★ 102 cited

Lattice thermal conductivities of two SiO polymorphs by first-principles calculation and phonon Boltzmann transport equation

Keiyu Mizokami, Atsushi Togo, Isao Tanaka

Lattice thermal conductivities of two SiO polymorphs, i.e., -quartz (low) and -cristobalite (low), were studied using first-principles anharmonic phonon calculation and l…

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★ 22 cited

Linearized machine-learning interatomic potentials for non-magnetic elemental metals: Limitation of pairwise descriptors and trend of predictive power

Akira Takahashi, Atsuto Seko, Isao Tanaka

Machine-learning interatomic potential (MLIP) has been of growing interest as a useful method to describe the energetics of systems of interest. In the present study, we examine th…