Nagoya Institute of Technology

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19932026

most citedSmooth PARAFAC Decomposition for Tensor Completion

296 citations

Showing 2019 · cond-mat.mtrl-sciShow all

3 papers · 2 filters

cond-mat.mtrl-sci2019★ 6 cited

Active-learning-based efficient prediction of ab-initio atomic energy: a case study on a Fe random grain boundary model with millions of atoms

Tomoyuki Tamura, Masayuki Karasuyama

We have developed a method that can analyze large random grain boundary (GB) models with the accuracy of density functional theory (DFT) calculations using active learning. It is a…

cond-mat.mtrl-sci2019★ 8 cited

Valence-selective local atomic structures on a YbInCu4 valence transition material by x-ray fluorescence holography

Shinya Hosokawa, Naohisa Happo, Kouichi Hayashi +7

An experimental technique of x-ray fluorescence holography for investigating valence-selective local structures was established by employing the incident x-ray energy at a characte…

cond-mat.mtrl-sci2019★ 6 cited

Hydrogenation, dehydrogenation of $α$ -tetragonal boron and its transition to $δ$ -orthorhombic boron

Naoki Uemura, Koun Shirai, Jens Kunstmann +2

Boron bulk crystals are marked by exceptional structural complexity and unusual related physical phenomena. Recent reports of hydrogenated $α$ -tetragonal and a new $δ$ -orthorhombic…

Active-learning-based efficient prediction of ab-initio atomic energy: a case study on a Fe random grain boundary model with millions of atoms

Valence-selective local atomic structures on a YbInCu4 valence transition material by x-ray fluorescence holography

Hydrogenation, dehydrogenation of α-tetragonal boron and its transition to δ-orthorhombic boron

Hydrogenation, dehydrogenation of $α$ -tetragonal boron and its transition to $δ$ -orthorhombic boron