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Atsuto Seko

As seen in: Physical Review B
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Articles

Predictive power of polynomial machine learning potentials for liquid states in 22 elemental systems

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By Hayato Wakai, Atsuto Seko, Hirosato Izuta, Takayuki Nishiyama
| Physical Review B
The polynomial machine learning potentials (MLPs) described by polynomial rotational invariants have been systematically developed for various systems and used in diverse applications in crystalline states.
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Structure search method for atomic clusters based on the dividing rectangles algorithm

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By Atsuto Seko, Kazuaki Toyoura, Kansei Kanayama
| Physical Review B
The Dividing Rectangles (DIRECT) algorithm is a deterministic optimization method to explore optimal solutions by repeatedly dividing a given hyperrectangle search space into subhyperrectangles. Herein, we propose a structure search method for atomic clusters based on the DIRECT algorithm in combination with a gradient-based local optimizer to enable an efficient structure search in high-dimensional search spaces.
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Fast material search of lithium ion conducting oxides using a recommender system

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By Kota Suzuki, Japan Science, Atsuto Seko, Kosei Ohura
| Royal Society of Chemistry Verified
Fast material search of lithium ion conducting oxides using a recommender system† Kota Suzuki, abc Kosei Ohura,a Atsuto Seko,bdef Yudai Iwamizu,a Guowei Zhao,c Masaaki Hirayama,ac Isao Tanakadefg and Ryoji Kanno*ac Author affiliations * Corresponding authors a Department of Chemical Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, 4259 Nagatsuta, Midori, Yokohama 226-8502, Japan E-mail: kanno@echem.titech.ac.jp b Japan Science and...
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