マテリアルズ・インフォマティクス計算法の開発と応用

効率的データ構造を利用した結晶構造列挙手法の開発

  1. K. Shinohara, A. Seko, T. Horiyama, M. Ishihata, J. Honda and I. Tanaka, Enumeration of nonequivalent substitutional structures using advanced data structure of binary decision diagram
    J. Chem. Phys. 153, 104109 (2020) [arXiv:2002.12603]

機械学習を利用した結晶構造探索

  1. T. Nishiyama, A. Seko, and I. Tanaka, Application of machine learning potentials to predict grain boundary properties in fcc elemental metals
    Phys. Rev. Materials 4, 123607 (2020) [arXiv:2007.15944]
  2. A. Seko and S. Ishiwata, Prediction of perovskite-related structures in ACuO3-x(A = Ca, Sr, Ba, Sc, Y, La) using density functional theory and Bayesian optimization
    Phys. Rev. B 101, 134101 (2020) (Editors' Suggestion) [arXiv:2001.09312]

推薦システムによる新規無機化合物の予測

  1. A. Seko, H. Hayashi, and I. Tanaka, Compositional descriptor-based recommender system for the materials discovery
    J. Chem. Phys. 148, 241719 (2018). [arXiv:1711.06387]
  2. A. Seko, H. Hayashi, H. Kashima and I. Tanaka, Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds
    Phys. Rev. Materials 2, 013805 (2018). [arXiv:1710.00659]

元素・構造特徴量に基づいた一般的化合物特徴量の生成手法

  1. A. Seko, H. Hayashi, K. Nakayama, A. Takahashi, I. Tanaka, Representation of compounds for machine-learning prediction of physical properties
    Phys. Rev. B 95, 144110 (2017).

バーチャルスクリーニングによる低格子熱伝導率材料の探索

  1. A. Seko, A. Togo, H. Hayashi, K. Tsuda, L. Chaput and I. Tanaka, Prediction of low-thermal-conductivity compounds with first-principles anharmonic lattice-dynamics calculations and Bayesian optimization
    Phys. Rev. Lett. 115, 205901 (2015).

機械学習による融点予測モデルの構築

  1. A. Seko, T. Maekawa, K. Tsuda and I. Tanaka, Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single and binary component solids
    Phys. Rev. B 89, 054303 (2014). [arXiv:1310.1546]

リチウム二次電池のための固体電解質のイオン伝導度予測

  1. K. Fujimura, A. Seko, Y. Koyama, A. Kuwabara, I. Kishida, K. Shitara, C. A. J. Fisher, H. Moriwake and I. Tanaka, Accelerated materials design of lithium superionic conductors based on first-principles calculations and machine learning algorithms
    Adv. Energy Mater. 3, 980-985 (2013).