Efficient construction of phase diagram by machine learning

DOI Web Site
  • TAMURA Ryo
    International Center for Materials Nanoarchitectonics, National Institute for Materials Science Graduate School of Frontier Sciences, The University of Tokyo
  • TERAYAMA Kei
    Graduate School of Medical Life Science, Yokohama City University
  • KATSUBE Ryoji
    Department of Materials Science and Engineering, Kyoto University
  • NOSE Yoshitaro
    Department of Materials Science and Engineering, Kyoto University

Bibliographic Information

Other Title
  • 機械学習による相図作成の効率化
  • キカイ ガクシュウ ニ ヨル ソウズ サクセイ ノ コウリツカ

Search this article

Abstract

<p>We developed a method called PDC (Phase Diagram Construction) that constructs a phase diagram using machine learning. In this method, based on uncertainty sampling, the most uncertain point in the phase diagram is selected as a candidate for the next experiments/simulations. Then, using experiments/simulations, the phase at the selected point is identified. Uncertainty sampling is performed again on the increased experimental data to select next candidates. By repeating this process, it is possible to draw a phase diagram quickly. By using PDC, an uninvestigated phase diagram for the deposition of Zn-Sn-P films by molecular beam epitaxy is constructed. In addition, we have released an application software for the phase diagram construction; the software can be executed on a Windows computer without any special settings.</p>

Journal

  • Oyo Buturi

    Oyo Buturi 91 (2), 96-100, 2022-02-01

    The Japan Society of Applied Physics

Details 詳細情報について

Report a problem

Back to top