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2D Magnetism Based Upon Asymmetric Coordination Complexes - Screening via First-Principles Structure Prediction

Publicly Offered Research

Project AreaCoordination Asymmetry: Design of Asymmetric Coordination Sphere and Anisotropic Assembly for the Creation of Functional Molecules
Project/Area Number 19H04574
Research Category

Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

Allocation TypeSingle-year Grants
Review Section Science and Engineering
Research InstitutionKyoto University

Principal Investigator

Packwood Daniel  京都大学, 高等研究院, 講師 (40640884)

Project Period (FY) 2019-04-01 – 2021-03-31
Project Status Completed (Fiscal Year 2020)
Budget Amount *help
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2020: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2019: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Keywords分子自己組織化 / 表面 / 構造予測 / 密度汎関数理論 / 進化アルゴリズム / 機械学習 / 磁気性 / 分子薄膜 / 第一原理構造予測 / 非対称金属錯体 / 材料探索・バーチャルスクリーニング / 二次元磁性 / 第一原理計算 / 二次元磁気性 / ベイズ機械学習
Outline of Research at the Start

本研究では、非対称金属錯体の自己組織化で形成した単一層を対象とし、第一原理から単一層の構造を予測できる手法の開発を目指す。また、コードによるバーチャルスクリーニングを行い、長距離磁気秩序を示す単一層を形成できる金属錯体を探索する。この探索を行うために、不対電子間の相互作用(強磁性相互作用、反強磁性相互作用)が電子間距離に依存することを活かす。具体的に、金属錯体の非対称性による単一層中の不対電子間距離に変異を導入し、新たなスピン配置を引き起こす。そして、非対称性を維持しながら金属錯体間相互作用を最適化して、長距離の強磁性・反強磁性を同時に示す単一層を形成できる金属錯体を絞り込む。

Outline of Annual Research Achievements

We created a new simulation method for self-assembly of asymmetric metal complexes on metallic surfaces, and used it to predict two-dimensional molecular assemblies with novel magnetic properties. During the research period, we created a new algorithm called Evolution Under Fire (EUF) which can optimize the configuration of metal complex molecules adsorbed to a surface. It was confirmed that EUF is about 10 - 20 % more successful than ordinary genetic algorithms for predicting self-assembled structures. With EUF, we succeed to predict the assembly of symmetric phthalocyanine complexes on Cu(111) surfaces and confirmed the ferromagnetic coupling property within the assembly. Simulations for asymmetric complexes will be completed within the next few months.

Research Progress Status

令和2年度が最終年度であるため、記入しない。

Strategy for Future Research Activity

令和2年度が最終年度であるため、記入しない。

Report

(2 results)
  • 2020 Annual Research Report
  • 2019 Annual Research Report
  • Research Products

    (6 results)

All 2020 2019 Other

All Journal Article (3 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 2 results) Presentation (2 results) (of which Invited: 2 results) Remarks (1 results)

  • [Journal Article] Disorder-robust bands from anisotropic orbitals in a coordination polymer semiconductor2020

    • Author(s)
      Daniel M. Packwood and Pichaya Pattanasattayavong
    • Journal Title

      Journal of Physics Condensed Matter

      Volume: 32 Issue: 27 Pages: 275701-275701

    • DOI

      10.1088/1361-648x/ab7d65

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Heavy Metal Effects on the Photovoltaic Properties of Metallocorroles in Dye-Sensitized Solar Cells2020

    • Author(s)
      Tomohiro Higashino, Yuma Kurumisawa, Abraham B. Alemayehu, Rune F. Einrem, Debashis Sahu, Daniel Packwood, Kosaku Kato, Akira Yamakata, Abhik Ghosh and Hiroshi Imahori
    • Journal Title

      ACS Applied Energy Materials

      Volume: 3 Issue: 12 Pages: 12460-12467

    • DOI

      10.1021/acsaem.0c02427

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Kernelized machine learning for a molecular self-assembly model2019

    • Author(s)
      Daniel M. Packwood
    • Journal Title

      Bulletin of the Japan Society for Coordination Chemistry

      Volume: 74 Pages: 62-62

    • Related Report
      2019 Annual Research Report
  • [Presentation] Structure prediction and control for functional surface materials2020

    • Author(s)
      Daniel M. Packwood
    • Organizer
      Applied Math for Energy: Future Directions (workshop at I2CNER, Kyushu University)
    • Related Report
      2020 Annual Research Report 2019 Annual Research Report
    • Invited
  • [Presentation] 表面上の分子集合体のための機械学習2020

    • Author(s)
      Daniel M. Packwood
    • Organizer
      近畿化学協会コンピューター化学部会 第107回例会
    • Related Report
      2020 Annual Research Report 2019 Annual Research Report
    • Invited
  • [Remarks] Research group website

    • URL

      http://www.packwood.icems.kyoto-u.ac.jp/

    • Related Report
      2019 Annual Research Report

URL: 

Published: 2019-04-18   Modified: 2021-12-27  

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