Simulation of Defects: Interplay of Structural and Electronic Properties; Metropolis Award Presentation

FOCUS · MAR-C49 · ID: 3104348







Presentations

  • ORAL

    Presenters

    • Shuaishuai Yuan

      • McGill University

    Authors

    • Shuaishuai Yuan

      • McGill University
    • Zhanghao Zhouyin

      • McGill University
    • Ding Wang

      • University of Michigan
    • Ding Wang

      • University of Michigan
    • Yuyang Pan

      • University of Michigan
    • Gunther Andersson

      • Flinders University
    • Gregory Metha

      • University of Adelaide
    • Zetian Mi

      • University of Michigan
    • Hong Guo

      • McGill University

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  • ORAL

    Publication: 1. M. H. Rahman et al., "Accelerating defect predictions in semiconductors using graph neural networks," APL Machine Learning, 2, 0166122 (2024)

    Presenters

    • Md Habibur Rahman

      • Purdue University School of Materials Engineering

    Authors

    • Md Habibur Rahman

      • Purdue University School of Materials Engineering
    • Arun Kumar Mannodi Kanakkithodi

      • Purdue University

    View abstract →

  • ORAL

    Presenters

    • Chengcheng Xiao

      • Imperial College London

    Authors

    • Chengcheng Xiao

      • Imperial College London
    • Arash A Mostofi

      • Imperial College London
    • Peter D Haynes

      • Imperial College London

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  • ORAL

    Presenters

    • Shiv Upadhyay

      • University of Washington

    Authors

    • Shiv Upadhyay

      • University of Washington
    • Agam Shayit

      • University of Washington
    • Hang Hu

      • University of Washington
    • Rajat Majumder

      • University of Washington
    • Alexandros Peltekis

      • University of Washington
    • Xiaosong Li

      • University of Washington

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  • ORAL

    Publication: M. E. Turiansky and C. G. Van de Walle, APL Quantum 1, 026114 (2024).

    Presenters

    • Mark E Turiansky

      • University of California, Santa Barbara
      • Materials Department, University of California, Santa Barbara, CA 93106-5050, U.S.A.

    Authors

    • Mark E Turiansky

      • University of California, Santa Barbara
      • Materials Department, University of California, Santa Barbara, CA 93106-5050, U.S.A.
    • Chris G Van de Walle

      • University of California, Santa Barbara
      • Materials Department, University of California, Santa Barbara, CA 93106-5050, U.S.A.

    View abstract →

  • ORAL · Invited

    Publication: - Mosquera-Lois, I. & Kavanagh, S. R. In search of hidden defects. Matter (2021).
    - Mosquera-Lois, I., Kavanagh, S. R., Walsh, A. & Scanlon, D. O. ShakeNBreak: Navigating the defect configurational landscape. Journal of Open Source Software (2022).
    - Kavanagh et al. doped: Python toolkit for robust and repeatable charged defect supercell calculations. Journal of Open Source Software (2024).
    - Mosquera-Lois, I., Kavanagh, S. R., Walsh, A. & Scanlon, D. O. Identifying the ground state structures of point defects in solids. npj Comput Mater (2023).
    - Mosquera-Lois, I., Kavanagh, S. R., Ganose, A. M. & Walsh, A. Machine-learning structural reconstructions for accelerated point defect calculations. npj Comput Mater (2024).
    - Kavanagh, S. R., Identifying Split Vacancies using Foundational Machine Learning Models. In Submission.

    Presenters

    • Seán R Kavanagh

      • Harvard University

    Authors

    • Seán R Kavanagh

      • Harvard University

    View abstract →