Electrons, Phonons, Electron-Phonon Scattering, and Phononics V

FOCUS · K58 · ID: 2155700

Presentations

  • ORAL

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    Presenters

    • Dmitri Kilin

      • North Dakota State University

    Authors

    • Dmitri Kilin

      • North Dakota State University

    • KAMRUN NAHAR KEYA

      • Iowa State University

    • Yulun Han

      • North Dakota State University

    • Wenfang Sun

      • University of Alabama, Tuscaloosa
      • University of Alabama

    • Wenjie Xia

      • Iowa State University

    • Bakhtiyor Rasulev

      • North Dakota State University

    • Svetlana Kilina

      • North Dakota State University

    View abstract →

  • ORAL

    –

    Publication: [1] Alghofaili, Yousef A., et al. "Accelerating Materials Discovery through Machine Learning: Predicting
    Crystallographic Symmetry Groups." The Journal of Physical Chemistry C 127.33 (2023): 16645-16653.

    [2] Alsaui, Abdulmohsen, et al. "Highly accurate machine learning prediction of crystal point groups for
    ternary materials from chemical formula." Scientific Reports 12.1 (2022): 1577.

    [3] Alsaui, Abdulmohsen A., et al. "Resampling techniques for materials informatics: limitations in crystal
    point groups classification." Journal of Chemical Information and Modeling 62.15 (2022): 3514-3523.

    [4] Baloch, Ahmer AB, et al. "Extending Shannon's ionic radii database using machine learning." Physical
    Review Materials 5.4 (2021): 043804.

    Presenters

    • Mohammed Alghadeer

      • University of California, Berkeley
      • University of Oxford

    Authors

    • Mohammed Alghadeer

      • University of California, Berkeley
      • University of Oxford

    • Yousef A Alghofaili

      • Xpedite Information Technology

    • Abdulmohsen A Alsaui

      • King Fahd Univ KFUPM

    • Saad M Alqahtani

      • Jubail Industrial College

    • Fahhad H Alharbi

      • King Fahd Univ KFUPM
      • Department of Electrical Engineering, King Fahd University of Petroleum and Minerals

    View abstract →