AI for Materials Discovery II

ORAL · MAR-S37 · ID: 3091519

Presentations

  • ORAL

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    Presenters

    • Alyssa Bragg

      • University of Minnesota

    Authors

    • Alyssa Bragg

      • University of Minnesota

    • Elihu Anouchi

      • Bar Ilan University

    • Liam Thompson

      • University of Minnesota

    • William Cho

      • University of Minnesota

    • Nitzan Yehudit Hirshberg

      • University of Minnesota

    • Brayden Lukaskawcez

      • University of Minnesota

    • Devon Uram

      • University of Minnesota
      • Harvard University

    • Madison Garber

      • University of Minnesota

    • Hayden Binger

      • University of Minnesota

    • Amos Sharoni

      • Bar Ilan University

    • Alexander S McLeod

      • University of Minnesota

    View abstract →

  • ORAL

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    Publication: arXiv:2409.19552

    Presenters

    • Deyu Lu

      • Brookhaven National Laboratory (BNL)

    Authors

    • Deyu Lu

      • Brookhaven National Laboratory (BNL)

    • Shubha Kharel

      • Brookhaven National Laboratory

    • Xiaohui Qu

      • Brookhaven National Laboratory (BNL)

    • Fanchen Meng

      • Brookhaven National Laboratory (BNL)

    • Matthew R Carbone

      • Brookhaven National Lab

    View abstract →

  • ORAL

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    Presenters

    • Yu Zhang

      • University of Florida

    Authors

    • Yu Zhang

      • University of Florida

    • Yong Zhong

      • Stanford University

    • Nhat Huy Mai Tran

      • University of Florida

    • Shuyi Li

      • University of Florida

    • Kyuho Lee

      • Stanford University
      • Massachusetts Institute of Technology

    • Harold Y Hwang

      • Stanford University

    • Zhi-Xun Shen

      • Stanford University

    • Chunjing Jia

      • University of Florida

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  • ORAL

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    Publication: G. Bellini et al., Angew. Chem. Int. Ed., DOI: 10.1002/anie.202417812

    Presenters

    • Lucas Foppa

      • Fritz Haber Institute of the Max Planck Society
      • The NOMAD Laboratory at FHI, Max Planck Society

    Authors

    • Lucas Foppa

      • Fritz Haber Institute of the Max Planck Society
      • The NOMAD Laboratory at FHI, Max Planck Society

    • Matthias Scheffler

      • The NOMAD Laboratory at FHI, Max Planck Society

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  • ORAL

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    Publication: Jia, X., Aziz, A., Hashimoto, Y. et al. Dealing with the big data challenges in AI for thermoelectric materials. Sci. China Mater. 67, 1173–1182 (2024).

    Presenters

    • Yusuke Hashimoto

      • FRIS, Tohoku University

    Authors

    • Yusuke Hashimoto

      • FRIS, Tohoku University

    • Xue Jia

      • AIMR, Tohoku University

    • Hao Li

      • AIMR, Tohoku University

    • Takaaki Tomai

      • FRIS, Tohoku University

    View abstract →

  • ORAL

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    Publication: 1] Xu. X, Wang. W. Multiferroic hexagonal ferrites (h-RFeO3, R = Y, Dy-Lu): a brief experimental review.
    Mod. Phys. Lett. B. 28 (21) (2014).
    [2] H. Yokota, T. Nozue, S. Nakamura, M. Fukunaga, and A. Fuwa, Examination of Ferroelectric and
    Magnetic Properties of Hexagonal ErFeO3 Thin Films, Jpn. J. Appl. Phys. 54, 10NA10 (2015).
    [3] K. K. Sinha, Growth and Characterization of Hexagonal Rare-Earth Ferrites (h-RFeO3; R = Sc, Lu, Yb),
    The University of Nebraska - Lincoln PP - United States -- Nebraska, 2018.
    [4] J. Kasahara, T. Katayama, S. Mo, A. Chikamatsu, Y. Hamasaki, S. Yasui, M. Itoh, and T. Hasegawa,
    Room-Temperature Antiferroelectricity in Multiferroic Hexagonal Rare-Earth Ferrites, ACS Appl. Mater.
    Interfaces 13, 4230 (2021).
    [5] J. M. Costantini, T. Ogawa, A. S. I. Bhuian, and K. Yasuda, Cathodoluminescence Induced in Oxides by
    High-Energy Electrons: Effects of Beam Flux, Electron Energy, and Temperature, J. Lumin. 208, 108
    (2019).
    [6] Liang. H. et al. Application of machine learning to reflection high-energy electron diffraction images
    for automated structural phase mapping. Phys. Rev. Materials. 6, 063805 (2022).
    [7] Wang. A. et al. Benchmarking active learning strategies for materials optimization and discovery.
    Oxford Open Materials Science, 2 (1) (2022).
    [8] Kusne. A. G. et al. On-the-fly closed-loop materials discovery via Bayesian active learning. Nat.
    Commun. 2020 111 11, 1–11 (2020).

    Presenters

    • Haotong Liang

      • University of Maryland College Park

    Authors

    • Haotong Liang

      • University of Maryland College Park

    • Ryan S Paxson

      • University of Maryland
      • University of Maryland, College Park

    • Yunlong Sun

      • The University of Tokyo

    • Aaron Kusne

      • University of Maryland College Park

    • Mikk Lippmaa

      • The University of Tokyo

    • Ichiro Takeuchi

      • University of Maryland College Park
      • University of Maryland
      • University of Maryland, College Park

    View abstract →