AI and Materials I

ORAL · A53 · ID: 1067000

Presentations

  • ORAL

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    Publication: Rapid discovery of stable materials by coordinate-free coarse graining, R. E. A. Goodall, A. S. Parackal, F. A. Faber, R. Armiento, and A. A. Lee, Science Advances 8, eabn4117 (2022) https://doi.org/10.1126/sciadv.abn4117.

    Presenters

    • Rickard Armiento

      • Linköping University

    Authors

    • Rickard Armiento

      • Linköping University

    • Abhijith S Parackal

      • Linköping University

    • Rhys Goodall

      • University of Cambridge

    • Felix A Faber

      • University of Cambridge

    • Alpha A Lee

      • University of Cambridge

    View abstract →

  • ORAL

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    Publication: "A semi-supervised deep-learning approach for automatic crystal structure classification"
    Satvik Lolla Et al, Journal of Applied Crystallography 55 (2022)
    https://doi.org/10.1107/S1600576722006069

    Presenters

    • William Ratcliff

      • National Institute of Standards and Technology
      • National Institute of Standards and Technology; University of Maryland

    Authors

    • William Ratcliff

      • National Institute of Standards and Technology
      • National Institute of Standards and Technology; University of Maryland

    • Satvik S Lolla

      • State of Maryland

    • Ichiro Takeuchi

      • University of Maryland, College Park
      • 1. Department of Materials Science and Engineering, University of Maryland, College Park, Maryland

    • Aaron Kusne

      • National Institute of Standards and Technology

    • Haotong Liang

      • University of Maryland, College Park

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  • ORAL

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    Presenters

    • Qunfei Zhou

      • Northwestern University

    Authors

    • Qunfei Zhou

      • Northwestern University

    • Suvo Banik

      • University of Illinois Chicago

    • Srilok Srinivasan

      • Argonne National Laboratory

    • Subramanian K Sankaranarayanan

      • University of Illinois, Argonne National
      • University of Illinois Chicago
      • Argonne National Laboratory

    • Pierre Darancet

      • Argonne National Laboratory

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  • ORAL

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    Publication: A. Ramdas, E. Antoniuk and E. J. Reed, "A Multi-Objective Approach for Rapid Identification of Post-Cu Interconnect Candidates," 2022 International Symposium on VLSI Technology, Systems and Applications (VLSI-TSA), 2022, pp. 1-2, doi: 10.1109/VLSI-TSA54299.2022.9770966.

    Presenters

    • Akash Ramdas

      • Stanford University

    Authors

    • Akash Ramdas

      • Stanford University

    • Evan J Reed

      • Stanford Rsch Lab

    • Felipe H da Jornada

      • Stanford University
      • Stanford

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  • ORAL

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    Presenters

    • Sean D Griesemer

      • Northwestern University

    Authors

    • Sean D Griesemer

      • Northwestern University

    • Ruijie Zhu

      • Northwestern University

    • Koushik Pal

      • Northwestern University

    • Cheol Park

      • Northwestern University

    • Logan Ward

      • Argonne National Laboratory
      • Data Science and Learning Division, Argonne National Lab

    • Christopher M Wolverton

      • Northwestern University

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  • ORAL

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    Publication: Shunshun Liu, Kyungtae Lee, and Prasanna V. Balachandran, "Integrating machine learning with mechanistic models for predicting the yield strength of high entropy alloys", Journal of Applied Physics 132, 105105 (2022) https://doi.org/10.1063/5.0106124

    Presenters

    • Shunshun Liu

      • University of Virginia

    Authors

    • Shunshun Liu

      • University of Virginia

    • Kyungtae Lee

      • University of Virginia

    • Prasanna V Balachandran

      • University of Virginia

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  • ORAL

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    Publication: Journey K. Byland, Yunshu Shi, David S. Parker, Jingtai Zhao, Shaoqing Ding, Rogelio Mata, Haley E. Magliari, Andriy Palasyuk, Sergey L. Bud'ko, Paul C. Canfield, Peter Klavins, and Valentin Taufour, Phys. Rev. Materials 6, 063803 (2022)

    Presenters

    • Journey K Byland

      • University of California, Davis

    Authors

    • Journey K Byland

      • University of California, Davis

    • Yunshu Shi

      • University of California, Davis

    • David S Parker

      • Oak Ridge National Laboratory

    • Journey K Byland

      • University of California, Davis

    • Shaoqing Ding

      • Pennsylvania State University

    • Rogelio Mata

      • University of California, Davis

    • Haley E Magliari

      • University of California, Davis

    • Andriy Palasyuk

      • Ames Laboratory

    • Sergey L Bud'ko

      • Iowa State University
      • Ames National Laboratory
      • Ames Laboratory, U.S. DOE and Department of Physics and Astronomy, Iowa State University
      • Ames Laboratory

    • Paul C Canfield

      • Iowa State University
      • Ames National Laboratory
      • Ames National Laboratory/Iowa State University

    • Peter Klavins

      • University of California, Davis

    • Valentin Taufour

      • Department of Physics, University of California, Davis
      • University of California, Davis

    View abstract →

  • ORAL

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    Publication: Lee, A., Sarker, S., Saal, J.E. et al. Machine learned synthesizability predictions aided by density functional theory. Commun Mater 3, 73 (2022). https://doi.org/10.1038/s43246-022-00295-7

    Presenters

    • Andrew Lee

      • Northwestern University

    Authors

    • Andrew Lee

      • Northwestern University

    • Suchismita Sarker

      • 3. Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, California
      • SLAC National Accelerator Laboratory
      • Stanford Synchrotron Radiation Lightsource

    • James E Saal

      • Citrine Informatics

    • Logan Ward

      • Argonne National Laboratory
      • Data Science and Learning Division, Argonne National Lab

    • Christopher Borg

      • Citrine Informatics

    • Apurva Mehta

      • 3. Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, California
      • SLAC National Accelerator Laboratory
      • Stanford Synchrotron Radiation Lightsource

    • Christopher M Wolverton

      • Northwestern University

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  • ORAL

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    Publication: [1] T. D. Rhone, et al., Sci Rep 10, 15795 (2020).
    [2] Y. Xie, et al., J. Phys. Chem. Lett., 12, 50, 12048–12054 (2021).

    Presenters

    • Trevor David Rhone

      • Rensselaer Polytechnic Institute

    Authors

    • Trevor David Rhone

      • Rensselaer Polytechnic Institute

    • Bethany A Lusch

      • Argonne National Laboratory

    • Misha Salim

      • Argonne National Laboratory

    • Haralambos Gavras

      • Rensselaer Polytechnic Institute

    • Vaishnavi Neema

      • Rensselaer Polytechnic Institute

    • Daniel T Larson

      • Harvard University
      • Department of Physics, Harvard University

    • Efthimios Kaxiras

      • Harvard University

    View abstract →