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AI and Materials I

ORAL · A53 · ID: 1067000

Presentations

  • Screening the unexplored crystal prototype space and inverting XRD patterns with the WREN machine-learning model

    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 →

  • Semi and Self Supervised approaches to Space Group and Bravais Lattice Determination

    ORAL

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    Publication: "A semi-supervised deep-learning approach for automatic crystal structure classification"<br>Satvik Lolla Et al, Journal of Applied Crystallography 55 (2022)<br>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

    View abstract →

  • Machine Learning the Electronic Structure of Phase Change Materials

    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

    View abstract →

  • Using chemical-formula-based generalizable models to expand the search space for viable interconnect materials

    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

    View abstract →

  • How to Search for Stable Inorganic Compounds More Efficiently

    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

    View abstract →

  • Integrating Machine Learning with Mechanistic Models for Predicting the Yield Strength of High Entropy Alloys

    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

    View abstract →

  • Statistics on the magnetism of cobalt compounds: A database approach to discovering new Co-based ferromagnets

    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 →

  • Machine Learned Synthesizability Predictions Aided by Density Functional Theory

    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

    View abstract →

  • Artificial intelligence guided materials discovery of van der Waals magnets

    ORAL

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    Publication: [1] T. D. Rhone, et al., Sci Rep 10, 15795 (2020). <br>[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 →