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AI Materials Design and Discovery II

FOCUS · C60 · ID: 381699

Presentations

  • A Novel Artificial Intelligence Platform Applied to the Generative Design of Polymer Dielectrics

    ORAL

    –

    Presenters

    • Rishi Gurnani

      Georgia Institute of Technology, Georgia Inst of Tech

    Authors

    • Rishi Gurnani

      Georgia Institute of Technology, Georgia Inst of Tech

    • Deepak Kamal

      Georgia Tech, Georgia Institute of Technology, Georgia Inst of Tech

    • Huan Tran

      School of Materials Science and Engineering, Georgia Institute of Technology, Georgia Inst of Tech

    • Rampi Ramprasad

      Georgia Inst of Tech, Georgia Tech, Georgia Institute of Technology, School of Materials Science and Engineering, Georgia Institute of Technology

    View abstract →

  • Machine learning the molecular dipole moment with atomic partial charges and atomic dipoles

    ORAL

    –

    Presenters

    • Max Veit

      Institute of Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland

    Authors

    • Max Veit

      Institute of Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland

    • David` Wilkins

      Queen's University Belfast, Belfast, UK

    • Yang Yang

      Chemistry and Chemical Biology, Cornell University, Department of Chemistry and Chemical Biology, Cornell University, Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY

    • Robert Distasio

      Chemistry and Chemical Biology, Cornell University, Department of Chemistry and Chemical Biology, Cornell University, Cornell University, Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY

    • Michele Ceriotti

      Ecole polytechnique federale de Lausanne, Ecole Polytechnique Federale de Lausanne, Institute of Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, École Polytechnique Federale de Lausanne, Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne

    View abstract →

  • Machine learning as a solution to the electronic structure problem

    ORAL

    –

    Presenters

    • Beatriz Gonzalez

      School of Materials Science and Engineering, Georgia Institute of Technology

    Authors

    • Beatriz Gonzalez

      School of Materials Science and Engineering, Georgia Institute of Technology

    • Rampi Ramprasad

      Georgia Inst of Tech, Georgia Tech, Georgia Institute of Technology, School of Materials Science and Engineering, Georgia Institute of Technology

    View abstract →

  • Predicting the Absorption Spectra of Azobenzene Dyes

    ORAL

    –

    Presenters

    • Valentin Stanev

      University of Maryland, College Park

    Authors

    • Valentin Stanev

      University of Maryland, College Park

    • Ryota Maehashi

      Research Division, Nissan Motor Co., Ltd

    • YOSHIMI OHTA

      Research Division, Nissan Motor Co., Ltd

    • Ichiro Takeuchi

      University of Maryland, College Park, Department of Materials Science, University of Maryland, Department of Materials Science and Engineering, University of Maryland

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  • Predicting outcomes of catalytic reactions using machine learning

    Invited

    –

    Presenters

    • Trevor Rhone

      Physics, Harvard University, Physics, Rensselaer Polytechnic Institute

    Authors

    • Trevor Rhone

      Physics, Harvard University, Physics, Rensselaer Polytechnic Institute

    • Robert Hoyt

      Physics, Harvard University

    • Christopher O'Connor

      Chemistry and Chemical Biology, Harvard University, Chemistry, Harvard University

    • Matthew M. Montemore

      Physics, Harvard University

    • Challa S.S.R. Kumar

      Chemistry, Harvard University

    • Cynthia Friend

      Chemistry and Chemical Biology, Harvard University, Chemistry, Harvard University

    • Efthimios Kaxiras

      Harvard University, Department of Physics, Harvard University, Physics, Harvard University

    View abstract →

  • Optical engineering of carbon-based nanowires using machine learning

    ORAL

    –

    Presenters

    • Ethan Shapera

      Physics, Graz University of Technology

    Authors

    • Ethan Shapera

      Physics, Graz University of Technology

    • Christoph Heil

      Graz Univ of Technology, Institute of Theoretical and Computational Physics, Graz University of Technology, Physics, Graz University of Technology

    • Philipp Braeuninger-Weimer

      Intellectual Ventures

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  • Machine Learning the Long-Time Dynamics of Spin Ice

    ORAL

    –

    Presenters

    • Kyle Sherman

      Binghamton University

    Authors

    • Kyle Sherman

      Binghamton University

    • Snigdhansu Chatterjee

      University of Minneapolis

    • Rejaul Karim

      University of Minneapolis

    • Kevin Mcilhany

      United States Naval Academy

    • Olivier Pauluis

      New York University

    • Dallas Trinkle

      University of Illinois at Urbana-Champaign

    • Michael Lawler

      Physics, Cornell University, Department of Physics, Applied Physics, and Astronomy, Binghamton University, Cornell University, Binghamton University

    View abstract →

  • Machine-Learning Thermal Properties

    ORAL

    –

    Presenters

    • Dale Gaines II

      Northwestern University

    Authors

    • Dale Gaines II

      Northwestern University

    • Yi Xia

      Northwestern University

    • Christopher Wolverton

      Northwestern University, Materials Science and Engineering, Northwestern University

    View abstract →