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Computational design and discovery of novel materials VII: Machine learning and high throughput computing

ORAL · X43 · ID: 352875

Presentations

  • Genarris 2.0: A Random Structure Generator for Molecular Crystals

    ORAL

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    Presenters

    • Rithwik Tom

      Carnegie Mellon University

    Authors

    • Rithwik Tom

      Carnegie Mellon University

    • Tim C Rose

      Carnegie Mellon University

    • Imanuel Bier

      Carnegie Mellon University

    • Harriet O'Brien

      Carnegie Mellon University

    • Alvaro Vazquez-Mayagoitia

      Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne National Lab, Computational Science Division, Argonne National Laboratory

    • Noa Marom

      Carnegie Mellon University, Carnegie Mellon Univ

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  • Exploring the quantum chemical space of small molecules: QM7-X database

    ORAL

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    Presenters

    • Alvaro Vazquez-Mayagoitia

      Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne National Lab, Computational Science Division, Argonne National Laboratory

    Authors

    • Johannes Hoja

      Physics and Materials Science Reasearch Unit, University of Luxembourg

    • Leonardo Medrano Sandonas

      Physics and Materials Science Reasearch Unit, University of Luxembourg

    • Brian Ernst

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

    • Alvaro Vazquez-Mayagoitia

      Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne National Lab, Computational Science Division, Argonne National Laboratory

    • Robert Distasio

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

    • Alexandre Tkatchenko

      Physics and Materials Science Reasearch Unit, University of Luxembourg, Physics and Materials Science Research Unit, University of Luxembourg, University of Luxembourg, University of Luxembourg Limpertsberg

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  • Predicting <i>h-</i>BCN Geometric Structures Using Clustering and Regression Methods

    ORAL

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    Presenters

    • Sonali Joshi

      Univ of Central Florida

    Authors

    • Sonali Joshi

      Univ of Central Florida

    • Dave Austin

      Univ of Central Florida

    • Duy Le

      Univ of Central Florida, Univeristy of Central Florida, Department of Physics, University of Central Florida, University of Central Florida, Physics and Renewable Energy and Chemical Transformations Cluster, University of Central Florida

    • Talat S. Rahman

      Univ of Central Florida, Univeristy of Central Florida, Department of Physics, University of Central Florida, Orlando, FL 32816, Department of Physics, University of Central Florida, Physics, Univ of Central Florida

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  • Multifidelity Learning and Statistical Analysis of Material Properties

    ORAL

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    Presenters

    • Abhijith Gopakumar

      Northwestern University

    Authors

    • Abhijith Gopakumar

      Northwestern University

    • Mohan Liu

      Northwestern University

    • Ramamurthy Ramprasad

      Georgia Institute of Technology, School of Materials Science and Engineering, Georgia Institute of Technology, Department of Material Science and Technology, Georgia Tech, Materials Science and Engineering, Georgia Institute of Technology

    • Christopher Mark Wolverton

      Northwestern University

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  • Symbolic Regression in Materials Science

    ORAL

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    Presenters

    • Yiqun Wang

      Northwestern University

    Authors

    • Yiqun Wang

      Northwestern University

    • James Rondinelli

      Northwestern University, Department of Materials Science and Engineering, Northwestern University, Materials Science and Engineering, Northwestern University, Deparment of Materials Science and Engineering, Northwestern University

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  • DFT-45B---a fertile soil (data) for your seeds (machine learning algorithms)

    ORAL

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    Presenters

    • Chandramouli Nyshadham

      Kebotix, Inc., Cambridge, MA 02139, USA., Brigham Young Univ - Provo

    Authors

    • Chandramouli Nyshadham

      Kebotix, Inc., Cambridge, MA 02139, USA., Brigham Young Univ - Provo

    • Christoph Kreisbeck

      Kebotix, Inc., Cambridge, MA 02139, USA.

    • Gus Hart

      Brigham Young Univ - Provo, Physics and Astronomy, Brigham Young University, Department of Physics and Astronomy, Brigham Young University

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  • A roadmap for machine learning in alloy modeling

    ORAL

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    Presenters

    • Gus Hart

      Brigham Young Univ - Provo, Physics and Astronomy, Brigham Young University, Department of Physics and Astronomy, Brigham Young University

    Authors

    • Gus Hart

      Brigham Young Univ - Provo, Physics and Astronomy, Brigham Young University, Department of Physics and Astronomy, Brigham Young University

    • Tim Mueller

      John Hopkins University

    • Cormac Toher

      Duke University

    • Stefano Curtarolo

      Duke University

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  • Leveraging machine learning to determine nanoscale structures from theory and experiments

    ORAL

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    Presenters

    • Maria Chan

      Argonne Natl Lab, Center for Nanoscale Materials, Argonne National Laboratory

    Authors

    • Venkata Surya Chaitanya Kolluru

      Argonne Natl Lab

    • Spencer Hills

      Argonne Natl Lab

    • Eric Schwenker

      Argonne Natl Lab

    • Nobuya Watanabe

      Argonne Natl Lab

    • Fatih G Sen

      Argonne Natl Lab

    • Arun Kumar Mannodi Kanakkithodi

      Argonne Natl Lab

    • Michael Sternberg

      Argonne Natl Lab

    • Maria Chan

      Argonne Natl Lab, Center for Nanoscale Materials, Argonne National Laboratory

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  • Machine learning for novel and improved inorganic scintillators

    ORAL

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    Presenters

    • Anjana Talapatra

      Los Alamos National Laboratory

    Authors

    • Anjana Talapatra

      Los Alamos National Laboratory

    • Christopher Stanek

      Los Alamos National Laboratory, Materials Science and Technology Division, Los Alamos National Lab

    • Blas Pedro Uberuaga

      Los Alamos National Laboratory, Materials Science and Technology Division, Los Alamos National Lab

    • Ghanshyam Pilania

      Los Alamos National Laboratory, Materials Science and Technology Division, Los Alamos National Lab

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  • Exploring Information Density in Crystalline and Amorphous Configurations using Deep Neural Networks

    ORAL

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    Presenters

    • Shyam Dwaraknath

      Lawrence Berkeley National Laboratory, Energy Technologies Area, Lawrence Berkeley National Laboratory

    Authors

    • Shyam Dwaraknath

      Lawrence Berkeley National Laboratory, Energy Technologies Area, Lawrence Berkeley National Laboratory

    • Wissam A Saidi

      Mechanical Engineering & Materials Science, University of Pittsburg, Univ of Pittsburgh, Department of Materials Science and Engineering, University of Pittsburgh

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