Machine Learning and Data in Polymer Physics II

Presentations

• Soft, biologically inspired materials for neuromorphic memristors and memcapacitors

  ORAL

  March 17, 2022, 3:00 PM – March 17, 2022, 3:12 PM

  Presenters

  • Charles P Collier

    • Oak Ridge National Lab

  Authors

  • Charles P Collier

    • Oak Ridge National Lab

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• Machine learning approach to identify critical configurations for strong electronic coupling

  ORAL

  March 17, 2022, 3:12 PM – March 17, 2022, 3:24 PM

  Presenters

  • Puja Agarwala

    • Pennsylvania State University

  Authors

  • Puja Agarwala

    • Pennsylvania State University

  • Shane Donaher

    • Penn State University

  • Baskar Ganapathysubramanian

    • Iowa State University

  • Enrique D Gomez

    • Pennsylvania State University
    • Department of Chemical Engineering, Department of Materials Science and Engineering & Materials Research Institute, The Pennsylvania State University
    • Department of Chemical Engineering, Department of Materials Science and Engineering, and Materials Research Institute, The Pennsylvania State University

  • Scott T Milner

    • Pennsylvania State University

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• The use of small angle neutron scattering data to support dark field data analysis in far-field interferometry

  ORAL

  March 17, 2022, 3:24 PM – March 17, 2022, 3:36 PM

  Presenters

  • Caitlyn M Wolf

    • National Institute of Standards and Technology, NIST Center for Neutron Research, Gaithersburg, MD
    • National Institute of Standards and Technology

  Authors

  • Caitlyn M Wolf

    • National Institute of Standards and Technology, NIST Center for Neutron Research, Gaithersburg, MD
    • National Institute of Standards and Technology

  • Youngju Kim

    • National Institute of Standards and Technology, Physical Measurement Laboratory, Gaithersburg, MD; University of Maryland, Dept of Chemistry and Biochemistry, College Park, MD
    • University of Maryland
    • University of Maryland, College Park; National Institute of Standards and Technology

  • Peter Bajcsy

    • National Institute of Standards and Technology, Information Technology Laboratory, Gaithersburg, MD
    • National Institute of Standards and Technology
    • NIST

  • Paul Kienzle

    • National Institute of Standards and Technology, NIST Center for Neutron Research, Gaithersburg, MD
    • NIST
    • National Institute of Standards and Technology

  • Daniel S Hussey

    • National Institute of Standards and Technology, Physical Measurement Laboratory, Gaithersburg, MD
    • National Institute of Standards and Technology

  • Katie M Weigandt

    • National Institute of Standards and Technology, NIST Center for Neutron Research, Gaithersburg, MD
    • National Institute of Standards and Technology

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• High-throughput microrheology of polymer solutions and gels

  ORAL · Invited

  March 17, 2022, 3:36 PM – March 17, 2022, 4:12 PM

  Presenters

  • Matthew E Helgeson

    • University of California, Santa Barbara
    • 1 Department of Chemical Engineering, University of California Santa Barbara
    • Department of Chemical Engineering and Materials Research Laboratory, University of California, Santa Barbara, 93106, United States

  Authors

  • Matthew E Helgeson

    • University of California, Santa Barbara
    • 1 Department of Chemical Engineering, University of California Santa Barbara
    • Department of Chemical Engineering and Materials Research Laboratory, University of California, Santa Barbara, 93106, United States

  • Yimin Luo

    • University of California, Santa Barbara

  • Alexandra V Bayles

    • University of California, Santa Barbara

  • Yuekun Heng

    • 3 Department of Statistics and Probability, University of California Santa Barbara

  • Maneesh K Gupta

    • 4 Air Force Research Laboratory, Wright-Patterson AFB
    • Air Force Research Laboratory, WPAFB

  • Todd M Squires

    • University of California, Santa Barbara

  • Megan T Valentine

    • University of California, Santa Barbara

  • Matthew E Helgeson

    • University of California, Santa Barbara
    • 1 Department of Chemical Engineering, University of California Santa Barbara
    • Department of Chemical Engineering and Materials Research Laboratory, University of California, Santa Barbara, 93106, United States

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• Predicting the Glass Transition of Complex Polymers via Integration of Machine Learning, Theory and Molecular Simulations

  ORAL

  March 17, 2022, 4:12 PM – March 17, 2022, 4:24 PM

  Publication: A. Alesadi et al., "Machine Learning Prediction of Glass Transition Temperature of Conjugated Polymers from Chemical Structure", 2021, in submission.
  A. Karuth et al., "Predicting Glass Transition of Amorphous Polymers by Application of Cheminformatics and Molecular Dynamics Simulations", Polymer, 2021, 218, 123495.

  Presenters

  • Wenjie Xia

    • North Dakota State University

  Authors

  • Wenjie Xia

    • North Dakota State University

  • Amirhadi Alesadi

    • North Dakota State University

  • Zhaofan Li

    • North Dakota State University

  • Zhiqiang Cao

    • University of Southern Mississippi

  • Xiaodan Gu

    • University of Southern Mississippi
    • The University of Southern Mississippi

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• Diverse property-spectrum of flavors of polyolefins: A data analysis study

  ORAL

  March 17, 2022, 4:24 PM – March 17, 2022, 4:36 PM

  Presenters

  • Arunkumar C Rajan

    • Georgia Institute of Technology

  Authors

  • Arunkumar C Rajan

    • Georgia Institute of Technology

  • Oliver B Hvidsten

    • Georgia Institute of Technology

  • Chiho Kim

    • Georgia Institute of Technology

  • Rampi Ramprasad

    • Georgia Institute of Technology

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• Machine Learning Discovery of Multi-Functional Polyimides

  ORAL

  March 17, 2022, 4:36 PM – March 17, 2022, 4:48 PM

  Publication: "Discovery of Multi-Functional Polyimides Through Exhausting Search Using Explainable Machine Learning Techniques", planned paper

  Presenters

  • Lei Tao

    • University of Connecticut

  Authors

  • Lei Tao

    • University of Connecticut

  • Jinlong He

    • University of Connecticut

  • Vikas Varshney

    • Air Force Research Laboratory

  • Ying Li

    • University of Connecticut
    • University of Connecticuit

  • Wei Chen

    • Northwestern University

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• HI vs AI: designing solvent-free brush networks with tissue-like mechanical properties

  ORAL

  March 17, 2022, 4:48 PM – March 17, 2022, 5:00 PM

  Presenters

  • Andrey V Dobrynin

    • University of North Carolina at Chapel Hill
    • UNC Chapel Hill

  Authors

  • Andrey V Dobrynin

    • University of North Carolina at Chapel Hill
    • UNC Chapel Hill

  • Sergei Sheiko

    • University of North Carolina at Chapel Hill

  • Anastasia Stroujkova

    • University of North Carolina at Chapel Hill

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• Illuminating Stress and Failure in Polyethylene with a Neural Network Potential

  ORAL

  March 17, 2022, 5:00 PM – March 17, 2022, 5:12 PM

  Presenters

  • Mark Dellostritto

    • Temple University

  Authors

  • Mark Dellostritto

    • Temple University

  • Simona Percec

    • Temple University

  • Michael Klein

    • Temple University

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• Machine Learning-based Study of Mechanical Properties of Dynamically Crosslinked Polymer Networks

  ORAL

  March 17, 2022, 5:12 PM – March 17, 2022, 5:24 PM

  Presenters

  • Alexandra Filiatraut

    • Miami University

  Authors

  • Mehdi B Zanjani

    • Miami University

  • Alexandra Filiatraut

    • Miami University

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• Application of machine-learned constitutive relations for well-entangled polymer melt flows

  ORAL

  March 17, 2022, 5:24 PM – March 17, 2022, 5:36 PM

  Presenters

  • Souta Miyamoto

    • Kyoto Univ

  Authors

  • Souta Miyamoto

    • Kyoto Univ

  • John J Molina

    • Kyoto University

  • Takashi Taniguchi

    • National Institute for Materials Science, Tsukuba, Japan
    • National Institute for Materials Science
    • NIMS
    • Kyoto Univ
    • International Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Ibaraki 305-0044, Japan.
    • 3 National Institute for Materials Science, Tsukuba, Japan
    • National Institute for Materials Science; 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
    • National Institute of Materials Science, Tsukuba, Japan
    • National Institute of Materials Science
    • Advanced Materials Laboratory, National Institute for Materials Science, 1-1 Namiki, Tsukuba, 305-0044, Japan
    • National Institute for Materials Science (Japan)
    • International Center for Materials Nanoarchitectonics, National Institute for Materials Science
    • International Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044, Japan
    • Kyoto University
    • International Center for Materials Nanoarchitectonics
    • International Center for Materials Nanoarchitectonics, National Institute for Materials Science, Tsukuba, Japan
    • International Center for Materials Nanoarchitectonics, National Institute for Materials Science, Japan
    • International Center for Materials Nanoarchitectonics, National Institute for MaterialsScience, 1-1 Namiki, Tsukuba 305-0044, Japan
    • National Institute for Material Science, Japan
    • National Institute for Material Science
    • National Institute of Material Sciences, Japan
    • NIMS, Tsukuba
    • 2National Institute for Materials Science, Namiki 1-1, Ibaraki 305-0044, Japan.
    • National Institute of Materials Science, Tsukuba, Ibaraki 305-0044, Japan
    • National Institute for Materials Science, Japan
    • International Center for Materials Nanoarchitectonics (WPI-MANA), National Institute for Materials Science, 1-1 Namiki Tsukuba, Ibaraki 305-0044, Japan.
    • NIMS, Japan
    • National Institute for Materials Science (NIMS)
    • NIMS. Japan
    • International Center for Material Nanoarchitectonics, National Institute for Materials Science, Tsukuba, Japan
    • International Center for Material Nanoarchitectonics, National Institute for Materials Science
    • National Institute for Materials Science Tsukuba
    • National Institute for Materials Science, 1-1 Namiki
    • National Institute for Materials Science of Japan
    • National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044, Japan
    • NIMS - National Institute for Material Science, Japan
    • International Center for Materials Nanoarchitectonics, National Institute for Material Science, Tsukuba, Ibaraki 305-0044, Japan.
    • National Institute for Material Science, Tsukuba
    • National Institute for Materials Science, International Center for Materials Nanoarchitectonics
    • International Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
    • National Institute of Material Science
    • National Institute for Materials Science,1-1 Namiki, Tsukuba, 305-0044, Japan

  View abstract →

• Machine Learning Parametrization of a Coarse-grained Epoxy Model at Varying Crosslink Density

  ORAL

  March 17, 2022, 5:36 PM – March 17, 2022, 5:48 PM

  Publication: A. Giuntoli, N. Hansoge, A. van Beek, Z. Meng, W. Chen, S. Keten; Systematic Coarse-graining of Epoxy Resins with Machine Learning-informed Energy Renormalization, npj Computational Materials (2021), 7:168; https://doi.org/10.1038/s41524-021-00634-1

  Presenters

  • Andrea Giuntoli

    • Zernike Institute, University of Groningen

  Authors

  • Andrea Giuntoli

    • Zernike Institute, University of Groningen

  • Nitin K Hansoge

    • Northwestern University

  • Anton van Beek

    • Northwestern University

  • Zhaoxu Meng

    • Clemson University

  • Wei Chen

    • Northwestern University

  • Sinan Keten

    • Northwestern University

  View abstract →

• Identifying Accelerated Ageing Pathways for Cross-Linked Polyethylene Pipes using Principal Component Analysis

  ORAL

  March 17, 2022, 5:48 PM – March 17, 2022, 6:00 PM

  Presenters

  • Michael Grossutti

    • Univ of Guelph
    • University of Guelph

  Authors

  • Michael Grossutti

    • Univ of Guelph
    • University of Guelph

  • Melanie Hiles

    • Univ of Guelph

  • Joseph D'Amico

    • Univ of Guelph

  • William C Wareham

    • Univ of Guelph

  • Benjamin E Morling

    • Univ of Guelph

  • Scott Graham

    • Univ of Guelph

  • John R Dutcher

    • Univ of Guelph
    • University of Guelph

  View abstract →