Machine Learning, Autonomous Experiments, and Big Data in Polymer Physics II

Presentations

• Olexandr Isayev

  ORAL · Invited

  March 9, 2023, 11:30 AM – March 9, 2023, 12:06 PM

  Presenters

  • Olexandr Isayev

    • Carnegie Mellon University

  Authors

  • Olexandr Isayev

    • Carnegie Mellon University

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• Linking Rheological Properties with Molecular-Scale Features via Molecular Dynamics Simulations and Machine Learning

  ORAL

  March 9, 2023, 12:06 PM – March 9, 2023, 12:18 PM

  Presenters

  • Wenhui Li

    • Indiana University

  Authors

  • Wenhui Li

    • Indiana University

  • JCS Kadupitiya

    • Indiana University

  • Vikram Jadhao

    • Indiana University Bloomington

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• Active Learning Exploration of Thermally Conductive Strained Polymers

  ORAL

  March 9, 2023, 12:18 PM – March 9, 2023, 12:30 PM

  Presenters

  • Renzheng Zhang

    • University of Notre Dame

  Authors

  • Renzheng Zhang

    • University of Notre Dame

  • Jiaxin Xu

    • University of Notre Dame

  • Hanfeng Zhang

    • University of Notre Dame

  • Tengfei Luo

    • University of Notre Dame
    • Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, United States

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• Connecting local structure and transport of small molecules through glassy polymers

  ORAL

  March 9, 2023, 12:30 PM – March 9, 2023, 12:42 PM

  Presenters

  • Samuel J Layding

    • University of Pennsylvania

  Authors

  • Samuel J Layding

    • University of Pennsylvania

  • Robert A Riggleman

    • University of Pennsylvania

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• Deep Learning Approaches for Property Prediction and Inverse Design of Polymers

  ORAL

  March 9, 2023, 12:42 PM – March 9, 2023, 12:54 PM

  Presenters

  • JIHUN AHN

    • Chonnam national university

  Authors

  • JIHUN AHN

    • Chonnam national university

  • Su-Mi Hur

    • Chonnam National University
    • Chonnam Natl Univ

  • Yeojin Choe

    • Chonnam National University

  • Gabriella Pasya Irianti

    • Chonnam National University

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• Developing Universal Machine Learning Model for Predicting Polymer Properties

  ORAL

  March 9, 2023, 12:54 PM – March 9, 2023, 1:06 PM

  Publication: Himanshu and Patra T K, When does deep learning fail and how to tackle it? A critical analysis on polymer?sequence-property surrogate models, https://doi.org/10.48550/arXiv.2210.06622 (2022)

  Presenters

  • Himanshu .

    • Indian Institute of Technology, Madras

  Authors

  • Himanshu .

    • Indian Institute of Technology, Madras

  • Tarak K Patra

    • Indian Institute of Technology Madras

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• Quantifying Pairwise Chemical Similarity of Polymers

  ORAL

  March 9, 2023, 1:06 PM – March 9, 2023, 1:18 PM

  Presenters

  • Jiale Shi

    • Massachusetts Institute of Technology

  Authors

  • Jiale Shi

    • Massachusetts Institute of Technology

  • Nathan J Rebello

    • Massachusetts Institute of Technology

  • Dylan Walsh

    • Massachusetts Institute of Technology

  • Weizhong Zou

    • Massachusetts Institute of Technology

  • Michael E Deagen

    • Massachusetts Institute of Technology

  • Debra J Audus

    • NIST

  • Bradley D Olsen

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology

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• Canonicalizing BigSMILES for Polymer Informatics Using Chemical Intuition and State Machines

  ORAL

  March 9, 2023, 1:18 PM – March 9, 2023, 1:30 PM

  Publication: https://doi.org/10.1021/acspolymersau.2c00009

  Presenters

  • Nathan J Rebello

    • Massachusetts Institute of Technology

  Authors

  • Nathan J Rebello

    • Massachusetts Institute of Technology

  • Tzyy-Shyang Lin

    • Massachusetts Institute of Technology MIT

  • Guang-He Lee

    • Massachusetts Institute of Technology MIT

  • Melody A Morris

    • Massachusetts Institute of Technology MIT

  • Bradley D Olsen

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology

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• CG-BigSMILES: a line notation for coarse-grained polymers

  ORAL

  March 9, 2023, 1:30 PM – March 9, 2023, 1:42 PM

  Presenters

  • Bruno S Leao

    • Massachusetts Institute of Technology and University of Campinas

  Authors

  • Bruno S Leao

    • Massachusetts Institute of Technology and University of Campinas

  • Weizhong Zou

    • Massachusetts Institute of Technology

  • Bradley D Olsen

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology

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• Machine learning of phase diagram based on GPR for the DPD simulation of drug delivery to endothelial cells

  ORAL

  March 9, 2023, 1:42 PM – March 9, 2023, 1:54 PM

  Presenters

  • Joao M Maia

    • Case Western Reserve University

  Authors

  • Saeed Akbari

    • Case Western Reserve University

  • Soumya Ray

    • Case western reserve university

  • Joao M Maia

    • Case Western Reserve University

  • Fei Zhou

    • Lawrence Livermore National lab

  • Xiao Chen

    • Lawrence Livermore National lab

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• Deep Learning Boosted Langevin Field-Theoretic Simulation of Polymers

  ORAL

  March 9, 2023, 1:54 PM – March 9, 2023, 2:06 PM

  Publication: Daeseong Yong and Jaeup U. Kim, Macromolecules, 2022, 55, 6505-6515.

  Presenters

  • Jaeup Kim

    • Ulsan Natl Inst of Sci & Tech
    • UNIST

  Authors

  • Jaeup Kim

    • Ulsan Natl Inst of Sci & Tech
    • UNIST

  • Daeseong Yong

    • Korea Institute for Advanced Study

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• Machine learning strategies for the structure-property relationship of copolymers

  ORAL

  March 9, 2023, 2:06 PM – March 9, 2023, 2:18 PM

  Publication: Tao, Lei, John Byrnes, Vikas Varshney, and Ying Li. "Machine Learning Strategies for the Structure-Property Relationship of Copolymers." iScience, 25, 104585 (2022).

  Presenters

  • Ying Li

    • University of Wisconsin-Madison

  Authors

  • Ying Li

    • University of Wisconsin-Madison

  • Lei Tao

    • University of Connecticut

  • Vikas Varshney

    • Air Force Research Laboratory

  • John Byrnes

    • SRI International

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• Data-driven identification and analysis of the glass transition in polymer melts

  ORAL

  March 9, 2023, 2:18 PM – March 9, 2023, 2:30 PM

  Publication: A. Banerjee, H.-P. Hsu, K. Kremer, O. Kukharenko (manuscript to be submitted)

  Presenters

  • Atreyee Banerjee

    • Max Planck Inst

  Authors

  • Atreyee Banerjee

    • Max Planck Inst

  • Hsiao-Ping Hsu

    • Max Planck Institute for Polymer Research

  • Kurt Kremer

    • Max Planck Institute for Polymer Research

  • Oleksandra Kukharenko

    • Max Planck Institute for Polymer Research

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