Machine Learning and Advanced Computational Methods in Polymer Physics

Presentations

• DPOLY Placeholder

  COFFEE_KLATCH · Invited

  March 5, 2024, 8:00 AM – March 5, 2024, 8:36 AM

  View abstract →

• Bicontinuous microemulsion in binary blends of complimentary diblock copolymers

  ORAL

  March 5, 2024, 8:36 AM – March 5, 2024, 8:48 AM

  Publication: J.D. Willis and M.W. Matsen, "Bicontinuous microemulsion in binary blends of complimentary diblock copolymers", J. Chem. Phys. (soon to be submitted).

  Presenters

  • James D Willis

    • University of Waterloo

  Authors

  • James D Willis

    • University of Waterloo

  • Mark W Matsen

    • University of Waterloo

  View abstract →

• Complex Solutions of Self-Consistent Field Theory

  ORAL

  March 5, 2024, 8:48 AM – March 5, 2024, 9:00 AM

  Presenters

  • Jaeup Kim

    • UNIST

  Authors

  • Jaeup Kim

    • UNIST

  • Wonjun Kang

    • UNIST

  • Daeseong Yong

    • Korea Institute for Advanced Study

  View abstract →

• Preserving Positivity: Developments in Density-Explicit Field-Theoretic Simulations

  ORAL

  March 5, 2024, 9:00 AM – March 5, 2024, 9:12 AM

  Presenters

  • Timothy Quah

    • University of California, Santa Barbara

  Authors

  • Timothy Quah

    • University of California, Santa Barbara

  • Kevin Shen

    • University of California, Santa Barbara

  • Kris T Delaney

    • University of California, Santa Barbara

  • Glenn H Fredrickson

    • University of California, Santa Barbara

  View abstract →

• Bridging Particle and Field-Theoretic Simulations of Polymers with Deep Learning

  ORAL

  March 5, 2024, 9:12 AM – March 5, 2024, 9:24 AM

  Presenters

  • Dongqi Zhao

    • University of Pennsylvania

  Authors

  • Dongqi Zhao

    • University of Pennsylvania

  • Robert A Riggleman

    • University of Pennsylvania

  View abstract →

• Molecular Dynamics Simulation of the Self-Assembly of Rigid Sphere-Rod Amphiphilic Marcomolecules into Onion-Like Assemblies

  ORAL

  March 5, 2024, 9:24 AM – March 5, 2024, 9:36 AM

  Presenters

  • Farzad Toiserkani

    • University of Akron

  Authors

  • Farzad Toiserkani

    • University of Akron

  • Yifan Zhou

    • the University of Akron

  • Tianbo Liu

    • University of Akron

  • Mesfin Tsige

    • The University of Akron

  View abstract →

• Coil-helix Block Copolymers Can Exhibit Divergent Thermodynamics

  ORAL

  March 5, 2024, 9:36 AM – March 5, 2024, 9:48 AM

  Publication: https://doi.org/10.1021/acs.jctc.3c00680

  Presenters

  • Poornima Padmanabhan

    • RIT
    • Rochester Institute of Technology

  Authors

  • Michael J Grant

    • Rochester Institute of Technology

  • Brennan J Fingler

    • Rochester Institute of Technology

  • Natalie Buchanan

    • Rochester Institute of Technology

  • Poornima Padmanabhan

    • RIT
    • Rochester Institute of Technology

  View abstract →

• Chemical Potential of a Flexible Polymer Liquid in a Coarse-grained Representation

  ORAL

  March 5, 2024, 9:48 AM – March 5, 2024, 10:00 AM

  Publication: "Chemical Potential of a Flexible Polymer Liquid in a Coarse-Grained Representation", M. Dinpajooh, J. Millis, J. P. Donley, and M. G. Guenza, The Journal of Physical Chemistry, submitted.

  Presenters

  • James Donley

    • University of Oregon

  Authors

  • James Donley

    • University of Oregon

  • Mohammadhasan Dinpajooh

    • Pacific Northwest National Laboratory

  • Jonathan Millis

    • University of Oregon

  • Marina G Guenza

    • University of Oregon

  View abstract →

• MolSets: Molecular graph deep sets model for mixture property modeling

  ORAL

  March 5, 2024, 10:00 AM – March 5, 2024, 10:12 AM

  Presenters

  • Hengrui Zhang

    • Northwestern University

  Authors

  • Hengrui Zhang

    • Northwestern University

  • James M Rondinelli

    • Northwestern University

  • Wei Chen

    • Northwestern University

  View abstract →

• Quantifying Similarity between Polymer Ensembles

  ORAL

  March 5, 2024, 10:12 AM – March 5, 2024, 10:24 AM

  Presenters

  • Debra J Audus

    • NIST

  Authors

  • Debra J Audus

    • NIST

  • Jiale Shi

    • Massachusetts Institute of Technology

  • Dylan Walsh

    • Massachusetts Institute of Technology

  • Weizhong Zou

    • Massachusetts Institute of Technology

  • Nathan J Rebello

    • Massachusetts Institute of Technology

  • Michael E Deagen

    • Rensselaer Polytechnic Institute

  • Katharina Fransen

    • Massachusetts Institute of Technology

  • Xian Gao

    • University of Notre Dame

  • Bradley D Olsen

    • Massachusetts Institute of Technology MI
    • Massachusetts Institute of Technology

  View abstract →

• Identifying promising anions for superionic single-ion conducting polymer electrolytes using data-science approaches

  ORAL

  March 5, 2024, 10:24 AM – March 5, 2024, 10:36 AM

  Presenters

  • Qinyu Zhu

    • Oak Ridge National Laboratory

  Authors

  • Qinyu Zhu

    • Oak Ridge National Laboratory

  • Catalin Gainaru

    • Oak Ridge National Laboratory

  • Kenneth S Schweizer

    • University of Illinois at Urbana Champaign
    • University of Illinois at Urbana-Champaign
    • University of Illinois at Urbana-Champai
    • University of Illinois Urbana-Champaign

  • Alexei P Sokolov

    • University of Tennessee

  • Yifan Liu

    • Oak Ridge National Laboratory

  • Valentino R Cooper

    • Oak Ridge National Lab

  • Rajeev Kumar

    • Oak Ridge National Lab
    • Oak Ridge National Laboratory

  View abstract →

• Predicting Nanoparticle Dispersion State in Polymer Films via Machine Learning

  ORAL

  March 5, 2024, 10:36 AM – March 5, 2024, 10:48 AM

  Presenters

  • Willliam C Marshall

    • Columbia University

  Authors

  • Willliam C Marshall

    • Columbia University

  • Sanat K Kumar

    • Columbia University

  View abstract →

• Nucleation patterns of polymer crystals analyzed by machine learning models

  ORAL

  March 5, 2024, 10:48 AM – March 5, 2024, 11:00 AM

  Publication: https://zenodo.org/records/8383061
  Manuscript title: Nucleation patterns of polymer crystals analyzed by machine learning models

  Presenters

  • Atmika Bhardwaj

    • Leibniz-Institut für Polymerforschung Dresden e. V.

  Authors

  • Atmika Bhardwaj

    • Leibniz-Institut für Polymerforschung Dresden e. V.

  • Jens-Uwe Sommer

    • Leibniz-Institut für Polymerforschung Dresden e. V.

  • Marco Werner

    • Leibniz-Institut für Polymerforschung Dresden e. V.

  View abstract →