Dillon Medal Symposium
FOCUS · K17 · ID: 47469
Presentations
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John H. Dillon Medal Award (2022): Toward quantitative modeling of polyelectrolyte complexation
ORAL · Invited
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Presenters
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Jian Qin
Stanford University
Authors
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Jian Qin
Stanford University
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Modeling the microemulsion channel in ternary mixtures of AB diblock copolymer with A and B homopolymers
ORAL
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Presenters
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David C Morse
University of Minnesota
Authors
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David C Morse
University of Minnesota
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Mridul Yadav
University of Minnesota
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Aging Resistant Toughness in Poly(lactide)
ORAL
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Presenters
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Frank S Bates
University of Minnesota, University of Minnesota - Twin Cities
Authors
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Charles McCutcheon
University of Minnesota
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Christopher J Ellison
University of Minnesota
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Boran Zhao
University of Minnesota
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Frank S Bates
University of Minnesota, University of Minnesota - Twin Cities
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Kailong Jin
Arizona State University
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Measuring the packing length in polymer simulations
ORAL
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Presenters
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Scott T Milner
Pennsylvania State University
Authors
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Scott T Milner
Pennsylvania State University
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Emerging AI-enhanced approaches for polymer design
ORAL
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Presenters
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Juan De Pablo
University of Chicago, Pritzker School of Molecular Engineering, University of Chicago
Authors
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Juan De Pablo
University of Chicago, Pritzker School of Molecular Engineering, University of Chicago
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Polymer electrolytes in heterogenous media
ORAL
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Presenters
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Monica Olvera De La Cruz
Northwestern University, Department of Physics and Astronomy, Department of Materials Science and Engineering, Department of Chemistry, Northwestern University
Authors
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Monica Olvera De La Cruz
Northwestern University, Department of Physics and Astronomy, Department of Materials Science and Engineering, Department of Chemistry, Northwestern University
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Trung Dac D Nguyen
Northwestern University
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Felipe Jimenez
Northwestern University
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Increased Donnan Exclusion at High Salt Concentrations
ORAL
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Publication: K.W. Gao, X. Yu, R. Darling, J. Newman, N. Balsara. "Increased Donnan exclusion at high salt concentrations," Soft Matter. 2021. Submitted.
Presenters
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Nitash P Balsara
University of California, Berkeley
Authors
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Kevin W Gao
University of California, Berkeley
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Xiaopeng Yu
University of California, Berkeley
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Nitash P Balsara
University of California, Berkeley
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Enhancing ion transport in charged block copolymers by stabilizing low symmetry morphology
ORAL
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Presenters
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Moon Park
Pohang Univ of Sci & Tech
Authors
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Moon Park
Pohang Univ of Sci & Tech
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Coarse-Grained Modeling of Ion Mobility and Conductivity in Block Copolymers
ORAL
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Presenters
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Lisa M Hall
Ohio State University, Ohio State Univ - Columbus
Authors
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Lisa M Hall
Ohio State University, Ohio State Univ - Columbus
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Mengdi Fan
Ohio State University, Ohio State Univ - Columbus
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Yuanhao Zhang
Ohio State University
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Quantifying the effects of intra-domain structure and dynamics on ion transport in nanostructured block polymer electrolytes
ORAL
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Presenters
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Thomas H Epps
University of Delaware
Authors
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Thomas H Epps
University of Delaware
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Modeling the Phase Behavior of Complex Coacervates formed from Polyelectrolytes and Surfactant Micelles
ORAL
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Presenters
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Charles E Sing
University of Illinois at Urbana-Champaign
Authors
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Charles E Sing
University of Illinois at Urbana-Champaign
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Jason Madinya
University of Illinois at Urbana-Champai
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Polyelectrolyte Complex Materials
ORAL
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Presenters
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Sarah L Perry
University of Massachusetts Amherst
Authors
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Sarah L Perry
University of Massachusetts Amherst
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A new computational method CREASE to analyze and interpret small angle scattering profiles from polymers and soft materials
ORAL
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Publication: 1. Beltran-Villegas, D. J.; Wessels, M. G.; Lee, J. Y.; Song, Y.; Wooley, K. L.; Pochan, D. J.; Jayaraman, A. Computational Reverse-Engineering Analysis for Scattering Experiments on Amphiphilic Block Polymer Solutions. J. Am. Chem. Soc. 2019, 141, 14916−14930.<br>2. Wessels, M. G.; Jayaraman, A. Computational Reverse-Engineering Analysis of Scattering Experiments (CREASE) on Amphiphilic Block Polymer Solutions: Cylindrical and Fibrillar Assembly. Macromolecules 2021, 54, 783-796. <br>3. Wessels, M. G.; Jayaraman, A. Machine Learning Enhanced Computational Reverse Engineering Analysis for Scattering Experiments (CREASE) to Determine Structures in Amphiphilic Polymer Solutions. ACS Polymers Au 2021, https://doi.org/10.1021/acspolymersau.1c00015<br>4. Ye, Z.; Wu, Z.; Jayaraman, A. Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) on Vesicles Assembled from Amphiphilic Macromolecular Solutions. JACS Au 2021, Advanced Article. https://doi.org/10.1021/jacsau.1c00305<br>
Presenters
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Arthi Jayaraman
University of Delaware
Authors
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Arthi Jayaraman
University of Delaware
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