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Rheological Characterization and Theoretical Modeling Establish Molecular Design Rules for Tailored Dynamically Associating Polymers
[Image: see text] Dynamically associating polymers have long been of interest due to their highly tunable viscoelastic behavior. Many applications leverage this tunability to create materials that have specific rheological properties, but designing such materials is an arduous, iterative process. Cu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523779/ https://www.ncbi.nlm.nih.gov/pubmed/36188349 http://dx.doi.org/10.1021/acscentsci.2c00432 |
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author | Cai, Pamela C. Su, Bo Zou, Lei Webber, Matthew J. Heilshorn, Sarah C. Spakowitz, Andrew J. |
author_facet | Cai, Pamela C. Su, Bo Zou, Lei Webber, Matthew J. Heilshorn, Sarah C. Spakowitz, Andrew J. |
author_sort | Cai, Pamela C. |
collection | PubMed |
description | [Image: see text] Dynamically associating polymers have long been of interest due to their highly tunable viscoelastic behavior. Many applications leverage this tunability to create materials that have specific rheological properties, but designing such materials is an arduous, iterative process. Current models for dynamically associating polymers are phenomenological, assuming a structure for the relationship between association kinetics and network relaxation. We present the Brachiation model, a molecular-level theory of a polymer network with dynamic associations that is rooted in experimentally controllable design parameters, replacing the iterative experimental process with a predictive model for how experimental modifications to the polymer will impact rheological behavior. We synthesize hyaluronic acid chains modified with supramolecular host–guest motifs to serve as a prototypical dynamic network exhibiting tunable physical properties through control of polymer concentration and association rates. We use dynamic light scattering microrheology to measure the linear viscoelasticity of these polymers across six decades in frequency and fit our theory parameters to the measured data. The parameters are then altered by a magnitude corresponding to changes made to the experimental parameters and used to obtain new rheological predictions that match the experimental results well, demonstrating the ability for this theory to inform the design process of dynamically associating polymeric materials. |
format | Online Article Text |
id | pubmed-9523779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-95237792022-10-01 Rheological Characterization and Theoretical Modeling Establish Molecular Design Rules for Tailored Dynamically Associating Polymers Cai, Pamela C. Su, Bo Zou, Lei Webber, Matthew J. Heilshorn, Sarah C. Spakowitz, Andrew J. ACS Cent Sci [Image: see text] Dynamically associating polymers have long been of interest due to their highly tunable viscoelastic behavior. Many applications leverage this tunability to create materials that have specific rheological properties, but designing such materials is an arduous, iterative process. Current models for dynamically associating polymers are phenomenological, assuming a structure for the relationship between association kinetics and network relaxation. We present the Brachiation model, a molecular-level theory of a polymer network with dynamic associations that is rooted in experimentally controllable design parameters, replacing the iterative experimental process with a predictive model for how experimental modifications to the polymer will impact rheological behavior. We synthesize hyaluronic acid chains modified with supramolecular host–guest motifs to serve as a prototypical dynamic network exhibiting tunable physical properties through control of polymer concentration and association rates. We use dynamic light scattering microrheology to measure the linear viscoelasticity of these polymers across six decades in frequency and fit our theory parameters to the measured data. The parameters are then altered by a magnitude corresponding to changes made to the experimental parameters and used to obtain new rheological predictions that match the experimental results well, demonstrating the ability for this theory to inform the design process of dynamically associating polymeric materials. American Chemical Society 2022-09-12 2022-09-28 /pmc/articles/PMC9523779/ /pubmed/36188349 http://dx.doi.org/10.1021/acscentsci.2c00432 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Cai, Pamela C. Su, Bo Zou, Lei Webber, Matthew J. Heilshorn, Sarah C. Spakowitz, Andrew J. Rheological Characterization and Theoretical Modeling Establish Molecular Design Rules for Tailored Dynamically Associating Polymers |
title | Rheological Characterization
and Theoretical Modeling
Establish Molecular Design Rules for Tailored Dynamically Associating
Polymers |
title_full | Rheological Characterization
and Theoretical Modeling
Establish Molecular Design Rules for Tailored Dynamically Associating
Polymers |
title_fullStr | Rheological Characterization
and Theoretical Modeling
Establish Molecular Design Rules for Tailored Dynamically Associating
Polymers |
title_full_unstemmed | Rheological Characterization
and Theoretical Modeling
Establish Molecular Design Rules for Tailored Dynamically Associating
Polymers |
title_short | Rheological Characterization
and Theoretical Modeling
Establish Molecular Design Rules for Tailored Dynamically Associating
Polymers |
title_sort | rheological characterization
and theoretical modeling
establish molecular design rules for tailored dynamically associating
polymers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523779/ https://www.ncbi.nlm.nih.gov/pubmed/36188349 http://dx.doi.org/10.1021/acscentsci.2c00432 |
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