Evidence map›Paper›PMID 36188349›Full record

ArticleACS central science2022

Rheological Characterization and Theoretical Modeling Establish Molecular Design Rules for Tailored Dynamically Associating Polymers.

Pamela C Cai, Bo Su, Lei Zou, Matthew J Webber, Sarah C Heilshorn, Andrew J Spakowitz

Abstract read
In one paragraph

Article in ACS central science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Pamela C CaiDepartment of Chemical Engineering, Stanford University, Stanford, California 94305, United States.
Bo SuDepartment of Chemical & Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Lei ZouDepartment of Chemical & Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Matthew J WebberDepartment of Chemical & Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.ORCID https://orcid.org/0000-0003-3111-6228
Sarah C HeilshornDepartment of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States.ORCID https://orcid.org/0000-0002-9801-6304
Andrew J SpakowitzDepartment of Chemical Engineering, Stanford University, Stanford, California 94305, United States.ORCID https://orcid.org/0000-0002-0585-1942

Funding

Non-Covalent Molecular Recognition for Drug Targeting in the BodyR35GM137987 · NIGMS · UNIVERSITY OF NOTRE DAME · PI WEBBER, MATTHEW · 2020 to 2024
$2.2M
NIGMS NIH HHS R35 GM137987
6 · The paper itself

Abstract

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.

Identifiers

PMID36188349
PMCPMC9523779

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.