Evidence map›Paper›PMID 37619531›Full record

ArticleACS macro letters2023

Preferential Mechanochemical Activation of Short Chains in Bidisperse Triblock Elastomers.

Zijian Huo, Kasey F Watkins, Brandon C Jeong, Antonia Statt, Jennifer E Laaser

Abstract read
In one paragraph

Article in ACS macro letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

5 authors.

Zijian HuoDepartment of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States.
Kasey F WatkinsDepartment of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States.
Brandon C JeongDepartment of Chemical and Biomolecular Engineering, University of Illinois, Urbana-Champaign, Illinois 61801, United States.
Antonia StattDepartment of Chemical and Biomolecular Engineering, University of Illinois, Urbana-Champaign, Illinois 61801, United States.ORCID 0000-0002-6120-5072
Jennifer E LaaserDepartment of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States.ORCID 0000-0002-0551-9659

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymer mechanochemistry offers attractive opportunities for using macroscopic forces to drive molecular-scale chemical transformations, but achieving efficient activation in bulk polymeric materials has remained challenging. Understanding how the structure and topology of polymer networks impact molecular-scale force distributions is critical for addressing this problem. Here we show that in block copolymer elastomers the molecular-scale force distributions and mechanochemical activation yields are strongly impacted by the molecular weight distribution of the polymers. We prepare bidisperse triblock copolymer elastomers with spiropyran mechanophores placed in either the short chains, the long chains, or both and show that the overall mechanochemical activation of the materials is dominated by the short chains. Molecular dynamics simulations reveal that this preferential activation occurs because pinning of the ends of the elastically effective midblocks to the glassy/rubbery interface forces early extension of the short chains. These results suggest that microphase segregation and network strand dispersity play a critical role in determining molecular-scale force distributions and suggest that selective placement of mechanophores in microphase-segregated polymers is a promising design strategy for efficient mechanochemical activation in bulk materials.

Identifiers

PMID37619531
PMCPMC10515626

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Registered trials

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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.