Evidence map›Paper›PMID 38794580›Full record

ReviewPolymers2024

Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials.

Weikang Xian, You-Shu Zhan, Amitesh Maiti, Andrew P Saab, Ying Li

Abstract readReview
In one paragraph

Review in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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.

Weikang XianDepartment of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0002-6802-651X
You-Shu ZhanDepartment of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0009-0004-9741-7503
Amitesh MaitiLawrence Livermore National Laboratory, Livermore, CA 94550, USA.
Andrew P SaabLawrence Livermore National Laboratory, Livermore, CA 94550, USA.
Ying LiDepartment of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.

Funding

Department of Energy DE-AC52-07NA27344National Science Foundation CAREER-2323108National Science Foundation CMMI-2314424National Science Foundation CMMI-2316200
6 · The paper itself

Abstract

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer-particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer-particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

Indexed as

constitutive modelelastomernanoparticlereinforcementthe Mullins effect

Identifiers

PMID38794580
PMCPMC11125212

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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.