Evidence map›Paper›PMID 32085489›Full record

ArticlePolymers2020

Role of Nanoparticle-Polymer Interactions on the Development of Double-Network Hydrogel Nanocomposites with High Mechanical Strength.

Andrew Chang, Nasim Babhadiashar, Emma Barrett-Catton, Prashanth Asuri

Abstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 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

4 authors.

Andrew ChangDepartment of Bioengineering, Santa Clara University, Santa Clara, CA 95053, USA.
Nasim BabhadiasharDepartment of Bioengineering, Santa Clara University, Santa Clara, CA 95053, USA.
Emma Barrett-CattonDepartment of Bioengineering, Santa Clara University, Santa Clara, CA 95053, USA.
Prashanth AsuriDepartment of Bioengineering, Santa Clara University, Santa Clara, CA 95053, USA.ORCID 0000-0003-4837-8400

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extensive experimental and theoretical research over the past several decades has pursued strategies to develop hydrogels with high mechanical strength. Our study investigated the effect of combining two approaches, addition of nanoparticles and crosslinking two different polymers (to create double-network hydrogels), on the mechanical properties of hydrogels. Our studies revealed that these orthogonal approaches may be combined to synthesize hydrogel composites with enhanced mechanical properties. However, the enhancement in double network hydrogel elastic modulus due to incorporation of nanoparticles is limited by the ability of the nanoparticles to strongly interact with the polymers in the network. Moreover, double-network hydrogel nanocomposites prepared using lower monomer concentrations showed higher enhancements in elastic moduli compared to those prepared using high monomer concentrations, thus indicating that the concentration of hydrogel monomers used for the preparation of the nanocomposites had a significant effect on the extent of nanoparticle-mediated enhancements. Collectively, these results demonstrate that the hypotheses previously developed to understand the role of nanoparticles on the mechanical properties of hydrogel nanocomposites may be extended to double-network hydrogel systems and guide the development of next-generation hydrogels with extraordinary mechanical properties through a combination of different approaches.

Indexed as

double-network hydrogelshydrogel mechanical propertiesnanocompositespolymer–nanoparticle interactions

Identifiers

PMID32085489
PMCPMC7077622

What OpenQuestion holds

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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.