Evidence map›Paper›PMID 38006160›Full record

ArticlePolymers2023

Polyurea-Graphene Nanocomposites-The Influence of Hard-Segment Content and Nanoparticle Loading on Mechanical Properties.

Demetrios A Tzelepis, Arman Khoshnevis, Mohsen Zayernouri, Valeriy V Ginzburg

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Bayesian Uncertainty Quantification for A Fractional-Order Model of the Human Ear.Journal of the Association for Research in Otolaryngology : JARO · 2026
    Article
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.

Demetrios A TzelepisDepartment of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI 48824, USA.ORCID 0000-0002-3390-612X
Arman KhoshnevisDepartment of Mechanical Engineering, Michigan State University, East Lansing, MI 48824, USA.ORCID 0009-0008-7806-1491
Mohsen ZayernouriDepartment of Mechanical Engineering, Michigan State University, East Lansing, MI 48824, USA.
Valeriy V GinzburgDepartment of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI 48824, USA.

Funding

National Science Foundation DMS-1923201United States Army Research Office W911NF-19-1- 0444
6 · The paper itself

Abstract

Polyurethane and polyurea-based adhesives are widely used in various applications, from automotive to electronics and medical applications. The adhesive performance depends strongly on its composition, and developing the formulation-structure-property relationship is crucial to making better products. Here, we investigate the dependence of the linear viscoelastic properties of polyurea nanocomposites, with an IPDI-based polyurea (PUa) matrix and exfoliated graphene nanoplatelet (xGnP) fillers, on the hard-segment weight fraction (HSWF) and the xGnP loading. We characterize the material using scanning electron microscopy (SEM) and dynamic mechanical analysis (DMA). It is found that changing the HSWF leads to a significant variation in the stiffness of the material, from about 10 MPa for 20% HSWF to about 100 MPa for 30% HSWF and about 250 MPa for the 40% HSWF polymer (as measured by the tensile storage modulus at room temperature). The effect of the xGNP loading was significantly more limited and was generally within experimental error, except for the 20% HSWF material, where the xGNP addition led to about an 80% increase in stiffness. To correctly interpret the DMA results, we developed a new physics-based rheological model for the description of the storage and loss moduli. The model is based on the fractional calculus approach and successfully describes the material rheology in a broad range of temperatures (-70 °C-+70 °C) and frequencies (0.1-100 s

Indexed as

adhesiveDMAelastomerfractional Maxwell modelgraphenenanocompositepolyureaSEM

Identifiers

PMID38006160
PMCPMC10675114

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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.