Evidence map›Paper›PMID 41552435›Full record

ArticleACS omega2026

Structural and Electromechanical Insights into Thermoplastic Polyurethane/3D Hybrid Carbon Nanocomposites for Strain Sensor Applications.

Vaishnav B, Benedikt Sochor, Ajay Gupta, Sarathlal Koyiloth Vayalil

Abstract read
In one paragraph

Article in ACS omega, 2026. 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. 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.

Vaishnav BDepartment of Physics, Applied Science Cluster UPES, Dehradun 248007 India.
Benedikt SochorDeutsches Elektronen-Synchrotron DESY, Notkestrasse 85, Hamburg 22607, Germany.
Ajay GuptaDepartment of Physics, Applied Science Cluster UPES, Dehradun 248007 India.ORCID https://orcid.org/0000-0002-4430-6875
Sarathlal Koyiloth VayalilDepartment of Physics, Applied Science Cluster UPES, Dehradun 248007 India.ORCID https://orcid.org/0000-0003-3483-3310

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incorporation of carbon allotropes of different dimensions within elastomeric matrices has been established as an effective strategy to fabricate functional conductive polymer nanocomposites (PNCs). In this work, higher-dimensional 3D hybrid carbon nanofillers, comprising synergistically integrated multiwalled carbon nanotubes immobilized onto few-layer graphene, were incorporated into the thermoplastic polyurethane (TPU) matrix to demonstrate their effectiveness as strain sensors. The conductive films were fabricated through a simple solution casting technique, in which the mechanical, electrical, and strain-sensing characteristics were studied in view of filler distribution, structural confinement, and interfacial interactions. Analyses using wide-angle X-ray scattering, Raman spectroscopy, and tensile testing revealed a higher degree of filler reinforcement within the TPU moieties, indicating pronounced interfacial interactions. Further, the tensile modulus increased significantly with filler loading above its percolation threshold (363% for 20 wt % loading). The structural features of dispersed filler aggregates were explored through an iterative model fitting of the ultra-small-angle X-ray scattering (USAXS) data, along with scanning electron microscopy (SEM). As a strain sensor, the films displayed a superior working-strain Gauge Factor (GF = 123, up to 8%), with exceptional stability under both unidirectional and cyclic strain. The findings provide a fundamental understanding while validating the potential of hybrid carbonaceous fillers for the fabrication of PNCs with futuristic applications.

Identifiers

PMID41552435
PMCPMC12809358

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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.