Evidence map›Paper›PMID 42590322›Full record

ArticleMaterials (Basel, Switzerland)2026

Micro-CT-Based Experimental Study on the 3D Structure-Electrical Conductivity Relationship of Metal-Coated Woven Fabrics.

Magdalena Tokarska, Adam K Puszkarz, Marcin Makówka

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Magdalena TokarskaFaculty of Textiles and Design, Institute of Architecture of Textiles, Lodz University of Technology, 116 Zeromskiego St., 90-543 Lodz, Poland.ORCID 0000-0001-8102-1230
Adam K PuszkarzFaculty of Textiles and Design, Textile Institute, Lodz University of Technology, 116 Zeromskiego St., 90-543 Lodz, Poland.ORCID 0000-0002-1765-9093
Marcin MakówkaFaculty of Mechanical Engineering, Institute of Materials Science and Engineering, Lodz University of Technology, 1/15 Stefanowskiego St., 90-924 Lodz, Poland.ORCID 0000-0003-1685-3174

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The investigated materials were metal-coated woven fabrics. X-ray micro-computed tomography was employed to characterize the fabrics, including their coating, yarn, and pore structures. Electrical resistance was measured using a four-electrode configuration inspired by the van der Pauw method. The obtained results revealed strong relationships between structural parameters and electrical properties of fabrics. Multidirectional resistance measurements confirmed continuous electrical conduction and low resistance values. Correlation analysis revealed that a thicker metal coating on the fabric surface may be associated with increased anisotropy of the electrical properties, with a correlation coefficient of 0.772 at the 0.05 significance level. The results suggest that an increase in pore sizes (mean and median) may be associated with higher resistance values (correlation coefficients ranged from 0.839 to 0.941 at the 0.05 significance level), potentially contributing to changes in the distribution of conductive regions within the fabric. An increase in pore sizes (median) may be associated with greater dimensional irregularity, which in turn may be related to increased direction-dependent variability in the electrical response, reflecting higher electrical anisotropy within the sample plane (correlation coefficient of 0.958 at the 0.05 significance level).

Indexed as

3D woven fabric geometryelectrical anisotropyelectrical conductivitymetal coatingmicro-CT

Identifiers

PMID42590322
PMCPMC13466654

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.