Evidence map›Paper›PMID 41942561›Full record

ArticleScientific reports2026

Sustainable polyurethane-based dielectric composites from industrial and E-waste for high-voltage insulation applications.

Vinoth Kumar Selvaraj, Jeyanthi Subramanian, Gokul Selvanathan, Nitesh Verma Kannammaraju, Vijayakumar Rajendran

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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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.

Vinoth Kumar SelvarajSchool of Mechanical Engineering, Vellore Institute of Technology, Chennai, 600127, Tamil Nadu, India.
Jeyanthi SubramanianSchool of Mechanical Engineering, Vellore Institute of Technology, Chennai, 600127, Tamil Nadu, India. jeyanthi.svitc@gmail.com.
Gokul SelvanathanDepartment of Mechanical engineering, Electrical and Energy Systems, Brandenburg University of Technology Cottbus-Senftenberg, 03046, Cottbus, Germany.
Nitesh Verma KannammarajuDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Vijayakumar RajendranCentre for Smart Energy Systems, Chennai Institute of Technology, Chennai, 600069, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing demand for sustainable materials in electrical and electronic applications has led to the reuse of industrial and electronic waste in high-performance polymer composites. In this study, rigid polyurethane foam waste (WRPU), recycled tire waste (RTW), and printed circuit board (PCB) scraps were incorporated as fillers into a polyurethane matrix using methylene diphenyl diisocyanate (MDI) as a binder. The composites were fabricated via mechanical stirring followed by hydraulic compression. Response Surface Methodology (RSM) using a Central Composite Design (CCD) was employed to optimize the filler composition for dielectric performance. The optimal formulation—15.94 wt% WRPU, 3.0 wt% RTW, and 10.0 wt% PCB—achieved a dielectric constant of 4.45. Confirmation experiments and simulations using COMSOL Multiphysics yielded values of 4.33 and 4.50, respectively, with minimal error margins. FTIR confirmed functional group integration, HR-SEM revealed uniform filler dispersion and strong interfacial bonding, and TGA indicated improved thermal stability. The results highlight the dielectric potential of recycled polymer composites as environmentally friendly dielectric materials, although further studies are needed on breakdown strength, dielectric loss and resistivity for assessing high-voltage insulation applications, such as battery cell separators and power systems.

Indexed as

Dielectric materialsElectrical insulationPolyurethane foam wastePrinted circuit board (PCB) recyclingResponse surface methodology (RSM)Sustainable polymer composites

Identifiers

PMID41942561
PMCPMC13057145

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LicenceCC BY-NC-ND
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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.