Evidence map›Paper›PMID 41457090›Full record

ArticleScientific reports2025

Enhanced UV resistance of polypropylene via copper nanoparticle incorporation for outdoor applications.

Mohammed Baafif, Hany S Abdo, Abdulmohsen Albedah

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. A Composite Based onPolymers · 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

3 authors.

Mohammed BaafifMechanical Engineering Department, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia.
Hany S AbdoCentre of Excellence for Research in Engineering Materials, Deanship of Scientific Research, King Saud University, Riyadh, 11421, Saudi Arabia.
Abdulmohsen AlbedahMechanical Engineering Department, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia. albedah@ksu.edu.sa.

Funding

Ongoing Research Funding Program, King Saud University ORFFT-2025-122-2
6 · The paper itself

Abstract

This study investigates the effect of copper nanoparticles (Cu NPs) on the ultraviolet (UV) resistance and long-term thermal and mechanical stability of polypropylene (PP) composites. Cu NPs were incorporated into PP at varying concentrations (0-10 wt%) to evaluate their influence on size distribution, melt flow index, density, tensile and flexural properties, Shore D hardness, and thermal behavior using Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC). Accelerated aging tests over 1000 h were conducted to assess durability under simulated environmental exposure. Results show that Cu NPs, particularly at 1-2 wt%, considerably improve mechanical performance and thermal stability while mitigating photo-oxidative degradation. Reinforced composites exhibited enhanced yield strength, elongation, stiffness, and energy absorption compared to pure PP after aging. DSC and TGA analyses revealed better retention of crystallinity and delayed thermal degradation in Cu NP-filled PP. Although higher nanoparticle loadings (> 5 wt%) led to diminished benefits due to stress concentration and possible agglomeration, the 2 wt% formulation demonstrated the optimal balance between UV protection and mechanical integrity. These findings highlight the potential of Cu NP-reinforced PP for outdoor and engineering applications requiring enhanced weatherability and long-term performance.

Indexed as

Copper nanoparticlesOutdoor applicationsPolymer compositePolypropyleneUV resistance

Identifiers

PMID41457090
PMCPMC12855964

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.