Evidence map›Paper›PMID 41555006›Full record

ArticleScientific reports2026

Optimization of mechanical and durability performance of graphene nanoplatelet modified PVA fiber reinforced cementitious composites using response surface methodology.

Muhammad Basit Khan, Muhammad Umer, Paul O Awoyera, Nasir Shafiq, Wisal Ahmed, Olaolu George Fadugba, Marwa Mohsen

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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

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

7 authors.

Muhammad Basit KhanDepartment of Civil and Environmental Engineering, Universiti Teknologi PETRONAS (UTP), Perak, Malaysia.
Muhammad UmerDepartment of Civil Engineering, NED University of Engineering and Technology, Pakistan, Karachi.
Paul O AwoyeraDepartment of Civil Engineering, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia. pawoyera@pmu.edu.sa.
Nasir ShafiqDepartment of Civil and Environmental Engineering, Universiti Teknologi PETRONAS (UTP), Perak, Malaysia.
Wisal AhmedDepartment of Architecture and Civil Engineering, City University of Hong Kong, Kowloon Tong, China. wahmed7@cityu.edu.hk.
Olaolu George FadugbaDepartment of Civil and Environmental Engineering, Federal University of Technology , Akure, Nigeria. ogfadugba@kab.ac.ug.
Marwa MohsenSchool of Civil and Environmental Engineering, University of Technology Sydney (UTS), Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the hybrid reinforcement of fiber-reinforced cementitious composites (FRCCs) with graphene nano-platelets (GNPs) and polyvinyl alcohol (PVA) fibers to enhance their mechanical, durability, and strain-hardening performance. A comprehensive experimental program, supported by Response Surface Methodology (RSM), was conducted to evaluate and model the behavior of FRCCs under varying GNP dosages. Key properties, including compressive, tensile, and flexural strength, modulus of elasticity, impact resistance, ultrasonic pulse velocity, water absorption, and dry density, were investigated. Results revealed that incorporating 0.15% GNP with 1% PVA fibers increased compressive strength, split tensile strength, and flexural strength by 43.7%, 21.6%, and 22.4%, respectively, while also improving impact resistance and material densification. The addition of GNPs effectively reduced porosity and enhanced durability, whereas PVA fibers contributed to strain-hardening behavior. The integration of experimental testing with RSM-based predictive modeling demonstrates a reliable pathway for optimizing GNPs in FRCCs, offering insights for the development of durable and sustainable construction materials.

Indexed as

DurabilityFiber-reinforced cementitious compositesGraphene nano-plateletsMechanical propertiesRSM

Identifiers

PMID41555006
PMCPMC12890966

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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.