Evidence map›Paper›PMID 41703034›Full record

ArticleScientific reports2026

Response surface modeling and correlation analyses of mechanical and non-destructive properties in graphene-date palm fiber reinforced concrete.

Ahmed A Abdou Elabbasy, Abdulrazak H Almaliki, Muhammad Basit Khan, Paul O Awoyera, Olaolu George Fadugba

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.

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

5 authors.

Ahmed A Abdou ElabbasyCivil and Architectural Engineering Department, College of Engineering and Computer Sciences, Jazan University, P.O. Box 706, 45142, Jazan, Saudi Arabia.
Abdulrazak H AlmalikiDepartment of Civil Engineering, College of Engineering, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia.
Muhammad Basit KhanDepartment of Civil and Environmental Engineering, Universiti Teknologi PETRONAS (UTP), Perak, Malaysia.
Paul O AwoyeraDepartment of Civil Engineering, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia. pawoyera@pmu.edu.sa.
Olaolu George FadugbaDepartment of Civil and Environmental Engineering, Federal University of Technology Akure, Akure, Nigeria. ogfadugba@kab.ac.ug.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Achieving fracture toughness and sustainability in concrete remains a major challenge in modern construction. This study explores the synergistic effects of graphene nano-platelets (GNPs) and date palm fiber (DPF) on the mechanical and eco-efficiency performance of concrete. Eleven mix proportions with varying GNP (0-0.2%) and DPF (0-2.5%) contents were tested. Response surface methodology was employed to model five key properties-compressive strength, flexural strength, modulus of elasticity, split tensile strength, and ultrasonic pulse velocity. Pearson and canonical correlation analyses were used to examine property interrelations. Multi-objective optimization indicated that incorporating 0.199% GNPs and 0.99% DPF achieved optimal performance, enhancing compressive strength by 44%. The developed models exhibited high accuracy (R² > 0.96, desirability = 0.971). While GNPs increased embodied carbon, the overall approach balances performance, modeling precision, and sustainability, offering valuable insights for next-generation green infrastructure materials.

Indexed as

Correlation analysesDate palm fiberGraphene nano-plateletsMulti-objective optimizationResponse surface modelingSustainable concrete materials

Identifiers

PMID41703034
PMCPMC13005002

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.