Evidence map›Paper›PMID 41492003›Full record

ArticleScientific reports2026

Sustainable grout for structural repairs incorporating waste master board and fiber: experimental study and RSM-based evaluation.

Saif Hameed Hlail, Rania Al-Nawasir, Riyadh Alturki, Muhammad Imran Khan

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

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

4 authors.

Saif Hameed HlailCollege of Engineering, University of Al-Shatrah, Thi-Qar, Iraq.
Rania Al-NawasirRoads and Transportation Engineering Department, College of Engineering, University of Al-Qadisiyah, Al-Diwaniyah, 58002, Iraq.
Riyadh AlturkiCivil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), 11564, Riyadh, Saudi Arabia.
Muhammad Imran KhanCivil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), 11564, Riyadh, Saudi Arabia. mekhan@imamu.edu.sa.

Funding

Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University IMSIU-DDRSP2502
6 · The paper itself

Abstract

This study develops a novel eco-friendly cementitious grout by incorporating waste-derived materials to enhance sustainability in structural repairs. Crushed master board (MB) was used as a partial cement replacement at 5%, 10%, 15%, and 20% by weight, alongside 1% steel fibers (SF) sourced from electrical wire waste. An extensive experimental program was conducted to evaluate the impact of these waste materials on the grout's density, flowability, compressive strength, and flexural strength. The results demonstrate that the inclusion of 1% SF enhanced the density at both 7 and 28 days, while MB alone slightly reduced its relative to the control mix. Flowability decreased with the addition of SF and increasing MB content, with a maximum reduction of 35.3%, indicating higher mixture cohesion. A significant improvement in compressive strength was observed with 1% SF (up to 14.8%), which was further elevated to a 31.7% gain compared to the reference mix when combined with 10% MB. Flexural strength followed a similar trend, confirming the structural integrity of the modified blends. Statistical analysis via ANOVA and predictive modeling using Response Surface Methodology (RSM) validated the experimental results, showing a strong correlation between predicted and observed values. The study concludes that an optimum mix containing 1% SF and 10% MB offers the best balance of strength and workability. This combination contributes to a denser microstructure, as evidenced by microscopic analysis, which revealed increased formation of calcium silicate hydrate (C-S-H) gel.

Indexed as

ANOVAConcrete repairElectrical steel fiber wasteEnvironmental sustainabilityMaster board wasteResponse surface methodology

Identifiers

PMID41492003
PMCPMC12848084

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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.