Evidence map›Paper›PMID 41545490›Full record

ArticleScientific reports2026

Engineering characteristics of agro-residue-based geopolymer concrete with fibre reinforcement.

Govind Ravish, Mahapara Abbass

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

2 authors.

Govind RavishMaharishi Markandeshwar Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, 133207, India.
Mahapara AbbassDepartment of Civil Engineering, Maharishi Markandeshwar Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, 133207, India. mahparaabbas@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The creation of eco-friendly construction materials by utilising agro-industrial by-products presents a promising approach to lowering the carbon emissions of the building industry. This research explores the engineering behaviour of geopolymer concrete formulated with sugarcane bagasse ash, rice husk ash, and cow dung ash as aluminosilicate sources, further strengthened with basalt fibres in varying amounts (0-2.5%). A wide range of experiments was performed to assess mechanical performance (compressive, flexural, and split tensile strengths) and durability characteristics (chloride ion penetration, water absorption, and resistance to acid attack) over curing periods extending to 180 days. Results exhibited a clear parabolic relationship with fibre content, identifying an optimum dosage near 1% basalt fibre. The compressive strength increased from 50 to 62 MPa (24% improvement), flexural strength from 4.4 to 5.8 MPa (32% increase), and split tensile strength from 3.7 to 4.8 MPa (30% gain) at 180 days. Durability indicators also improved at the optimum fibre dosage: water absorption decreased from 8 to 5%, acid attack-induced mass loss reduced from 38 to 6%, and RCPT values dropped from 3100 to 1600 C, shifting chloride penetrability from moderate to low. However, fibre contents above 1.5% led to reduced workability, fibre clustering, and increased permeability. ANOVA confirmed the dominance of the quadratic fibre effect, with Fibre

Indexed as

Agro-waste valorisationCircular economyFibre reinforcementGeopolymer concreteLow-carbon building materialsStrength and durabilitySustainable construction

Identifiers

PMID41545490
PMCPMC12891576

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.