Evidence map›Paper›PMID 39897817›Full record

ArticleHeliyon2025

Experimental investigation on fresh, hardened and durability characteristics of partially replaced E-waste plastic concrete: A sustainable concept with machine learning approaches.

Md Hamidul Islam, Zannatun Noor Prova, Md Habibur Rahman Sobuz, Nusrat Jahan Nijum, Fahim Shahriyar Aditto

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In one paragraph

Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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.

Md Hamidul IslamDepartment of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.
Zannatun Noor ProvaDepartment of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.
Md Habibur Rahman SobuzDepartment of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.
Nusrat Jahan NijumDepartment of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.
Fahim Shahriyar AdittoDepartment of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid global expansion of e-waste poses significant environmental and health risks, making it crucial to find sustainable uses and mitigate its harmful effects. The significance of this research is to look into the impact of e-waste as a possible substitute for natural coarse aggregates (NCA) on the fresh, hardened and durability characteristics of concrete, alongside machine learning (ML) predictive analysis. Four kinds of concrete mixes were made with produced coarse aggregates as a substitute material for NCA, and substitution levels were calculated as 0 %, 10 %, 15 % and 20 % (by mass of NCA). Compressive and splitting tensile tests evaluated the mechanical properties of e-waste concrete, whereas water permeability and electrical resistivity tests assessed durability to determine the optimal e-waste proportion for construction. The compressive and tensile strengths of e-waste concrete were reduced by 13.41%-25.50 % and 11%-19.26 %, respectively, for replacement levels ranging from 10 % to 20 % at 28 days. The specimens, evaluated at 300 °C, exhibited reductions in compressive strength by 15.26%-30.87 % and tensile strength by 10.52%-19.74 % for e-waste replacement levels of 10%-20 %, respectively. With high coefficient correlation (R

Indexed as

Durability propertiesElectronic wasteMachine learning approachesMechanical propertiesSustainable concept

Identifiers

PMID39897817
PMCPMC11783426

What OpenQuestion holds

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LicenceCC BY-NC
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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.