Evidence map›Paper›PMID 42020609›Full record

ArticleScientific reports2026

Optimization of oil shale ash-based cement composite incorporating a ternary chemical modifier.

Faris Matalkah, Yazan Akkam, Mohammed A Zaitoun, Aya Al-Haj Issa

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

4 authors.

Faris MatalkahDepartment of Civil Engineering, Yarmouk University, Irbid, 21163, Jordan. matalkah@yu.edu.jo.
Yazan AkkamDepartment of Medicinal Chemistry and Pharmacognosy, Yarmouk University, Irbid, 21163, Jordan.
Mohammed A ZaitounDepartment of Medicinal Chemistry and Pharmacognosy, Yarmouk University, Irbid, 21163, Jordan.
Aya Al-Haj IssaDepartment of Chemistry, Yarmouk University, Irbid, 21163, Jordan.

Funding

Scientific Research and Innovation Support Fund ENG/1/13/2021
6 · The paper itself

Abstract

The high carbon footprint of Portland cement manufacturing motivates researchers toward finding suitable cement replacement. This study investigates the development and optimization of a high-volume oil shale ash (OSA) cement composite using ternary chemical additives composed of sodium sulfate (2-8%), cysteine methyl ester (0.2-1.0%), and silica gel powder (1-5%). The ordinary Portland cement (OPC) was replaced by a 50% OSA. The clinker demand was reduced, achieving compressive strength up to 33.66 MPa, meeting structural requirements. An optimization statistical model was used to determine the optimal formulation, which was then evaluated through fresh, mechanical, water transportation, and durability tests. Among the 15 experimental mixtures, 28-day compressive strengths ranged from about 18-26 MPa, and 90-day strengths ranged from 21 to 34 MPa, showing a steady increase in strength due to improved pozzolanic activity, with the 90-day compressive strength exceeding 33.5 MPa. Physicochemical characterization of the paste was performed to gain insight into the hydration mechanism. The performance enhancement observed in the optimization mix is attributed to a synergistic chemical-activation mechanism in which sulfate-induced ettringite formation, sodium-driven dissolution of reactive OSA phases, and chelation-stabilized crystallization, supplemented by silica-gel-based pozzolanic refinement, collectively densify the microstructure and promote sustained strength development.

Indexed as

CementCompressive strengthCysteine methyl esterOil shale ashOptimization

Identifiers

PMID42020609
PMCPMC13272948

What OpenQuestion holds

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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.