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Research Article

Predictive modeling of glass powder and activator effects on slag-based geopolymers via central composite design

Amirouche Berkouche1, Ahmed Abderraouf Belkadi1, Salima Aggoun2, Redha Hammouche3, Samir Benaniba4

1Dept. of Civil Eng., Mohamed El-Bachir El-Ibrahimi University of Bordj Bou Arreridj, El-Anasser, Algeria
2CY Cergy Paris Université, L2MGC, F-95000 Cergy, France
3Materials and Durability of Construction Laboratory, Dept. of Civil Eng., Faculty of Science and Technology, Frère Mentouri University of Constantine 1, Constantine 25000, Algeria
4Mechanical Eng. Dept., Faculty of Sciences and Technology, University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj, El-Anasser, Algeria

Keywords

Abstract


Geopolymer;

 Modeling; 

 Glass powder; 

Optimization;

 Central composite design



This study investigates the effects of glass powder (GP) content and activator-to-precursor (Ac/Pr) ratio on the properties of slag-based geopolymer mortars using a central composite design approach. GP content ranging from 0% to 30% and Ac/Pr ratios between 0.65 and 0.75 were examined. Response surface methodology was utilized to construct predictive models for slump, 28-day compressive strength, and porosity. Scanning electron microscopy and energy dispersive X-ray spectroscopy were utilized to analyze the microstructure and chemical composition of the geopolymer matrices. Results indicate that both GP content and Ac/Pr ratio significantly influence mortar properties. Increasing GP content and Ac/Pr ratio generally improved workability, while optimal mechanical performance was achieved at moderate levels of both factors. The optimal formulation, determined through desirability analysis, consisted of 18.2% GP content and 0.72 Ac/Pr ratio, yielding predicted outcomes of 16.53 cm slump, 46.64 MPa compressive strength, and 15.85% porosity. This study demonstrates the potential of incorporating waste glass in slag-based geopolymers and provides a framework for optimizing mix designs to achieve desired performance characteristics.

© 2024 MIM Research Group. All rights reserved.

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LATEST AWARDS


2023 Reviewer Awards:

Please, visit Reviewer Awards section for the winners of the 2022 RESM reviewer awards.



2023 Best Paper Award:

The paper authored by Ferzan Fidan, Naim Aslan, Mümin Mehmet Koç entitled as “Morpho-structural and compressive mechanical properties of graphene oxide reinforced hydroxyapatite scaffolds for bone tissue applications” is awarded.



2023 Most Cited Paper Award:

The paper authored by Ercan Işık, Ehsan Harirchian, Hüseyin Bilgin, Kirti Jadhav entitled as “The effect of material strength and discontinuity in RC structures according to different site-specific design spectra" is awarded.


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