Optimization of Mix Proportions and Random-Forest-Assisted Exploratory Modeling for Alkali-Activated Fly Ash Geopolymer

Alkali-activated fly ash geopolymers are promising low-carbon binders, but their performance depends strongly on mix proportion design. This study investigated the effects of water-to-binder ratio, sand content, and NaOH concentration on fly ash-based geopolymer using an L25(56) orthogonal design. Flexural and compressive strengths were evaluated through range analysis and Analysis of Variance (ANOVA), while Random Forest was used as an exploratory tool for factor-response interpretation. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) were conducted to relate mechanical behavior to microstructural evolution. The optimal combination within the tested levels was a water-to-binder ratio of 0.30, sand content of 40%, and NaOH concentration of 12 mol/L. The maximum flexural and compressive strengths reached 3.65 MPa and 17.98 MPa, respectively. NaOH concentration dominated flexural strength, whereas water-to-binder ratio primarily controlled compressive strength. Model benchmarking and cross-validation showed that the machine-learning results had limited generalization capability under the small-sample condition and should be interpreted as candidate screening rather than independent predictive validation. Microstructural analyses indicated that strength development was associated with matrix densification, aluminosilicate network reorganization, and amorphous geopolymeric gel formation.

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Publication Details

Journal
Buildings
Published
2026-07-16
DOI
https://doi.org/10.3390/buildings16142843
Primary Topic
Concrete and Cement Materials Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimization of Mix Proportions and Random-Forest-Assisted Exploratory Modeling for Alkali-Activated Fly Ash Geopolymer

Guihong Guo, Binsheng Zhang, Yawei Ma, Ying Zhang et al.
Buildings
Concrete and Cement Materials Research
article

Optimization of Mix Proportions and Random-Forest-Assisted Exploratory Modeling for Alkali-Activated Fly Ash Geopolymer

Guihong Guo, Binsheng Zhang, Yawei Ma, Ying Zhang, Xianyang Wang
article en

Abstract

Alkali-activated fly ash geopolymers are promising low-carbon binders, but their performance depends strongly on mix proportion design. This study investigated the effects of water-to-binder ratio, sand content, and NaOH concentration on fly ash-based geopolymer using an L25(56) orthogonal design. Flexural and compressive strengths were evaluated through range analysis and Analysis of Variance (ANOVA), while Random Forest was used as an exploratory tool for factor-response interpretation. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) were conducted to relate mechanical behavior to microstructural evolution. The optimal combination within the tested levels was a water-to-binder ratio of 0.30, sand content of 40%, and NaOH concentration of 12 mol/L. The maximum flexural and compressive strengths reached 3.65 MPa and 17.98 MPa, respectively. NaOH concentration dominated flexural strength, whereas water-to-binder ratio primarily controlled compressive strength. Model benchmarking and cross-validation showed that the machine-learning results had limited generalization capability under the small-sample condition and should be interpreted as candidate screening rather than independent predictive validation. Microstructural analyses indicated that strength development was associated with matrix densification, aluminosilicate network reorganization, and amorphous geopolymeric gel formation.

BuildingsVol. 16(14)
Lanzhou University (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 14%
Concrete and Cement Materials Research
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