Influence of Silica Fume on Performance of Alkali-Activated Cementitious Materials and Prediction via BP Neural Network

Alkali-activated slag–fly ash cementitious materials (AAMs) are low-carbon and mechanically favorable, but suffer from pronounced drying shrinkage and high brittleness. Silica fume (SF), with its large specific surface area and strong pozzolanic reactivity, offers a promising route to mitigate these drawbacks. This study systematically investigates how SF dosage affects workability, mechanical properties, drying shrinkage behavior, chloride resistance, and microstructural evolution in alkali-activated slag–fly ash mortars. The optimal baseline mixture is determined as slag/fly ash = 3:1, activator content 15%, and water/binder ratio 0.26. At an SF replacement level of 10%, compressive and flexural strengths peak at 3, 28, and 90 days, with 90-day compressive strength reaching 83 MPa, about 24% higher than the SF-free control. Concurrently, SF exerts a marked retarding effect on drying shrinkage; at 15% replacement, 90-day shrinkage is reduced by more than 43%. Microstructural analyses reveal that SF’s micro-filler and pozzolanic reactions promote additional C-S-H/C-A-S-H gel formation, substantially densifying the matrix. However, when SF exceeds 10%, workability deteriorates, and strength slightly declines; moreover, the chloride migration coefficient increases with SF content, implying excessive SF may adversely affect chloride durability. We developed a BP neural network model to quantify nonlinear relationships between SF content and compressive/flexural strengths, shrinkage, and the chloride migration coefficient, achieving high predictive accuracy (training R2 = 0.90763, testing R2 = 0.81832) and providing a reliable data-driven tool for mix proportion optimization and performance prediction. In summary, proper SF dosage markedly enhances mechanical and shrinkage properties, yet careful consideration of trade-offs with workability and durability is required.

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Publication Details

Journal
Eng—Advances in Engineering
Published
2026-11-06
DOI
https://doi.org/10.3390/eng7110622
Primary Topic
Concrete and Cement Materials Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Influence of Silica Fume on Performance of Alkali-Activated Cementitious Materials and Prediction via BP Neural Network

爽 宋, He Li, Yiming Wang, Jingyao Li et al.
Eng—Advances in Engineering
Concrete and Cement Materials Research
article

Influence of Silica Fume on Performance of Alkali-Activated Cementitious Materials and Prediction via BP Neural Network

爽 宋, He Li, Yiming Wang, Jingyao Li, Ran Zheng
article en

Abstract

Alkali-activated slag–fly ash cementitious materials (AAMs) are low-carbon and mechanically favorable, but suffer from pronounced drying shrinkage and high brittleness. Silica fume (SF), with its large specific surface area and strong pozzolanic reactivity, offers a promising route to mitigate these drawbacks. This study systematically investigates how SF dosage affects workability, mechanical properties, drying shrinkage behavior, chloride resistance, and microstructural evolution in alkali-activated slag–fly ash mortars. The optimal baseline mixture is determined as slag/fly ash = 3:1, activator content 15%, and water/binder ratio 0.26. At an SF replacement level of 10%, compressive and flexural strengths peak at 3, 28, and 90 days, with 90-day compressive strength reaching 83 MPa, about 24% higher than the SF-free control. Concurrently, SF exerts a marked retarding effect on drying shrinkage; at 15% replacement, 90-day shrinkage is reduced by more than 43%. Microstructural analyses reveal that SF’s micro-filler and pozzolanic reactions promote additional C-S-H/C-A-S-H gel formation, substantially densifying the matrix. However, when SF exceeds 10%, workability deteriorates, and strength slightly declines; moreover, the chloride migration coefficient increases with SF content, implying excessive SF may adversely affect chloride durability. We developed a BP neural network model to quantify nonlinear relationships between SF content and compressive/flexural strengths, shrinkage, and the chloride migration coefficient, achieving high predictive accuracy (training R2 = 0.90763, testing R2 = 0.81832) and providing a reliable data-driven tool for mix proportion optimization and performance prediction. In summary, proper SF dosage markedly enhances mechanical and shrinkage properties, yet careful consideration of trade-offs with workability and durability is required.

Eng—Advances in EngineeringVol. 7(11)
Jilin University (CN), Jilin Jianzhu University (CN), Key Laboratory of Automobile Materials, Ministry of Education, Jilin University (CN), Jilin University of Architecture and Technology (CN)
Natural Science Foundation of Jilin Province, Jilin University
Industry, innovation and infrastructure, Responsible consumption and production
Openalex Percentile: Top 21%
Concrete and Cement Materials Research
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