ArticleScientific reports2025
Optimizing the utilization of Metakaolin in pre-cured geopolymer concrete using ensemble and symbolic regressions.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Machine learning-driven evaluation of mechanical and microstructural properties of agro-waste-derived geopolymer concrete.Scientific reports · 2026Article
- Geopolymer Materials for Additive Manufacturing: Chemical Stability, Leaching Behaviour, and Radiological Safety.Materials (Basel, Switzerland) · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The optimization of metakaolin (MK) in pre-cured geopolymer concrete involves developing predictive models to capture the interplay of various influencing factors and guide mix design for improved compressive strength and sustainability. Ensemble methods and symbolic regression are promising approaches for this task due to their complementary strengths and solving challenges associated with repeated experiments in the laboratory. Choosing machine learning predictions over repeated, expensive, and time-consuming experiments in research projects, such as optimizing the utilization of metakaolin in pre-cured geopolymer concrete, presents a paradigm shift in how data-driven insights can revolutionize material development. The integration of ensemble and symbolic regression models enables researchers to derive valuable predictions and optimize critical performance parameters efficiently. In this research work, 235 records were collected from extensive literature search for compressive strength for different mixing ratios of pre-cured metakaolin-based geopolymer concrete with concrete at different ages. Each record contains MK: The content of metakaolin (kg/m
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