ArticleMaterials (Basel, Switzerland)2024
Performance Characterization and Composition Design Using Machine Learning and Optimal Technology for Slag-Desulfurization Gypsum-Based Alkali-Activated Materials.
Article in Materials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Effect of Industrial Byproduct Gypsum on the Mechanical Properties and Stabilization of Hazardous Elements of Cementitious Materials: A Review.Materials (Basel, Switzerland) · 2024Review
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Authors and funding
6 authors.
Funding
Abstract
Fly ash-slag-based alkali-activated materials have excellent mechanical performance and a low carbon footprint, and they have emerged as a promising alternative to Portland cement. Therefore, replacing traditional Portland cement with slag-desulfurization gypsum-based alkali-activated materials will help to make better use of the waste, protect the environment, and improve the materials' performance. In order to better understand it and thus better use it in engineering, it needs to be characterized for performance and compositional design. This study developed a novel framework for performance characterization and composition design by combining Categorical Gradient Boosting (CatBoost), simplicial homology global optimization (SHGO), and laboratory tests. The CatBoost characterization model was evaluated and discussed based on SHapley Additive exPlanations (SHAPs) and a partial dependence plot (PDP). Through the proposed framework, the optimal composition of the slag-desulfurization gypsum-based alkali-activated materials with the maximum flexural strength and compressive strength at 1, 3, and 7 days is Ca(OH)
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