ArticleScientific reports2025
Compressive strength modelling of cenosphere and copper slag-based geopolymer concrete using deep learning model.
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 12 papers.
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Who cites it
12 citing papers in PubMed.
- Influence of hybrid fiber reinforcement on strength and durability properties of fly ash blended PSC concrete.Scientific reports · 2026Article
- Machine learning-driven evaluation of mechanical and microstructural properties of agro-waste-derived geopolymer concrete.Scientific reports · 2026Article
- Assessment of thermally induced strength loss in alkali-activated concrete through ensemble regression models.Scientific reports · 2026Article
- Effect of nano-silica and sisal fibre on the mechanical and durability properties of concrete.Scientific reports · 2026Article
- Influence of paper mill sludge ash on mechanical, microstructural and durability properties of metakaolin based geocrete.Scientific reports · 2026Article
- Interface improvement and multiscale assessment of recycled concrete aggregates with epoxy resin polymer.Scientific reports · 2026Article
- Compressive strength prediction of carbonated recycled aggregate concrete using regression based machine learning models.Scientific reports · 2026Article
- Impact of magnetic water treatment on the properties of high-performance concrete.Scientific reports · 2025Article
- Prediction of rapid chloride permeability using silica fume, fly ash, GGBS and micro fibers based geopolymer concrete.Scientific reports · 2025Article
- Evaluation of nonfired ceramic tiles using phosphogypsum waste and Ceiba Pentandra fiber for sustainable construction.Scientific reports · 2025Article
- Sustainable and cost-efficient machining of ZE41 magnesium alloy through optimization with Intuitionistic Fuzzy TOPSIS.Scientific reports · 2025Article
- Enhancing sustainability in RC beams with magnetically treated mixing water for improved flexural performance.Scientific reports · 2025Article
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Authors and funding
5 authors.
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Abstract
Geopolymer concrete (GPC) is an eco-friendly alternative for conventional concrete. It exploits industrial by-products in production to reduce the environmental impact and improve sustainability. This study focuses on envisaging the 28-day compressive strength of cenosphere-based geopolymer concrete incorporating copper slag using Artificial Neural Networks (ANN). The assimilation of ANN models in predicting the compressive strength of cenosphere-based geopolymer concrete with copper slag offers a promising approach to sustainable construction. By precisely forecasting the compressive strength of concrete based on the ingredient proportions, these models can rationalise the design process. The test results signposted that the developed model gives higher accuracy (> 98.6%), capability and flexibility in predicting the compressive strength of geo-polymer concrete incorporated with cenosphere and copper slag.
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