Comprehensive study of sequester-based carbon concrete in an acidic environment using artificial neural networks

The building industry has investigated innovation to protect the environment and save resources. The COVID-19 pandemic has limited building supplies, which is raising construction costs. This emphasizes cycle economy-based sustainable growth. C&D trash and other trustworthy resources may be used. C&D wastes dominate solid waste, causing environmental issues. The best method to combat climate change is to cut construction CO₂ emissions. CO₂ emissions are a global issue prompting carbon storage innovation. Alkaline calcium hydroxide and calcium silicate hydrate (C-S-H) in C&D waste may convert CO2 into stable carbonates at ambient temperatures. Temperature, CO₂ partial pressure, time, process route, humidity, and water-to-solids ratio affect C&D CO₂ storage. Due to fast infrastructure development, natural resources are depleting. Industrialization produces CO2, which dominates the atmosphere. CCS involves collecting rubbish, transporting it to a safe place, and burying it to limit CO₂ emissions. Find the source of carbon dioxide, generally a significant point source like a cement mill or biomass power plant, to capture and store it. Corporations should cease emitting tons of CO₂. It may reduce the impact of industrial and residential heating CO₂ on climate change and ocean acidification. Long-term carbon dioxide storage in building materials is novel, although people have poured it into rock formations for decades. The neural network was trained using the same experimental research design, resulting in an ANN model that accurately predicted compressive strength properties (R² ≥ 0.99). This validates the ANN’s effectiveness in response estimation and parameter identification. The ANN technique was also utilized to determine optimal parameters, demonstrating its reliability in predicting and analyzing structural properties.