Using AI to make lower-carbon, faster-curing concrete

This post details the development and open-sourcing of an AI tool (SustainableConcrete) leveraging Bayesian optimization (BoTorch, Ax) to accelerate the discovery of low-carbon, high-performance concrete mixes. It describes the multi-objective optimization problem, the key ingredients, the AI pipeline workflow involving lab testing and iterative refinement, and the metrics used (compressive strength, curing speed, slump, sustainability proxy). The successful deployment of an AI-designed mix at a data center construction site is highlighted, demonstrating the practical application of AI in materials science and industrial sustainability.