I-Corps: Artificial Intelligence (AI)-assisted sustainable cement manufacturing technology

Award ID: 2243641

The broader impact/commercial potential of this I-Corps project is the development of a computational technology for building sustainable cement construction materials. Cement manufacturing is one of the largest and most energy and carbon-intensive industries in the world. Reducing the energy costs and the carbon footprint of cement manufacturing may offer an opportunity to improve profitability and lower environmental impact. The proposed technology may be used by research scientists and decision makers to improve performance, sustainability, and economic value of the cementitious materials and manufacturing process. The pathway for improving the sustainability of cementitious material manufacturing and product quality is low energy input, leading to a low carbon footprint and high economic benefits. End users include product manufacturers, cement and concrete admixture companies, codes and standards committees, and public decision-makers. This technology may be important to ensuring development is planned and conducted in a manner that is consistent with an accurate view of sustainability. This I-Corps project is based on the development of data-driven physical and chemical modeling for cement materials and manufacturing process. The proposed technology integrates the advanced reaction process simulation, cementitious materials modeling, and artificial intelligence optimization and machine learning algorithms. The technology has the potential to effectively provide optimal operational conditions for low-cost, low-carbon, high-performance cementitious materials and a manufacturing industry based on user-defined criteria. In addition, a user-friendly platform is a part of the proposed design to facilitate the use of artificial intelligence technology in improving the sustainability of construction materials industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Jaime A. Camelio