Integrated Design of Chemical Admixture Systems For Ultradurable, Low Co2 Alternative Binder Chemistries Via Machine Learning
This topic would develop extremely durable concretes and cementitious materials to tackle technology challenges in the development of widely applicable concrete and cement. Cement is the second most used substance in the world (next to water), largely due to its low cost, abundance, and reliability in a wide variety of environments. Cement has been a LITERAL building block of society dating back to the ancient Egyptians, Greeks, and Romans, but current production and utilization methods pose significant energy and emissions challenges. These threaten cement’s growth as domestic infrastructure degrades with age. Cement is important to U.S. energy production, as well as to infrastructure industry. The International Energy Agency estimated that in 2016 the cement and concrete sector consumed 10.5 exa-joules of energy and generated 2.2 gigatons of CO2 emissions globally. ARPA-E is seeking to develop novel materials for infrastructure with improved performance and lifetime and lower energy and emissions impacts. These projects present opportunities to develop material and process improvements that could improve the durability of cement, while maintaining or lowering production and deployment-related emissions. They could also ensure new types of cement are cost-competitive with existing traditional materials.
Project Innovation + Advantages:
Develop a machine learning algorithm to guide the design of molecular additives that streamline the path for alternative binder chemistries concrete use in existing construction methods and equipment. The central goals are to increase the durability of US infrastructure by at least twofold and reduce the energy expended in producing this concrete by at least half.