Data­-Driven Molecular Engineering of Solar­ Powered Windows

PI Jacqueline Cole, University of Cambridge
Project Description

Materials discovery of better performing light-absorbing dye molecules will be enabled via a synergistic computational and experimental science approach, wherein machine learning and data mining are used in conjunction with large-scale simulations and experiments to facilitate a materials-by-design workflow. These dye molecules are needed to realize a next-generation technology of solar-powered windows, which are prospected to power buildings in future cities, in an entirely energy-sustainable fashion.

Allocations