Data-Driven Design of Hybrid Membrane Materials for Organic Liquid Separations
Chemicals that are free of impurities are critical to everyday products such as electronics, medicine, and food. However, separating a chemical mixture into its pure constituents is energy intensive and expensive. This project will develop new membrane materials that can separate chemical mixtures at lower cost and use less energy. The research team will combine advanced data science with lab experiments to speed up materials discovery.
The project will focus on separating a liquid mixture of small molecules called paraffins and olefins. This specific separation is especially important to the chemical industry because these molecules are used to make fuels and plastics. The results of this project will be new membrane materials, and better computr programs for finding these materials. Additional benefits to society will come from training science and engineering students in data science, undergraduate research and training, and public outreach at science festivals.