This project addresses a grand challenge facing society today--how to make clean water available to a growing population at low cost. Membranes used in water treatment processes are exposed to feed waters containing organic, inorganic, and biological species, which leads to fouling and loss of membrane productivity over time. Since performance loss due to fouling is one of the largest costs associated with membrane processes in water treatment, discovery of new surface treatments that limit fouling would have significant economic and societal impacts. Fouling propensity of a membrane depends greatly on its surface properties such as chemistry and morphology. The goal of this project is to develop the multiscale mathematical framework to predict fouling behavior on the surfaces of membranes with different geometric patterns and chemical coatings. The ability to predict fouling properties of new membrane surfaces in silico will accelerate the discovery of novel membrane designs and decrease the time from laboratory to market. This work will be transformational because delivering an experimentally-validated computational framework will enable rapid screening of many membrane surface modifications to short-list the most promising ones for further testing, and it will lead to a leapfrog improvement in membrane filtration technologies. This project will provide a multidisciplinary environment for training graduate and undergraduate researchers. New communication platforms such as Zoom video conferencing will be used to deliver virtual science demonstrations and laboratory tours to elementary school.