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Accumulation of contaminants in water is an urgent and growing global concern, from a combined sustainability and public health perspective. Wastewater treatment has become an attractive target for reclaiming valuable resources that have been rapidly depleted, such as rare metals and fertilizer chemicals, as well as for filtering components from wastewater effluent that are harmful to both humans and wildlife. Reclamation of these contaminants necessitates materials that have been engineered to selectively sequester and release specific targets. We take a computational approach toward designing, understanding, and optimizing these materials by combining molecular dynamics simulations with modern data science methods. We are specifically interested in polypeptide-based materials, where specific amino-acid sequences may be chosen and tuned to optimize contaminant capture and release. Students working on this project will learn how to perform molecular dynamics simulations and then apply these skills to evaluate and compare various candidate materials for selective capture and release of target molecules. No prior experience is necessary, but students must have a strong interest in the physical sciences and basic familiarity with computers and programming.
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