![]() Research in the Webb group centers on accurate and chemically specific computational approaches to simulate, characterize, and design novel materials for health and sustainability applications. We are particularly interested in the study of both natural and synthetic polymers, which have applications that range from simple thickening agents in foods to electrolyte solvents in batteries to stimuli-responsive drug-delivery systems. This versatility inherent to polymeric materials can be largely attributed to their macromolecular nature in combination of chemical and topological diversity, which presents both exciting engineering opportunities as well as complex challenges for molecular simulation. Central questions to our research are how does the chemistry matter and how can we effectively describe it across multiple spatiotemporal scales? Through the development and application of hierarchical simulation techniques, we aim to provide chemical insights on experimental metrology and guide the design of future functional materials. |
Designing Polymeric Membranes for Sustainability Applications
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Controlling Biopolymer Interactions for Health Applications![]() |
Advancing Hierarchical Simulation Capabilities![]() |
Integrating Machine Learning & Modeling in Soft Materials DesignWhile machine learning algorithms have emerged as powerful tools for molecular property prediction and design for many problems in chemistry, engineering, and materials science--successful application of ML to problems in soft materials has been much more limited. With the aid of our systematic coarse-graining techniques, we are exploring, integrating, and exploiting ML techniques in tandem with soft matter simulation to facilitate materials design.
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