The chemical engineering science of materials is entering a new era of so-called "designer materials,'' wherein, based upon the properties required for a particular application, a material is designed by exploiting the self-assembly of appropriately-chosen molecular constituents.
Materials so fabricated (also sometimes referred to as advanced materials), are presently proposed for numerous applications, ranging from photonic and quantum devices to biomedical and tissue engineering applications. My research focus is to develop a theoretical and computationally-based program aimed at elucidating the fundamental mechanisms underlying the design of novel, self-assembled advanced materials. The goal is to complement the research of experimentalists (synthetic chemists, chemical engineers, and material scientists) by providing simple but quantitative guidelines to rationally design and synthesize these materials. Towards this broad objective, our group's research focuses on the development and use of a wide variety of tools spanning both equilibrium and nonequilibrium statistical mechanics, conventional fluid mechanics, molecular rheology and computational tools to complex fluids and biological systems.
A common theme that has pervaded most of our research has been the multiscale approach. Quite often in the systems we are considering, and for the properties we are interested in predicting, modeling descriptions at a single scale (either molecular or continuum) do not typically suffice or even exist. Our research focuses on using either computational approaches (combining molecular simulations with continuum level numerical methods) or statistical mechanical models to link the molecular details of the components to macroscopically measurable and tunable properties. Within this broad theme, the problems we work on are typically characterized by experimental accessibility (i.e. for issues which are either currently of experimental focus and/or experimentally testable) and impact on practical applications. In this manner, our results and models relate to "real world" phenomena, thereby providing graduate students with a plethora of career opportunities at the end of their research.