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Hierarchical self-assembly provides a route for the bottom-up fabrication of nanomaterials with tailored structure and function that cannot readily be produced by top-down processing. Multiscale computational modeling is a powerful tool to establish fundamental understanding and control of hierarchical assembly processes across different length/time scales. To study mesoscopic behavior, my Ph.D. research concerned the mesoscale modeling of particle assembly in evaporating droplets by integrating Brownian dynamics simulations of the colloidal particle dynamics with lattice Boltzmann simulations of the multiphase fluid dynamics. We studied particle assembly for both colloidal particles in the liquid bulk and at the liquid-vapor interface of static and evaporating droplets and the coupling to contact line dynamics. To further reveal molecular-level structure, my current research interest as a postdoc is to explore hierarchical self-assembly of peptoids using all-atom and coarse-grained molecular dynamics simulations to guide the rational design of peptoid-based nanomaterials. Peptoids are synthetic peptidomics polymers with precise sequence control, high biocompatibility, and chemical stability. Using all-atom molecular simulations, we identified a previously unknown hierarchical self-assembly pathway for the formation of crystalline peptoid sheets and made testable predictions for the stable structures as a function of solvent conditions that were subsequently validated by our experimental collaborators. We also developed the first MARTINI-compatible coarse-grained peptoid force field from bottom-up parameterization from all-atom molecular dynamic simulations. Taken together, my work in hierarchical nanomaterials has established a new understanding and control of colloidal and peptoid assembly using multiscale computational simulation conducted in close concert with experimental collaborators with various materials, biomedical, biochemical, and engineering applications. Host: Sandrasegaram Gnanakaran |