Our research

Our multi-disciplinary team uses combinatorial nanoscience techniques to control the synthesis of colloidal nanoparticles with complex structure and to direct the complex dynamics of excited states in such materials. As nanomaterials incorporate more components (e.g., elements, or domains in heterostructures), their synthesis requires reaction pathways with an increasing number of interactions between chemical species. Likewise, the energy transfer (ET) pathways that often determine the optical properties of doped materials such as upconverting nanoparticles are convoluted into nonlinear networks. Due to feedback in these networks, understanding their isolated interactions (i.e., homogeneous nucleation) is insufficient for understanding the overall process (e.g., nanoparticle growth). We use a holistic approach to understand the dynamics of an entire reaction or ET network. High-throughput combinatorial methods are necessary to probe the large number of possible variations, and computational models are necessary to describe network properties. We leverage automated workflows in which we (1) develop computational models to identify promising material candidates, (2) use combinatorial methods to experimentally synthesize libraries of these candidates in parallel, and (3) use high-throughput characterization and data analysis to understand the properties of these material libraries. To realize these objectives, we have established three major Research Areas described below.