CaIFF Webinar: Lilo Pozzo

Prof. Lilo Pozzo

Department of Chemical Engineering, University of Washington, Seattle WA USA

Autonomous decision-making agents, when paired with accessible laboratory automation, promise to greatly accelerate materials optimization and scientific discovery. For example, such frameworks can efficiently map a phase diagram through intelligent sampling campaigns, or tackle ‘retrosynthesis’ problems, where a material with a target structure is desired but a viable synthetic route is not yet known. These approaches are especially promising in soft-matter systems, including block copolymer self-assembly, nanoparticle synthesis, and controlled colloidal assembly. In these systems, design parameters (e.g., composition, MW, topology, processing) are vast, ‘out-of-equilibrium’ structures are common, and functional properties are intimately tied to molecular design features and processing history. In addition, for AI algorithms to operate efficiently in these spaces, they must be encoded with domain expertise specific to the problems being tackled. This talk will cover recent advances in democratized open hardware and software tools for accelerated materials research in polymeric and soft-matter systems, including dispersions and colloids. Finally, it will outline remaining challenges in autonomous materials optimization workflows and identify future opportunities for research.

Prof. Pozzo studies colloids, polymers, and soft matter, controlling materials structure for applications in healthcare, alternative energy, and sustainability. Her group also develops scattering (X-ray and neutron), automation, and AI tools to accelerate material development timescales. She also supports early-stage researchers as they apply their creativity and innovation toward technology translation and service-oriented engagement.

Registration link to Zoom Event

https://ucph-ku.zoom.us/webinar/register/WN_dKOX_lg8QX6qjSeRb4wnkw