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The Pozzo Research Group focuses on control and optimization of material structures for applications in alternative energy, synthesis, separations, medicine, and more. We work to accelerate the discovery and screening of novel materials through the utilization of machine learning, high-throughput analysis, automation of laboratory procedures, and advanced characterization using small angle x-ray and neutron scattering.

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Science Jubilee

An open-science, multi-tool motion platform for sciene automation!

In the Pozzo Group we are developing open-hardware and open-software for self-driving labs using low-cost and accessible automation! Science Jubilee is a collaborative effort with Dr. Nadya Peek and her group, Machine Agency, at UW. This project aims to create community-driven efforts in collaborating on ways of developing, sharing, vetting, and maintaining open source hardware for science and engineering research.


Check out our own version of an autonomous color matching campaing using Science Jubilee equipped with a Raspberry Pi camera and an Opentrons OT2 pipette!

Follow the links below to learn more:

Latest Publications

Metric geometry tools for automatic structure phase map generation

This paper describes a computational statistical tool to efficiently obtain a phase map from multi-scale experimental measurement profiles obtained from high-throughput small-angle X-ray scattering experiments of polymer blend systems. We show that learned metric geometry can efficiently differentiate ordered phase regions with shifted, missing, and broad Bragg peaks along with features related to non-Bragg behavior of soft-matter systems. The metric geometry allows us to define a shape distance between scattering profiles invariant to phase-independent transformations thus valuable for obtaining a phase map. 

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