Concurrent, multi-modal, multi-facility scattering experiments on polymer materials with the Autonomous Formulation Lab

The Autonomous Formulation Lab (AFL) at the National Institute of Standards and Technology (NIST) presents a powerful approach to characterizing complex polymer materials by combining open hardware, AI decision agents, and X-ray and neutron scattering techniques (SAXS and SANS). In collaboration with industrial partners, the AFL aims to improve the reformulation of industrial and everyday polymer formulations to accelerate progress toward a greener, healthier future. Recently, the AFL program has explored several applications of multi-modal decision-making, where multiple types of measurement data are collected on each sample and used by the AI decision agent to guide the course of the experiment. From combining SAXS and spectroscopy to better understand dye solubilization to SANS and turbidity for bioformulations, these experiments demonstrated the utility of integrating diverse data streams for improved decision-making. Our multi-modal studies culminated in a multi-facility experiment where the AI agent leveraged concurrent SAXS and SANS measurements to elucidate the multi-scale structure of paint formulations. This talk will discuss the instrumentation, methodologies, and the role of AI/ML in the AFL's multi-modal scattering campaigns, with a focus on our multi-facility experiments.