The Autonomous Formulation Laboratory: An Open Liquid Handling Platform for Formulation Discovery Using SAXS and SANS
Peter Beaucage, Tyler Martin
The application of machine learning techniques to x-ray scattering experiments has been of significant recent interest, offering advances in areas such as the study of complex oxides. Despite these success stories, few applications of these techniques into soft materials have been reported, likely due in part to the highly non-equilibrium nature of soft materials phase spaces and the complexities associated with autonomous formulation preparation. Here, we report the design of the Autonomous Formulation Laboratory, a robust platform for the automated synthesis and measurement of complex liquid mixtures using x-ray and neutron scattering, readily extensible to system-specific complementary techniques such as spectroscopy and rheometry. We describe the application of the resulting highly reproducible, dense datasets to materials systems ranging from silica nanoparticles to block copolymer micelles. We expect the platform to prove revolutionary to understanding of the stability of complex liquid formulations and the resulting datasets to provide fertile ground for the development of machine learning techniques for complex soft materials phase spaces.
and Martin, T.
The Autonomous Formulation Laboratory: An Open Liquid Handling Platform for Formulation Discovery Using SAXS and SANS, Chemistry of Materials, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933344
(Accessed June 7, 2023)