Abstract Scope |
While scattering methods (SAXS, SANS, WAXS) are workhorse techniques for characterizing model macromolecular formulations, they have not been widely used to characterize real products, largely because the large number of components (10-100) often precludes rational mapping between component fractions, structure, and product stability. Multimodal characterization and machine learning (ML) tools promise to greatly reduce the expense of exploring the stability boundaries of a particular, desirable phase in highly multicomponent products. Here we describe the development of the Autonomous Formulation Laboratory, a highly adaptable platform capable of autonomously synthesizing and characterizing liquid mixtures with varying composition and chemistry using x-ray and neutron scattering in addition to a suite of secondary measurements such as optical imaging, UV-vis-NIR and capillary rheometry. |