Data-driven tools to “fingerprint” soft material structuring in complex processing flows

Flows involving complex time-varying deformations are ubiquitous in polymer processing, and are important to engineering non-equilibrium structure in soft materials, yet design of such processes is challenged by the availability of accurate structure-based rheological models. The development of these models is biased toward the simple viscometric flows in which they are tested, limiting their applicability in complex processes. We introduce a new experimental methodology to “fingerprint” the microstructural response of complex fluids to nearly arbitrary flows and enable an alternative approach of data-driven modeling and design. The method involves scanning small angle x-ray scattering (sSAXS) in a fluidic four roll mill (FFoRM) device that can produce arbitrarily variable two-dimensional stagnation flows. Using measurements on rod-like polymers, we demonstrate how FFoRM-sSAXS can be used to generate thousands of Lagrangian trajectories that map structural response to the time history of deformation type and rate in a flow. We show how these large data sets can be used to understand the effects of flow history on material order, rigorously test physics-based constitutive models, emulate common processing flows, and directly synthesize process-structure-property relationships.