Computational Methods for Analysis of Small Angle Scattering Data from Polymer Networks

Polymer networks are a broad class of materials with applications in food science, chemical separations, and tissue engineering. The structure of a polymer network greatly impacts the macroscopic properties of the material, including mechanical properties and transport of fluids through the material. Small-angle X-ray and neutron scattering (SAXS and SANS) are techniques used to study the structure of polymeric materials at multiple length scales. Conventional analysis of scattering profiles involves extracting structural parameters by fitting an analytical model to the profile; however, the existing analytical models may be too approximate for unconventional structures accessed by novel polymer chemistries, creating a need for new analysis methods that do not rely on analytical model fits. The Computational Reverse-Engineering for Scattering Experiments (CREASE) algorithm is such a computational method. In this talk, we will present our ongoing work extending CREASE to provide structural information from scattering experiments of network structures.