Accessing Higher-Order Structural Information in Semiconducting Polymer GIWAXS Patterns by Predictive Modeling Using GIWAXSPal

Semiconducting polymer research relies heavily on grazing-incidence wide-angle X-ray scattering (GIWAXS) methods to gather structural information about polymer crystallites in films, such as crystallite distances and orientations. Despite this reliance, the structural information in 2D GIWAXS patterns is often under-utilized due to a lack of tools for predictive X-ray pattern modeling. GIWAXSPal is a predictive modeling package that specializes in simulating polymer diffraction patterns from atomic models. This package has proven useful in improving our understanding of oriented polymer film structure and counterion localization within polymer crystallites. The package's optimized algorithm permits the composition of multiple crystallite populations and orientations in each simulated GIWAXS pattern, allowing aspects of structural disorder to be modeled. Because the program is based on the structure factor equation, it can also be used for validating mathematical models linking X-ray diffraction peaks to structural features. This poster presentation seeks to introduce the package as a new tool for enabling higher-order interpretation of polymer diffraction patterns and to provide example use cases in topics relevant to contemporary topics in semiconducting polymer research.