Computational Reverse Engineering Analysis of Scattering Experiments (CREASE) on Amphiphilic Block Polymer Solutions

In this talk we will present the extension of a recently developed Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) approach to analyze spherical, cylindrical, fibrillar, and elliptical cylinder assembled structures in amphiphilic block copolymer solutions. Using CREASE one can analyze scattering profiles when existing analytical models are insufficient to correctly interpret the shape and dimensions of the assembled solution structure and the chain conformations and packing within the assembled domains. CREASE is comprised of two steps: the first step involves a genetic algorithm (GA) to determine the shape and dimensions of the domains in assembled structure and the second step uses molecular simulations to reconstruct chain conformations and monomer level arrangements within the assembled structure. We will also demonstrate the integration of machine learning enhanced genetic algorithm step in the CREASE framework to speed up the CREASE calculation as well improve accuracy of the CREASE predictions.