Systematic copolymer screening for foaming experiments supported by computational methods

Abstract

Computational methods for the optimization of synthetic as well as processing parameters for the fabrication of polymeric foams based on styrene and methyl methacrylate are introduced in the current study. Small scale experiments are utilized to develop a synthetic procedure for polymers with desired chain length and composition. After the upscaling of these experiments, the optimal processing parameters for autoclave foam production are determined applying Bayesian optimization, active learning algorithms and random sampling as well as exploitation-based algorithms (Greedy). By these experiments the power of such a systematic approach is shown and the foamability of styrene-methyl methacrylate-based copolymers is investigated.