A predictive framework for mixing low dispersity polymer samples to design custom molecular weight distributions

Abstract

The physical properties of polymer samples are dependent on the overall shape and breadth of the molecular weight distribution (MWD). A small number of methods are available to tune the shape and characteristics of MWDs based on influencing controlled radical polymerizations and mixing individual distributions. However, no systematic framework exists to date to predict the characteristics and shapes of artificial MWDs prior to the experiments. In this work we present such a framework based on the interpolation of individual distributions.