Abstract

Polymer blends are critical in many commercial products and industrial processes. For instance, in membrane or fibre spinning, composite materials manufacturing, and thermoplastic compounding and moulding. In most circumstances, such products are formulated with samples of high dispersity, which have generally only been studied at the mean-field level. In this talk, I show how field theoretic treatments of concentration fluctuations can be applied to blends of disperse polymers. This requires a careful analysis of both short- and long-range correlations along with thermodynamic analysis in terms of moments of the molecular weight distribution(s). This powerful combination yields analytical results for the inverse susceptibility, i.e. spinodal curve, which is critical in industrial applications. We demonstrate the importance of dispersity on several example systems, including both “toy” models that may be realized in computer simulation and more realistic industrially relevant blends. We find that the effects of long-range fluctuations are particularly prominent in blends where the component dispersities are mismatched, especially when there is a small quantity of the high-dispersity species. This can be understood as a consequence of the shift in the critical concentration(s) from the monodisperse value(s).