Modeling and prediction of morphology and crystallinity for cylindrical-shaped crystals during polymer processing

To describe and predict the crystallization and morphology evolution of semicrystalline polymers, the shape of crystals is often modeled as spheres and/or cylinders. The Kolmogoroff-Avrami model, which is often used to model the crystallinity and spherulite growth of polymer materials under isothermal and nonisothermal conditions, has shortcomings in dealing with conditions when spherulites and cylindrical crystals form simultaneously. This study adopted the Monte Carlo method, a method based on the random theory, to model and predict the morphological evolution of crystallization and the degree of crystallinity for polymers that exhibit concurrently growing spherulites and cylindrical crystals. A case study on predicting the morphology and crystallinity of a solidifying polymer melt with the memory effect (self-seeding) from prior stretching is presented. The effectiveness of this Monte Carlo approach vs. the original Kolmogoroff- Avrami model was demonstrated when compared with experimental results. In addition, for the ideal cylindrical growth of crystals, a modified Kolmogoroff-Avrami model based on the Monte Carlo method solutions is proposed to predict the crystallinity without intensive computation. The results showed that the modified expression performs better than the original Avrami prediction.