Probabilistic numerical simulation of morphology development from non-isothermal calorimetric crystallization curves

Abstract This work introduces a probabilistic numerical simulation method to describe or predict the spherulitic morphology of semicrystalline polymer formed during non-isothermal crystallization process. The numerical simulation is based on the general crystallization theory, which consists of random nucleation and subsequent growth of supermolecular formations. The model is capable for prediction of morphology from the conversion curve of crystallization recorded by calorimetry during crystallization at a constant cooling rate. Samples made of polypropylene nucleated by different nucleating agents were used as a model material for testing the simulation approach. The results indicated that valuable structural information can be predicted from the conversion curve, like nucleus density, average spherulite size and size distribution as well. In addition, the simulation method also capable to predict the mechanism of nucleation during the crystallization process, namely, whether the number of nuclei is constant or continuously changing. The results also indicated that nucleus density increases significantly as a consequence of heterogeneous nucleation, which indicates that the simulation results in realistic and reliable structural data both in nucleated and non-nucleated samples.