The stochastic geometry of polymer crystallization processes

The process of crystallization of polymers may be modelled as a spatially structured counting process, whose intensity kernel depends upon the available free volume. Due to the effect of impingement, an explicit expression for the stochastic occupied volume is difficult to obtain, while derivations of its expected value have been provided since the pioneering work of Kolmogorov and Avrami, in use of chemical engineers. In this paper we provide two theorems which, by the use of stochastic geometry, ensure local and global convergence of the stochastic growth process to its expected value, justifing so the use of deterministic models to predict the results of real experiments. Also consistent statistical estimators of the growth parameters can be provided. Their asymptotic normality gives the possibility to build confidence intervals for their predicted values