This
paper provides a model of the crystallization kinetics of
polyamide 6 (PA6), including primary and secondary crystallization,
lamellar thickness distribution, and the evolution of the mobile and
rigid fractions of the amorphous phase. The kinetics includes the
two-phase structure, the monoclinic α-phase and the pseudo-hexagonal
γ-meso phase, of which the fractions depend on the thermal history
during solidification. The model is parameterized with experimental
results from the literature. The thickness of the rigid amorphous
layer was the only parameter to be estimated. The obtained results
indicate that the fraction of the amorphous rigid fraction depends
not only on the thermal history but also on the crystalline phase
and if the rigid amorphous layer was formed in combination with the
α- or γ-meso phases. These results provide the bases for
predicting and controlling mechanical properties, which can strongly
depend on processing conditions as, for example, experienced during
injection molding.
A population balance model for the prediction of molecular weight distribution (MWD) in a continuous stirred tank reactor (CSTR) has been developed accounting for multiradicals and gel formation in the framework of Galerkin-FEM. In the absence of recombination, gel does not form, but accounting for multiradicals leads to a better prediction of the long MWD tail. Results of the multiradical model with topological scission are well in line with Monte Carlo (MC) simulations. For the case of recombination without scission the multiradical model leads to perfect agreement with MC simulations as regards prediction of the gel fraction and chain length distribution. The classical monoradical model fails to describe the gel regime. We account for gel fragmentation in systems with gelation and scission. Results for this case are in agreement with MC simulations. A nongel assuming variant allows properly detecting the gelpoint and the associated distribution. The scission model adopted, linear or topological scission, turns out to be of extreme importance for the gel regime prediction.
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