Morphology evolution during polymer crystallization. Simultaneous calorimetric and optical measurements. Felice De Santis*, Anna Rosa Vietri, Roberto Pantani Department of Chemical and Food Engineering, University of Salerno Via Ponte don Melillo, 84084 Fisciano (SA), Italy Phone +39 089 96 4013; Fax +39 089 96 4057; E-mail: fedesantis@unisa.it Summary: The crystallization of the isotactic poly(propylene) (i-PP) has been studied carrying out measurements by means of a special calorimeter connected to a microscope and a digital acquisition system of images. The analysis of Polarized Optical Microscopy images has allowed the appraisal of nucleation density and growth rate in isothermal and non isothermal conditions. The results obtained in isothermal conditions have been analyzed through the Kolmogoroff model and the crystallinity calculated from the model has been compared with that obtained from the calorimetric measurements. Keywords: calorimetry, crystallization, poly(propylene) (PP), spherulites Introduction Calorimetry and polarized optical microscopy are commonly adopted techniques in the study of polymer crystallization. Calorimetry allows the determination of the evolution of the crystalline degree through the latent heat of crystallization. Information about the evolution of morphology inside the sample cannot be obtained by this technique. On the other hand, optical microscopy allows the direct determination of the evolution of morphological characteristics of the sample, which in quiescent conditions essentially mean number of nuclei and spherulite dimensions (radii). Despite of the fact that both techniques provide data about the same phenomenon, it is still under discussion which is the appropriate relationship linking the resulting data. The aim of this work is the study of crystallization kinetics of isotactic poly(propylene) (i-PP), by coupling the two techniques in simultaneous measurements through a novel transparent single cell system from Linkam Scientific Instruments. [1] The Kolmogoroff-Avrami-Evans (KAE) model was adopted to relate the two sets of data.