Using an on-line image analysis technique to characterize sucrose crystal morphology during a crystallization run

Abstract

The morphological forms and habits of crystals and agglomeration are important properties on crystallization processes. Online techniques for realtime measurement of these properties are mandatory for a better comprehension of crystal growth phenomenon. The present paper presents and describes a new online method to determine the complexity level of a crystal or a population of crystals during a crystallization process. An image analysis technique is combined with discriminant factorial analysis leading to results that allow the computation of the complexity of crystals through the parameter agglomeration degree of crystals. With this methodology, it has been possible to distinguish online and automatically among three different classes of crystals according to their complexity. It further describes the application of such methodology on the study of CaCl2, D-fructose, and D-glucose influence on the crystallization of sucrose, namely, on crystal size, morphology, and complexity. The effect of supersaturation, growth rate, and impurity concentration on the type, amount, and complexity level of the agglomerates was determined at different temperatures. The combination of image analysis and kinetic results allowed to understand better the crystallization phenomena in the presence and absence of impurities. The image analysis results suggest the possible application of this tool for process control, optimizing, by this way, laboratory and industrial crystallizers.