X-ray micro tomography and image analysis as complementary methods for morphological characterization and coating thickness measurement of coated particles

This work demonstrates the potentiality of X-ray micro tomography as a powerful tool for morphological characterization of coated particles and, in particular, of their coating layer. X-ray micro tomography provides a high level of details at both micro and macro-scale. It was, in this work, used in the determination of density, porosity, surface/volume ratio, and thickness of the coating layer. Special emphasis was put on evaluation of the adhesion core/coating shell due to its strong influence on the acceptance and goodness of the final coated compound. Different definitions of coating thickness are evaluated. The variance of these properties is assessed within particles and between particles. A novel protocol was developed in order to segment the coating shell out from the core particles. The segmented out images were used to create 3D models of such coating shells. General aspects of theses models are discussed. The potential and limitations of X-ray micro tomography are finally highlighted based on the experimental work. Image analysis was used to determine the coating thickness applied on the core particles as complementary and reference method. As case study, two series of coated particles, prepared using top-spray fluidized bed coater, were obtained, each one employing three standard well-know coating agents.     

A population balance model for high shear granulation

In a previous paper, Hoornaert et al. ( Powder Technol. 96 (1998); 116-128) presented data from granulation experiments performed in a 50 L Lödige high shear mixer. In this study that same data was simulated with a population balance model. Based on an analysis of the experimental data, the granulation process was divided into three separate stages: nucleation, induction, and coalescence growth. These three stages were then simulated separately, with promising results. It is possible to derive a kernel that fit both the induction and the coalescence growth stage. Modeling the nucleation stage proved to be more challenging due to the complex mechanism of nucleus formation. From this work some recommendations are made for the improvement of this type of model.     

Failure mechanism determination for industrial granules using a repeated compression test

This work describes the development of a particle compression test that allows direct and repeated application of the stress. The test is designed to quickly reduce the load on a granule during its incipient failure. By so doing, the breakage can be arrested and thus the process can be studied in detail. Experimental tests have been made on samples of industrial enzyme granules, which have a complex layered structure, and reproducible results have been obtained. The contribution of the various layers to the strength of the granule has been investigated, showing that the use of coating materials results in improved granule strength. The microstructure of the granule determines the failure mode of the granule. It is concluded that the failure mechanisms can be defined from tests on only a few granules as can assessment of the relative contribution of the layers and of the granule core to its strength. A measurement of the distribution of strength requires a larger, statistically representative, sample.     

Attrition strength of water-soluble cellulose derivatives coatings

The aim of this paper was to compare the attrition strength of microparticles coated with various water-soluble cellulose derivatives coatings using the repeated impact tester (RIT). As a core material glass beads of diameter 650-850 μm were used. Four water-soluble cellulose derivatives have been investigated as coating materials: methylcellulose (MC), two types of carboxymethylcellulose (CMC — low and high viscous type) and hydroxypropylcellulose (HPC). Within the research coatings of 5 μm and 20 μm thickness were attrition tested. For all tested cellulose derivatives coatings, attrition occurred according to the layer fatigue sub-mechanism. Overall, HPC coatings were found to be the strongest since they did hardly show any coating mass loss during attrition testing. Most of the low viscous CMC coatings were resistant to fatigue for a low number of impacts, only, and they have shown the lowest strength against attrition. Attrition data showed the relationship between coating uniformity and coating strength in that uneven and irregular surfaces resulted in a lower strength against attrition. Coating thickness also influenced the results of the repeated impact tests: thicker coatings generally presented a higher attrition strength compared to 5 μm coatings. Testing two different carboxymethylcellulose types showed the influence of molecular weight on the coating strength. High viscous CMC, having a higher molecular weight, also presented a higher strength against attrition.     

On the fluidization of cohesive powders: Differences and similarities between micro- and nano-sized particle gas–solid fluidization

The fluidization of cohesive powders has been extensively researched over the years. When looking at literature on the fluidization of cohesive particles, one will often find papers concerned with only micro- or only nano-sized powders. It is, however, unclear whether they should be treated differently at all. In this paper, we look at differences and similarities between cohesive powders across the size range of several nanometres to 10s of micrometres. Classification of fluidization behaviour based on particle size was found to be troublesome since cohesive powders form agglomerates and using the properties of these agglomerates introduces new problems. When looking at inter-particle forces, it is found that van der Waals forces dominate across the entire size range that is considered. Furthermore, when looking into agglomeration and modelling thereof, it was found that there is a fundamental difference between the size ranges in the way they agglomerate. Where the transition between the types of agglomeration is located is, however, unknown. Finally, how models are made and agglomerate sizes are measured is currently insufficient to accurately predict or measure their sizes consistently.