Viability of the COG for studying consolidation and layered growth

However, the question remains as to whether this newly developed equipment is useful for the study of consolidation and layered growth. This question concerns both the reliability of the results presented, as well as the actual process by which granulation takes place in the COG.

The repeatability of the COG was evaluated by performing a triplicate series of experiments with lactose-105 mPa•s silicone oil. The results are shown in Figure 5.14. For short granulation times, i.e. times when the maximum attainable granule mass has not been reached, the results show good agreement. However, as the granulation process progresses, the spread in data points becomes larger. For longer granulation times, which are not shown in the figure, the agreement between the three sets completely vanishes. This increase in error could be the result of breakage and attrition, which causes inaccuracies in the measured granule mass.

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Overall, it appears as though the reliability of the COG is sufficient for obtaining growth data for intermediate granulation times. However, the accuracy and precision of the COG are both greatly reduced for long granulation times. As a result, a different method is needed to determine the maximum attainable granule size for a specific system.

An additional limitation of the COG is the fact that the granules it produces provide no useful data with which to investigate granule consolidation. Although X-ray tomography images suggest that at least some consolidation occurs in the outer shell of the granule, no overall consolidation is observed from pycnometry measurements. This effect is most likely caused due to the balance of consolidation with fracture formation. It is possible that in industrial granulation, a combination of consolidation, breakage and reagglomeration causes the overall decrease in porosity. Alternatively, an increase in the pore saturation by the constant addition of liquid binder might also promote the deformability of the granules, which could aid in the reduction of the macrovoid volume due to deformation.

Regardless of the actual mechanisms, the COG is designed in such a way that the data it provides cannot provide clear data concerning consolidation. Increasing consolidating forces would also increase breakage, invalidating the growth data, as would promoting agglomeration and reagglomeration.

Figure 5.14: Comparison of granule mass as a function of time for three lactose-105 mPa•s silicone oil data sets. Lines were fitted by using Hounslow et al.’s model for surface tension-driven growth [30].

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In spite of its limitations, the COG provides kinetics of layered growth that appear to describe granule growth behaviour quite well. The resulting growth rate, a fitting constant a, could be used for modelling of the process. Ideally, an expression to estimate critical-packing liquid volume fraction ϕcp should be found to determine the maximum attainable granule size

and the time needed to reach this size, as well as the full predictive kinetics. As a final remark, it is interesting that the typically found growth times are in the order of minutes to hours for the systems evaluated. This suggests that the critical-packing liquid volume fraction is never reached during practical granulation processes, unless perhaps aggressive consolidation and breakage is applied to force growth.

5.5 Conclusions

In this study, granule consolidation and layered growth behaviour was studied using a newly developed consolidation-only granulator (COG). Experiments were set up in such a way that the effects of wetting and nucleation as well as agglomeration were eliminated, and the effect of breakage and attrition was greatly reduced. The data obtained in the experiments was compared with predictions from existing models in the literature in order to elucidate the mechanisms and kinetics of growth. In this way, three of the key objectives of this work were addressed; the development of an experimental method to study consolidation and layered growth, the generation of experimental data using this method, and the identification of a model that describes the kinetics of layered growth.

Layered growth proceeded linearly with the square root of time, as predicted by Hounslow et al.’s model on surface tension-driven growth [30]. This model uses the critical-packing liquid volume fraction ϕcp and final granulation time tmax as the only two unknown parameters

for determining growth kinetics. The fact that this model predicts granule growth implies that powder-binder interaction is the driving force behind layering. There was very little qualitative difference between static growth data from Pitt et al. [31] and the dynamic growth data obtained in this work. Quantitatively, however there were differences in both the observed and interpolated tmax, and no trends were found to predict it accurately. Furthermore,

the obtained critical-packing liquid volume fraction is smaller for dynamic situations compared to the static case. This effect can partially be attributed to the fact that static growth requires a 2.5-D bed, whereas more realistic dynamic growth takes place in a 3-D environment.

From porosity calculations using pycnometry, it appears as though no overall consolidation of the granules occurred in the COG. In spite of this, X-ray computed tomography revealed that the additional powder mass layered around the granule has a higher density than the core. However, fractures negate the effect this denser layer would have on the overall granule porosity. Comparison with statically grown granules showed that such granules grow differently, with fewer macrovoids inside the granules, but a less dense grown layer around the core. It appears as though consolidation, in practice, occurs via either stronger impacts that force breakage and reagglomeration, or by constant wetting, which increases the deformability of the granules.

Overall, the COG was successful in isolating layered growth from other granulation mechanisms, and the growth kinetics obtained are a major leap in understanding and modelling layered growth. However, there are several limitations to experiments using the COG. In eliminating the effect of wetting and nucleation by prenucleation, the liquid fraction

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of the granules can only decrease. In combination with the relatively weak impacts of the COG to eliminate breakage and attrition, overall consolidation does not occur. Therefore, the COG is not suitable for studying consolidation. Moreover, breakage and attrition is not fully eliminated, and the granules show attrition and fracturing after long granulation times. Although results for short and intermediate granulation times are consistent, results for long granulation times show significant variation between different repeats. In addition, determining tmax and the final granule volume is impossible due to significant breakage after

long granulation times. A final limitation of the COG is the fact that early growth behaviour cannot be measured, although Pitt et al. proposed a method of addressing the initial leap in granule mass at the start of granulation [31].

Using the kinetic data successfully obtained with the COG, the initial workings of a model have been put in place. However, works needs to be performed to accurately determine the key parameters ϕcp and tmax. The following chapter focuses on addressing this issue.

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Chapter 6.

Layered growth in a mixer with a flat plate