Regarding product properties, the mechanical strength of the final granule is of vital importance. Due to handling, transportation, packing and further mixing with e.g. detergents, the enzyme granule is exposed to many types of mechanical stresses, causing degradation and breakdown of the coating layer. This is unwanted not just for health and safety reasons but also because of reduced enzyme activity. Especially impact strength is important regarding mechanical properties of granules made in fluid beds. Consequently, it is desired to optimise the impact strength by adjustment of the formulation and process conditions.
A systematic experimental study of vital process and formulation parameters (fluidisation velocity, nozzle pressure, coating solution dry matter contents and bed temperature) is conducted to optimise impact strength of placebo enzyme Na2SO4 cores (200 - 300 ìm) coated with solutions of Na2SO4/Dextrin in a small-scale top-spray GEA Aeromatic-Fielder Strea-1 fluid bed while at the same time reducing the agglomeration tendency during coating. Based on an unreplicated 2^(4-1) fractional factorial design, two models are derived describing the agglomeration tendency and impact strength respectively as function of the screened parameters. Model tendencies are further investigated in additional experiments including studies of coating liquid droplet penetration and SEM studies of coating layer and core morphology as function of coating liquid formulation properties. It is observed that the degree of droplet penetration is significant and that this may explain the observed tendencies of increasing impact strength with increasing coating solution dry matter contents. Validation of the models shows satisfactory consistency between the agglomeration model and new experimental data. Similar validation of the impact strength model is somewhat less satisfactory but the model succeeds in predicting the overall experimental trends. These models may be seen as an important first step towards the development of models capable of predicting unagglomerated enzyme granules with high mechanical strength besides constituting a contribution to the quantification of qualitative fluid bed product and process tendencies.
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