(373c) A Mechanistic Model for Nucleation and Aggregation in Population Balances of Granulation: Batch Characterisation Studies and Experimental Validation | AIChE

(373c) A Mechanistic Model for Nucleation and Aggregation in Population Balances of Granulation: Batch Characterisation Studies and Experimental Validation


Ramachandran, R. - Presenter, Massachusetts Institute of Technology
Poon, J. M. -. - Presenter, Imperial College London
Sanders, C. F. W. - Presenter, University of California
Stepanek, F. - Presenter, Institute of Chemical Technology, Prague
Wang, F. - Presenter, The University of Queensland
Cameron, I. - Presenter, University of Queensland
Immanuel, C. D. - Presenter, Imperial College London

Granulation is the generic term for particle size enlargement processes. It is the process of agglomerating fine powders to form larger semi-permanent aggregates by spraying a liquid binder onto the primary particles. Despite its widespread use, granulation processes are highly inefficient and current industrial plants often operate with high recycle ratios. Thus, there is an economic incentive for better understanding of granulation processes, leading to their more effective operation. Hitherto, the majority of granulation research has focussed on granule size. However, in addition to size, the binder content and the porosity of the particles need to be accounted for since all three attributes will play a predominant role amongst the numerous interactions between the individual granulation sub-processes. Thus, it is essential to account for the size, porosity and the binder content in order to accurately model the granulation process.

In this paper, a series of batch granulation experiments was carried out to determine the growth kinetics of calcite (limestone) using small-scale drum granulator. Intermittent sampling of granules allowed for the observation of the growth behaviour during the process. In addition, the effects of different combinations of binder to solids ratio and bed depth on granule size, binder content and porosity were investigated. Sieve analysis, spectrophotometry and pycnometry were employed to obtain granule size, binder content and porosity data respectively. Laboratory scale studies on the formulation properties (e.g. surface tension, contact angle, dynamic yield stress and powder shape) for the granulation recipe (Calcite/Polyvinyl alcohol+water) were also performed to gain further insight of their influences on the predominant granulation mechanisms (e.g. aggregation, breakage, layering etc.). The lab-scale studies were also performed to isolate various mechanistic parameters in the nucleation and aggregation kernels and these lead into the modelling/validation aspect of the study described in the next paragraph.

The application of population balances, which accounts for the individual sub-processes (e.g. nucleation, aggregation and consolidation), provides a convenient framework from which the granulation process is modelled and these sub-processes will be the emphasis of this study [1-4]. One major challenge in developing these population balance models is the identification of appropriate kernels for the sub-processes. Due to the limited knowledge of the mechanisms that underlie the granulation process, many of the proposed kernels are empirical or semi-empirical, which may not be valid over a wider operating range. In order to further improve the predictive capabilities of the kernels and to extend their region of validity, one has to directly incorporate the mechanistic features of the process and develop kernels strongly based on first-principles. In a previous study the three-dimensional volume-based population balance equation eliciting the three key granule properties was solved using a constant number Monte-Carlo approach showing a close correspondence between simulation and experimental observations for the particle size and the binder liquid content [5]. Another study utilised the three particle attributes to determine the granule porosity at different stages of the consolidation stage in an attempt to predict the induction time during consolidation. It was also found that the particle size predicted compared well with those that were experimentally observed with chalcopyrite powder studies [6]. In this study a three-dimensional volume-based population balance model for the granulation process is presented with the current focus on developing and experimentally validating the population balance model incorporating mechanistic formulations for the nucleation and aggregation phenomena, in combination with an empirical relation for consolidation. Typically in experimental validation of a granulation process, only one or/and two granule attributes (e.g. granule size and binder content or porosity) are validated. In this study, all three granule attributes (granule size, binder content and porosity) are measured and validated, and this adds to the completeness of the model validation. By means of the batch granulation experiments, the underlying theory in which the kernels are formulated, are validated by comparing the experimental data of granule size, binder content and porosity with those predicted by the mechanistic model. A robust and efficient numerical solution technique (known as the hierarchical two-tier technique) was employed for the solution of the population balance model [7].


1. L.X. Liu and J.D. Litster., Population balance modelling of granulation with a physically based coalescence kernel. Chemical Engineering Science, 57: 2183-2191, 2002. 2. H.S. Tan, A.D. Salman, and M.J. Hounslow., Kinetics of fluidized bed melt granulation ? II: Modelling the net rate of growth. Chemical Engineering Science, 61: 3930-3941, 2006. 3. Biggs, C.A., Sanders, C., Scott, A.C., Willemse, A.W., Hoffman, A.C., Instone, T., Salman, A.D. and Hounslow, M.J., Coupling granule properties and granule rates in high shear granulation. Powder Technology, 130: 162-168, 2003. 4. I.T. Cameron, F.Y. Wang, C.D. Immanuel, and F. Stepanek., Process systems modelling an applications in granulation: A review. Chemical Engineering Science, 60: 3723-3750, 2005. 5. P.A.L. Wauters. Modelling and mechanisms of granulation. PhD thesis, Department of Chemical Engineering, University of Queensland, Delft University of Technology, The Netherlands, 2001. 6. W.J. Wildeboer. Design and operation of regime separated granulators. PhD thesis, Department of Chemical Engineering, University of Queensland, 2002. 7. C.D. Immanuel and F.J. Doyle III. Solution technique for a multi dimensional population balance model describing granulation processes. Powder Technology, 156: 213-225: 2005.


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