Model Assisted Design of Granular Products

Publication Reference: 
ARR-59-03
Author Last Name: 
Smith
Authors: 
Rachel Smith, Bilal Ahmed, Faraj Shmam, Peyman Mostafaei
Report Type: 
ARR
Research Area: 
Particle Formation
Publication Year: 
2022
Publication Month: 
1
Country: 
United Kingdom

Executive Summary
The vast majority of granular products are granulated to produce some desired function and performance. This function may be improved flow, reduced dustiness, specific granule strengths and attrition resistance, or could be specific criteria for dispersion or dissolution.
While these performance criteria are typically the driving reason to granulate in the first place, we are still unable to confidently design granulation processes which optimise for desired product performance. There are several reasons for this, but two of the largest hurdles to overcome are:
1) the lack of mechanistic models which relate granule structure and material properties to granule properties, and
2) the cooperative development of linked process and product models, to ensure essential parameters are modelled throughout the process and product.
The aim of this project is to demonstrate the ability to link process and product models for wet granulation processes, and to initiate solution of the inverse problem, i.e. to determine the required process parameters and material properties to provide desired granule performance. A case study of granule disintegration/dispersion has been chosen as the product performance model for this work.
This annual report summarises key progress toward the project aims made over the past 12 months. In particular, a mechanistic single granule model has been developed, which includes rates processes such as liquid penetration, liquid absorbance, swelling and stress build-up. This single granule model has been coupled with a population balance model, to enable the modelling of swelling driven breakage for populations of granules.
A preliminary parametric sensitivity analysis was conducted for the unified granule disintegration model, which investigated the effects of initial granule size, disintegrant particle size, initial granule porosity and disintegrant absorption ratios on granule size distributions and size evolution. The model was found to be sensitive to all four parameters, with faster disintegration promoted by increased granule size, decreased disintegrant particle size, lower initial porosity and increased absorption ratios.
Initial experimental method development is also presented. In this work, the relationship between granulation process parameters, internal granule structure and granule dissolution kinetics was studied. The results demonstrate the important role of granule porosity in granule dissolution, and provide important steer for the development of validation experiments for granule disintegration.
In the immediate future, work within this project will focus on disintegration model sensitivity analysis, model calibration and validation. The disintegration model will then be linked to an existing model for high shear granulation, and the process of inverse problem solving for the linked process-product model initiated.