Discrete computational modelling of twin screw granulation

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Many industrial processing operations depend on feed materials that are fine powders with poor handling characteristics, which have to be rectified by granulation to form coarser granules. Generally wet granulation is employed, in which a binder is added to the powder in a mixer usually in batch processes. Continuous Twin Screw Granulation (TSG) has considerable potential, eg in the pharmaceutical sector, because of the flexibility in throughput and equipment design, reproducibility, short residence times, smaller liquid/solid ratios and also the ability to granulate difficult to process formulations. However, there remain significant technical issues that limit its widespread use and a greater understanding of the process is required to meet regulatory requirements. Moreover, encapsulated APIs (Active Pharmaceutical Ingredients) are of increasing interest and the development of a TSG process that did not damage such encapsulates would significantly extend applications. Experimental optimisation of TSG is expensive and often sub-optimal because of the high costs of APIs and does not lead to a more generic understanding of the process. Computational modelling of the behaviour of individual feed particles during the process will overcome these limitations. The Distinct Element Method (DEM) is the most widely used method but has rarely been applied to the number of particles in a TSG extruder (~ 55 million) and such examples involve simplified interparticle interactions e.g. by assuming that the particles are smooth and spherical and any liquid is present as discrete bridges rather than the greater saturation states associated with granulation. The project will be based on a multiscale strategy to develop advanced interaction laws that are more representative of real systems. The bulk and interfacial properties of a swelling particulate binder such as microcrystalline cellulose will be modelled using Coarse-grained Molecular Dynamics to derive inputs into a meso-scale Finite Discrete Element Method model of formulations that include hard particles and a viscous polymeric binder (hydroxypropylcellulose). Elastic particles (e.g. lactose and encapsulates) with viscous binder formulations will be modelled using the Fast Multi-pole Boundary Element Method. These micro- and meso-scale models will be used to provide closure for a DEM model of TSG. It will involve collaboration with the Chinese Academy of Science, which has pioneered the application of massively parallel high performance computing with GPU clusters to discrete modelling such as DEM, albeit with existing simpler interaction laws. An extensive experimental programme will be deployed to measure physical inputs and validate the models. The screw design and operating conditions of TSG for the formulations considered will be optimised using DEM and the results validated empirically. Optimisation criteria will include the granule size distribution, the quality of tablets for granules produced from the lactose formulation and the minimisation of damage to encapsulates. The primary benefit will be to provide a modelling toolbox for TSG for enabling more rapid and cost-effective optimisation, and allow encapsulated APIs to be processed. Detailed data post-processing will elucidate mechanistic information that will be used to develop regime performance maps. The multiscale modelling will have applications to a wide range of multiphase systems as exemplified by a large fraction of consumer products, catalyst pastes for extrusion processes, and agriculture products such as pesticides. The micro- and mesoscopic methods have generic applications for studying the bulk and interfacial behaviour of hard and soft particles and also droplets in emulsions. The combination of advanced modelling and implementation on massively parallel high performance GPU clusters will allow unprecedented applications to multiphase systems of enormous complexity.