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Open Access research which pushes advances in bionanotechnology

Strathprints makes available scholarly Open Access content by researchers in the Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS) , based within the Faculty of Science.

SIPBS is a major research centre in Scotland focusing on 'new medicines', 'better medicines' and 'better use of medicines'. This includes the exploration of nanoparticles and nanomedicines within the wider research agenda of bionanotechnology, in which the tools of nanotechnology are applied to solve biological problems. At SIPBS multidisciplinary approaches are also pursued to improve bioscience understanding of novel therapeutic targets with the aim of developing therapeutic interventions and the investigation, development and manufacture of drug substances and products.

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Role of turbulent shear rate distribution in aggregation and breakage processes

Marchisio, D L and Soos, M and Sefcik, J and Morbidelli, M (2006) Role of turbulent shear rate distribution in aggregation and breakage processes. AIChE Journal, 52 (1). pp. 158-173. ISSN 0001-1541

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Abstract

The effect of spatial flow heterogeneity on shear-induced aggregation and breakage of fine particles in turbulent flow conditions is investigated using computational fluid dynamics (CFD) and population balance modeling. The quadrature method of moments (QMOM), particularly suitable for implementation in commercial CFD codes, has been used to solve the corresponding population balance equation. QMOM is first tested and compared with alternative numerical methods (sectional/fixed-pivot methods) for a specific set of realistic operating conditions. Then QMOM is implemented in a CFD code and the effect of spatial heterogeneities on the cluster mass distribution in a Taylor-Couette vessel is investigated. Simplified models have been derived based on the separation of the timescales of mixing on one hand and of aggregation and breakage on the other and compared with the full CFD model. Guidelines for use and limitations of such models and the identification of the underlying aggregation and breakage kernels are discussed.