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Updated: May 12, 2026

Fabrication and Characterization of Thickness Mode Piezoelectric Devices for Atomization and Acoustofluidics
Published on: August 5, 2020
CFD modelling and simulations of atomization-based processes for production of drug particles: A review
Mohamad Baassiri1, Vivek Ranade2, Luis Padrela1
1SSPC Research Centre, Department of Chemical Sciences & Chemical Engineering, Bernal Institute, University of Limerick, Limerick V94 T9PX Ireland.
Abstract:
Atomization-based techniques are widely used in pharmaceutical industry for production of fine drug particles due to their versatility and adaptability. Key performance measure of such techniques is their ability to provide control over critical quality attributes (CQAs) of produced drug particles. CQAs of drug particles produced via atomization critically depend on fluid dynamics of sprays; resulting mixing, heat and mass transfer; distribution of supersaturation and subsequent nucleation and growth of particles. It is essential to develop and use computational fluid dynamics (CFD) models for adequate understanding of multi-scale transport processes ranging from molecular scale mixing and particle scale processes, and from atomizer nozzle to overall spray chamber scale establishing relationships between CQAs and design and operating parameters of spray nozzle and chamber. In this work, we critically review past and current research efforts on CFD modelling of pharmaceutical atomization-based processes with an objective to provide clear assessment of the state of the art and to provide recommendations. An overview of the key atomization-based methods for producing drug particles with desired CQAs is presented. Key underlying physical processes and relevant concepts are then outlined. This discussion is related to the demands on CFD models; and state of the art is then discussed with respect to the process needs. Recommendations are provided towards higher fidelity and more efficient models of atomized multiphase flow dynamics and turbulence, drying modelling for the produced particles, and validation approaches. We conclude by highlighting a perceived need for numerical atomization studies with a pharmaceutical context; then, we deliver an outlook on current promising active control and machine learning strategies to augment the shift towards quality-by-design approaches in pharmaceutical manufacturing.
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