In the last two decades, micro-droplets have attracted increasing amounts of investigations due to promising technological and commercial applications in biological analysis, cancer diagnosis, drug discovery and everyday products. Microfluidic devices have been chosen to produce micro-droplets since the droplets generated are highly monodispersed with a controllable size. The diameter and size variation of droplets are controlled by a series of parameters, including the geometries and dimensions of the microfluidic devices, properties of liquids (viscosity, interfacial tension, etc.) used and then flow rates and surfactant concentrations. Although abundant experimental studies have been performed, the effects of the controlling parameters and the relevant mechanisms have not been elucidated. The application of micro-droplet in biological and pharmaceutical areas involves the use of non-Newtonian solutions, but they have been avoided by previous research because their high viscosities, high molecular weights and elastic behaviour complicate the formation process and analysis. Furthermore, there is a dearth of modelling studies to predict the diameter of droplets formed in microchannels.The work in this thesis concentrates on understanding the droplet formation process at a microfluidic T-junction employing xanthan gum solutions that exhibit shear thinning behaviour. The effects of the controlling parameters such as the flow rate, viscosity and inlet angles of the T-junction as well as xanthan gum concentrations were experimentally studied. The droplet diameter can be adjusted with a small size variation by choosing the controlling parameters. The role of controlling parameters in different droplet controlling regimes was elucidated. The dynamic behaviour of droplet formation at a T-junction has been studied, and the effect of xanthan gum solution was highlighted. Separate force balance models were proposed to predict the diameter of droplets produced in the squeezing and jetting regimes. Both models provided satisfactory predictions for the experimental results as well as data published in similar studies.
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