Simulation studies on picolitre volume droplets generation and trapping in T-junction microchannels

Splitting of droplet with different sizes inside a symmetric T-junction microchannel using an electric field

In the current study, droplets dynamics under an asymmetric electric field in a T-junction are numerically studied using COMSOL Multi-physics software. The effect of different factors such as dimensionless length of mother droplet (L^*), Capillary number (Ca), and electric capillary number (Ca_e) are investigated on the breakup process in symmetric T-junctions. Two novel patterns of droplets, namely, hybrid asymmetric splitting mode and sorting patterns, have been observed by imposing an electric field in one branch of the microchannel. It is also concluded that using an electric field is a promising strategy to reach droplets with arbitrary sizes and control over the splitting ratio of daughter droplets precisely in a T- junction by adjusting the electric field strength. After a certain electric capillary number (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left. {Ca_{e} } \right|_{Sorting}$$\end{document}CaeSorting), the mother droplet does not breakup and is sorted on the side of the branch that the electric field imposes. Furthermore, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left. {Ca_{e} } \right|_{Sorting}$$\end{document}CaeSorting increases with the increment of L^* and Ca.

Micro and nanofluidics for high throughput drug screening

In this book chapter, we elaborate on the state-of-the-art technology developments in high throughput screening, microfluidics and nanofluidics. This book chapter further elaborated on the application of microfluidics and nanofluidics for high throughput drug screening with respect to communicable diseases and non-communicable diseases such as cancer. As a future perspective, there is tremendous potential for microfluidics and nanofluidics to be applied in high throughput drug screening which could be applied for various biotechnology applications such as in cancer precision medicine, point-of-care diagnostics and imaging. With the integration of Fourth industrial revolution (4IR) technologies with micro and nanofluidics technologies, it envisioned that such integration along with digital health would enable next generation technology development in medical field.

Hydrodynamics of Liquid-Liquid Flows in Micro Channels and Its Influence on Transport Properties: A Review

Hydrodynamics plays a major role in transport of heat and mass transfer in microchannels. This includes flow patterns and flow regimes in which the micro-channels are operated. The flow patterns have a major impact the transport properties. Another important aspect is the pressure drop in micro-channels. In the present review, the experimental and Computational Fluid Dynamics (CFD) studies covering all the above aspects have been covered. The effect of geometrical parameters like shape of channel, channel size, material of construction of channels; operating parameters like flow velocity, flow ratio and fluid properties have been presented and analyzed. Experimental and analytical work of different pressure drop models has also been presented. All the literature related to influence of flow patterns on transport properties like volumetric mass transfer coefficients (VMTC) and heat transfer coefficients (HTC) have been presented and analyzed. It is found that most works in Liquid-Liquid Extraction (LLE) systems have been carried out in slug flow and T-junctions. Models for coupled systems of flow and mass transfer have been presented and works carried out for different coupled systems have been listed. CFD simulations match experimental results within 20% deviations in quantitative and qualitative predictions of flow phenomena for most research articles referred in this review. There is a disparity in prediction of a generalized regime map and a generalized regime map for prediction of flow patterns for various systems would need the help of Artificial Intelligence.