Droplet dynamics in microfluidics through experimental, numerical and data driven approaches–a review

Droplets generated in microfluidics find applications in various engineering and biological systems. Control of size, generation frequency and stability are essential features in manufacturing microfluidics devices and testing of droplets. These parameters are significantly influenced by factors such as geometry, flow conditions, and fluid properties. Researchers have used experimental, computational and machine-learning models to investigate the underlying dynamics of micro level fluid flow phenomenon. It is important to understand the comparative advantages and disadvantages of these investigation methods and their applicability for a given microflow situation. Through a survey of past published research literature, this review article discusses various aspects of droplet microfluidics, including channel fabrication, droplet generation and visualization techniques. Additionally, the effect of influencing parameters on droplet formation across all three investigative approaches is briefly examined. This review aims to provide insight into the usefulness of each of methods separately and in integrated approach along with their performance. It also provides a benchmark for improving droplet generation and visualization techniques for engineering and biological applications, ensuring efficient usage.