Size-controllable micro-droplets obtained in microfluidic cross-junctions are significant in
microfluidics. Modeling and predictions in microfluidic-based droplet formation …

User-specified droplets generated by microfluidics are critical but requires intensive
expertise and much time. Stimulated by data boosts from microfluidic experiments, deep …

Predicting drop coalescence based on process parameters is crucial for experimental
design in chemical engineering. However, predictive models can suffer from the lack of …

Droplet microfluidics has attracted much attention in recent years. For many droplet-based
applications, researchers want to predict the size of the droplets in a certain experimental …

The distribution of droplet sizes produced in a microfluidic T‐junction is modeled using the
gamma probability distribution. The proposed model is validated using physical insight from …

Though much experimental work has been done on droplet formation in microfluidic T-
junctions, the field is fragmented due to differences in channel dimensions, flow rates, and …

Real-time object identification and classification are essential in many microfluidic
applications especially in the droplet microfluidics. This paper discusses the application of …

This study employed computational fluid dynamics (CFD) to investigate various regimes of
droplet formation in a square microfluidic cross-junction device. The first part of the study …

A visualization experiment was conducted to study the formation of droplets in the cross-
junctions with various bifurcation angles. The squeezing, dripping, jetting, and threading …

Machine learning has recently been introduced in the context of droplet microfluidics to
simplify the process of droplet formation, which is usually controlled by a variety of …