1. Development of Robust and Accurate CFD Models for Microfluidic Multiphase Flows

Our team focuses on advancing computational fluid dynamics (CFD) models specifically tailored for microfluidic multiphase systems. These models enable precise simulations and predictive analyses, contributing to breakthroughs in microfluidics. Key areas of research include:

• Enriched Finite Element Method
• Enhanced Level-Set Technique
• Improved Level-Set Redistancing Method
• Conservative Level-Set Technique
• Electro-Hydrodynamics Coupled Problems

2. Experimental Studies of Microfluidics

Our experimental investigations provide valuable insights into microfluidic phenomena. We utilize state-of-the-art equipment and techniques to explore various aspects:

• Micro-dispenser Systems
• Fluids Subjected to Electric Field
• Electrospray (EHDA)

3. Artificial Intelligence for Microfluidic Technologies

Harnessing the power of AI, we integrate machine learning and image processing into microfluidic research:

• Image Recognition and Processing
• Machine Learning for Predicting Liquid Transport Microsystems
• Digital Twins for Microfluidic Devices

For more detailed information, explore our research publications and ongoing projects on our webpage.