Collaborative Research: Experimental and Computational Studies of Droplet and Bubble Flows through Complex Geometries

Yale University, New Haven CT

Investigators

Abstract

This award aims to advance our understanding of how soft, deformable particles, such as oil droplets and cells, move through complex environments consisting of narrow constrictions and obstacles. Unlike previous research on rigid particles like sand, this study will explore the behavior of extremely deformable particles that can significantly change their shapes—by more than 50% in many cases. This research has important implications for numerous industrial processes and applications, from improving diagnostic techniques in healthcare (such as cell sorting), to developing better filtration and wastewater treatment devices. By combining carefully designed experiments with advanced computer simulations, the researchers aim to develop predictive models that can accurately describe how deformable particles flow and interact with their surroundings under different driving conditions. This research not only pushes the boundaries of science, but also has the potential to drive innovations leading to improved design and operation of systems that rely on the controlled flow of soft particles, ultimately benefiting national interests such as public health, economic competitiveness, and environmental sustainability. Furthermore, the project includes educational outreach initiatives to mentor students, promote diversity and inclusion in STEM fields, and foster the next generation of scientists and engineers. The project will systematically investigate the flow of bubbles and droplets through obstacle arrays, studying the effect of particle surface tension, as well as the obstacle density, size, and placement, on the particle trajectories. Specifically, this project will investigate whether the flow rate of deformable particles through a narrow orifice can be described by the Beverloo equation and if flows through obstacle arrays can be characterized by an effective permeability, similar to fluid flows through porous media. It will also explore how surface tension of the droplets and shear forces due to the surrounding fluid influence particle breakup and coalescence, culminating in a quantitative framework capable of predicting the size distribution of deformable particles generated by emulsification devices employing obstacle array geometries. Experimental studies will be complemented by efficient computer simulations of bubbles and droplets flowing through constrictions and obstacle arrays in both two and three dimensions, enabled by the development of a new deformable particle model (DPM) that incorporates surface tension. The project's potential contributions include a predictive framework for deformable particle transport through obstacle arrays, which could lead to improved design and operation of microfluidic and lab-on-a-chip devices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.