Droplet sorting computer: Design, optimization and device dynamics

doi:10.1016/j.ces.2025.121507

Droplet sorting computer: Design, optimization and device dynamics

2025-06-01

0

PRE

AI

M

Mohammad Shahab *

R

Raghunathan Rengaswamy

DOI：10.1016/j.ces.2025.121507

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Droplet sorting is a crucial component for integrated lab-on-a-chip applications, but conventional methods require active control and a sorter component. This study presents a state-of-the-art droplet sorting computer that incorporates a quality droplet sorter into a microfluidic device without the need for an additional mechanism for active detection and control. The device is computationally optimized using a novel combined design framework based on multi-agent reinforcement learning. The beauty of this sorting computer is that a device optimized for fewer drops can be used for thousands of drops, based on optimal hydrodynamic interactions between drops. The framework for developing a sorting computer is described, and the dynamics behind passive routing of droplets inside the device is explained. The proposed device can achieve droplet movement similar to that of an automated microfluidic device for droplet sorting or any given objective, making it a pioneer in passive droplet routing when implemented with appropriate process conditions.

Keyword:

Droplet sorting

Microfluidics

Reinforcement learning

Multi-agent systems

Optimization

Scalability

Droplet sorting computer: Design, optimization and device dynamics

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