My work brings together science, engineering, and design to study microfluidics, embedded systems, and Lab-on-PCB platforms.
Discover is the space where concepts evolve — from hands-on experiments to collaborative research and peer-reviewed publications.
This work introduces a modular droplet-based sensor system designed to make microfluidic measurements simpler and more accessible. Built with off-the-shelf electronic components and PMMA flow-focusing chips, the device uses an optical light source and detector to count and characterize water-in-oil droplets directly on-chip. It accurately measures droplet length, volume, and monodispersity—with only 2.06 % error and 2.35 % variation—demonstrating stable, repeatable performance across multiple channel sizes. The design advances affordable and user-friendly Lab-on-PCB systems aligned with the ASSURED framework.
This review analyzes the current state of droplet-based microfluidic systems using the ASSURED criteria as a benchmark for their future development. The study identifies progress in sensitivity, specificity, and robustness, while highlighting gaps in affordability, equipment-free operation, and deliverability. It also points to optical and electrical detection methods as the most promising paths toward next-generation Lab-on-Chip devices.
This work presents a fully integrated calibration method for optical droplet-based Lab-on-PCB systems. Using a simple LED–LDR setup controlled by an Arduino, the platform measures droplet velocity, length, and volume across multiple flow regimes. The proposed λ-based calibration improves accuracy and reproducibility, achieving mean relative errors between 2.4 % and 17 % for multiphase flows up to 1000 droplets per second.
