On cloud microfluidic experiment platform powered by in situ maskless lithography

Abstract

Microfluidics has seen rapid growth across research and development, offering significant potential for scientific, engineering, and commercial applications. Yet, current teaching methodologies often lack a hands-on, problem-based learning approach, limiting students' practical experience. Researchers in low-resource regions also face barriers to accessing comprehensive microfluidic setups. Addressing this gap, we introduce a cloud-based platform for microfluidic experiments that integrates in situ polymerization, advanced fluid flow control, high-speed imaging, and edge computing. This first-of-its-kind platform allows users to fabricate high-resolution microfluidic devices and conduct experiments remotely through a web interface, expanding access for researchers, educators, and students. It features an image-assisted in situ polymerization process that enables easy pattern generation from uploaded images or CAD files, alongside robust computational resources for data processing, analysis, and machine learning applications. We demonstrate the platform in an educational setting through a Biological Fluid Mechanics course project and in research through experiments on organoid mechanical stretching. This work marks a milestone in democratizing access to microfluidic technology and advancing experimental capabilities in research and education.