On cloud microfluidic experiment platform powered by in situ maskless lithography

Area of Science:

• Microfluidics
• Cloud Computing
• Educational Technology

Background:

• Microfluidics offers significant potential but lacks hands-on learning and accessible setups, particularly in low-resource regions.
• Current teaching methods often do not provide sufficient practical experience in microfluidics.
• Barriers exist for researchers in low-resource settings to access advanced microfluidic equipment.

Purpose of the Study:

• To introduce a novel cloud-based platform for remote microfluidic experiments and device fabrication.
• To address the limitations in hands-on learning and accessibility of microfluidic technology.
• To expand access to microfluidic capabilities for researchers, educators, and students globally.

Main Methods:

• Development of a cloud-based platform integrating in situ polymerization, fluid flow control, high-speed imaging, and edge computing.
• Implementation of an image-assisted in situ polymerization process for pattern generation from images or CAD files.
• Remote operation via a web interface with computational resources for data processing and machine learning.

Main Results:

• Successful remote fabrication of high-resolution microfluidic devices and execution of experiments.
• Demonstration of the platform in an educational setting (Biological Fluid Mechanics course) and research (organoid mechanical stretching).
• Enabled easy pattern generation and provided robust computational resources for data analysis.

Conclusions:

• The platform democratizes access to microfluidic technology, overcoming resource and geographical barriers.
• It enhances experimental capabilities in both research and educational contexts.
• This work represents a significant advancement in making microfluidics more accessible and versatile.