EAGER: Microfluidic Design Automation

Microfluidic systems employ hair-sized channels to analyze fluids in credit card sized devices. Microfluidics has been shown to improve the accuracy, speed, and cost of medical tests, drug discovery, and chemical testing, but every new medical test needs to be custom designed, making microfluidic chips expensive. 3D printing (3DP) has the potential to make custom devices quickly and inexpensively. The problem with combining microfluidics and 3D printing is that an engineer with deep knowledge of the 3DP process is needed to do each design. In contrast, engineers have developed microelectronic design tools that design chips automatically. This EArly-concept Grant for Exploratory Research (EAGER) project will investigate using the principles applied in microelectronic design to produce automated design tools that enable medical technicians to design custom microfluidic devices that can be ordered and reliably 3D printed. Ultimately, custom tests might be designed, ordered, printed, and sent to a clinic or doctor’s office. The microfluidic devices could become a critical part of healthcare, food safety, chemical testing, and biodefense.

The use of design automation approaches and software can greatly improve the efficiency of design, validation, and manufacturing of microfluidic devices. Current CAD and simulation tools must be customized for each application, making them slow and expensive, and microfluidic chips often require redesign due to imperfect manual placement and routing. To overcome these challenges, several key scientific barriers need to be overcome to utilize design automation for 3D printed microfluidics. Specifically, there is a need to emulate the complexities of fluid dynamics in design automation simulation software, perform 3D placement and routing, and automate the post-processing of 3D printed microfluidic devices. The research team will develop a physics-based fluid dynamics framework for SPICE simulations coded in Verilog-AMS that handles the complexities of fluids, a placement and routing approach to build 3D designs using current open-source EDA tools with a multilayer approach, and automated systems to remove uncured resin in printed devices. The approach will be validated by using the tools to design, optimize, fabricate, and test DNA analysis devices.

This research effort is funded by NSF CMMI award number #2140148.