UC Riverside

Continuous flow based microfluidic devices have made great strides in fields like rapid DNA sequencing and ex-vivo tissue samples, so-called organ-on-a-chip devices, for biological testing. While a large number of new components and biological processes have been developed, tools to help design these devices have not followed suit. As the field grows and the devices being designed become more complex, they will quickly become too difficult for a single person or small group to develop without computer assistance. This necessitates the development of tools and algorithms that can accelerate or automate parts of the design process. This dissertation presents and evaluates a collection of algorithms that form the crux of a larger software platform for microfluidic design. Algorithms are presented here for automated flow layer design and post-processing for area reduction and to automate the process of high-throughput conversions. It concludes by introducing a suite of benchmarks and design metrics to facilitate unbiased comparisons between the microfluidic design automation algorithms introduced here, and future work in the space to be performed by others.