AitF: EXPL: Algorithmic Fluid Concentration Management for Programmable Microfluidics

University Of California-Riverside, Riverside CA

Investigators

Abstract

The miniaturization of technology has produced not only programmable microprocessor circuits, but also programmable lab-on-a-chip (PLoC) systems for microfluidics. These systems control tiny fluid droplets, allowing precise mixing and testing, that can be developed into environmental monitors, malaria diagnostics, or blood tests for cancer cells. As with microprocessors, programming a lab on a chip takes knowledge of what the chip can and cannot do, and a suitable language in which to express the commands. This project 1) develops a theory of computational complexity for designing microfluidic devices that produce fluid mixtures with desired concentrations, 2) creates a domain-specific language (including an Application Program Interface, or API and a compiler) for these devices, 3) fabricates and tests devices, and 4) explores the broader impacts of the ability to program complex biochemical reactions that include fluid concentration steps. The project results will make PLoC systems much easier to use, which the PIs will first demonstrate with students, including those from underrepresented groups, and then through tutorials presented at scientific meetings to promote the use of PLoC technologies among the broader scientific community. This project investigates the complexity and approximability of algorithms to generate one or more discrete fluid droplets having a desired concentration, e.g., a sample diluted to 10%, 15%, etc., with objectives such as minimizing the number of dilution steps, minimizing waste, minimizing reactant usage, etc. These algorithms will be generalized to produce of a stream of droplets having desired time-dependent concentrations. Meanwhile, a collection of representative PLoCs will be designed and fabricated on-site, along with a domain-specific language and compiler, which will allow the PLoCs to be programmed using high-level software. The algorithms developed in the course of this project will be integrated into an API that can be called from the domain-specific language. This will enable users to specify biochemical reactions that include fluid concentration generation subroutines (which are performed automatically). The system will be validated by executing these biochemical reactions using the PLoCs that have been fabricated on-site. Upon successful completion of the project, PLoC design files along with the domain-specific language specification and compiler, documentation, and tutorial material, will be released publicly to encourage other scientists to use this platform and approach to increase productivity and reduce human error in their respective laboratories.