Capacitance-Based Droplet Position Sensing Optimization Through Digital Microfluidic Parameters

Abstract

Design of a closed-loop droplet position control is an essential step towards the development of fully automated digital microfluidic devices. However, the performance of any closed-loop controller is ultimately limited by the accuracy and precision of the feedback sensors. In this paper, an effective capacitance based droplet sensor was designed and optimized through simulation to reduce the droplet position error. A full factorial design was conducted on the droplet sensor simulation model to observe the behavior of the position error as a function of the parameters of a digital microfluidic device. An empirical model was then fitted to the data obtained from the designed simulations and optimized to reduce the position estimate error. Results suggest that the performance of the capacitance based droplet sensor studied in this work is most dependent on the dielectric thickness, droplet radius, electrode pitch, electrode separation, filler fluid permittivity, and plate gap. Isoperformance curves of the sensor performance were obtained using the empirical model to show the interaction between digital microfluidic parameters, as well as to aid in the design of digital microfluidic devices equipped with a similar capacitance based droplet sensor.