Validity of Capillary Imbibition Models in Paper-Based Microfluidic Applications

Paper-based microfluidics has grown continuously over the last few years. One of the most important characteristics of paper-based microfluidic devices is the ability to pump fluids with the single action of capillary forces. However, fluid flow control in paper-based microfluidic devices has been studied primarily through empirical approaches; and as paper-based microfluidic devices have become more complex, more general and precise models of fluid flow are required. Particularly difficult to model are unsaturated flow conditions, which are critical to the overall performance of paper-based analytical devices, which may contain pre-adsorbed reagents such as indicator particles or antibodies. In this work we propose an objective test and a discussion on the suitability of different models (including a novel model derived here from LET-based models) that represent fluid imbibition dynamics in paper substrates. We reproduce experimental fluid fronts with the best parameter fits of the different models to show their actual capabilities to represent the moisture content function and present an analysis of propagation of uncertainties to obtain a final objective quantification of the quality of model fits. This objective analysis will endow the paper-based microfluidics community with objective information about modeling tools to improve the designs and performance of these devices.

Automated summary

Paper-based microfluidics has been continuously growing in recent years. One of its key features is the ability to pump fluids using capillary forces. However, the control of fluid flow in paper-based microfluidic devices has primarily relied on empirical approaches, and as the devices become more complex, more accurate models are needed. This study proposes an objective test and discusses the suitability of different models for representing fluid imbibition dynamics in paper substrates. The study reproduces experimental results and analyzes the propagation of uncertainties to provide an objective quantification of model quality, which can help improve the design and performance of paper-based microfluidic devices.