Characterization of wax valving and μPIV analysis of microscale flow in paper-fluidic devices for improved modeling and design. Issue 14 (28th June 2022)

• Record Type: Journal Article
• Authors: Newsham, Emilie I.; Phillips, Elizabeth A.; Ma, Hui; Chang, Megan M.; Wereley, Steven T.; Linnes, Jacqueline C.
• Is Part Of: Lab on a chip. Volume 22:Issue 14(2022)
• Page Start: 2741
• Page End: 2752
• Publication Date: 2022-06-28
• Subjects: Miniature electronic equipment -- Periodicals; Combinatorial chemistry -- Periodicals; Biotechnology -- Periodicals; 543.0813
• DOI: 10.1039/d2lc00297c
• Languages: English
• ISSNs: 1473-0197

Abstract

Abstract : Wax valves were modeled and optimized for use in multi-step paper-fluidic devices. Micro-particle image velocimetry quantified microscale flow in nitrocellulose. Abstract : Paper-fluidic devices are a popular platform for point-of-care diagnostics due to their low cost, ease of use, and equipment-free detection of target molecules. They are limited, however, by their lack of sensitivity and inability to incorporate more complex processes, such as nucleic acid amplification or enzymatic signal enhancement. To address these limitations, various valves have previously been implemented in paper-fluidic devices to control fluid obstruction and release. However, incorporation of valves into new devices is a highly iterative, time-intensive process due to limited experimental data describing the microscale flow that drives the biophysical reactions in the assay. In this paper, we tested and modeled different geometries of thermally actuated valves to investigate how they can be more easily implemented in an LFIA with precise control of actuation time, flow rate, and flow pattern. We demonstrate that bulk flow measurements alone cannot estimate the highly variable microscale properties and effects on LFIA signal development. To further quantify the microfluidic properties of paper-fluidic devices, micro-particle image velocimetry was used to quantify fluorescent nanoparticle flow through the membranes and demonstrated divergent properties from bulk flow that may explain additional variability in LFIA signal generation. Altogether, we demonstrate that a more robust characterization of paper-fluidic devices can permit fine-tuning of parameters for precise automation of multi-step assays and inform analytical models for more efficient design.