Back to Search
Start Over
Modeling-Guided Design of Paper Microfluidic Networks: A Case Study of Sequential Fluid Delivery
- Source :
- ACS Sensors. 6:91-99
- Publication Year :
- 2020
- Publisher :
- American Chemical Society (ACS), 2020.
-
Abstract
- Paper-based microfluidic devices are popular for their ability to automate multistep assays for chemical or biological sensing at a low cost, but the design of paper microfluidic networks has largely relied on experimental trial and error. A few mathematical models of flow through paper microfluidic devices have been developed and have succeeded in explaining experimental flow behavior. However, the reverse engineering problem of designing complex paper networks guided by appropriate mathematical models is largely unsolved. In this article, we demonstrate that a two-dimensional paper network (2DPN) designed to sequentially deliver three fluids to a test zone on the device can be computationally designed and experimentally implemented without experimental trial and error. This was accomplished by three new developments in modeling flow through paper networks: (i) coupling of the Richards equation of flow through porous media to the species transport equation, (ii) modeling flow through assemblies of multiple paper materials (test membrane and wicking pad), and (iii) incorporating limited-volume fluid sources. We demonstrate the application of this model in the optimal design of a paper-based signal-enhanced immunoassay for a malaria protein, PfHRP2. This work lays the foundation for the development of a computational design toolbox to aid in the design of paper microfluidic networks. ©
- Subjects :
- Paper
Optimal design
Reverse engineering
Computer science
Microfluidics
Bioengineering
02 engineering and technology
computer.software_genre
01 natural sciences
Lab-On-A-Chip Devices
Instrumentation
Immunoassay
Fluid Flow and Transfer Processes
Mathematical model
Process Chemistry and Technology
010401 analytical chemistry
Control engineering
Microfluidic Analytical Techniques
021001 nanoscience & nanotechnology
Trial and error
0104 chemical sciences
Flow (mathematics)
Richards equation
0210 nano-technology
Convection–diffusion equation
computer
Subjects
Details
- ISSN :
- 23793694
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- ACS Sensors
- Accession number :
- edsair.doi.dedup.....ca617ddd7c55cb3b20b2638c268a4689