Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/143756
Title: A 3D-printed modular magnetic digital microfluidic architecture for on-demand bioanalysis
Authors: Kanitthamniyom, Pojchanun
Zhou, Aiwu
Feng, Shilun
Liu, Aiqun
Vasoo, Shawn
Zhang, Yi
Keywords: Engineering::Mechanical engineering
Issue Date: 2020
Source: Kanitthamniyom, P., Zhou, A., Feng, S., Liu, A., Vasoo, S., & Zhang, Y. (2020). A 3D-printed modular magnetic digital microfluidic architecture for on-demand bioanalysis. Microsystems and Nanoengineering, 6(1), doi:10.1038/s41378-020-0152-4
Journal: Microsystems and Nanoengineering
Abstract: Magnetic digital microfluidics (MDM) manipulates fluids in the form of droplets on an open substrate, and incorporates surface energy traps (SETs) to facilitate the droplet manipulation. Conventional MDM devices are fabricated monolithically, which makes it difficult the modify the device configuration without completely overhauling the original design. In this paper, we present a modular MDM architecture that enables rapid on-demand configuration and re-configuration of MDM platforms for customized bioanalyses. Each modular component contains a SET and a Lego-like antistud that fits onto a base board with Lego-like studs. We illustrate the versatility of the modular MDM architecture in biomarker sensing, pathogen identification, antibiotic resistance determination and biochemical quantification by demonstrating immunoassays, phenotypical assays and enzymatic assays on various modular MDM platforms configured on demand to accomplish the fluidic operations required by assorted bioanalytical assays. The modular MDM architecture promises great potential for point-of-care diagnostics by offering on-demand customization of testing platforms for various categories of diagnostic assays. It also provides a new avenue for microfluidic assay development with its high configurability which would significantly reduce the time and cost of the development cycle.
URI: https://hdl.handle.net/10356/143756
ISSN: 2055-7434
DOI: 10.1038/s41378-020-0152-4
Rights: © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SC3DP Journal Articles

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