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Open AccessArticle

A High-Throughput Microfluidic Magnetic Separation (µFMS) Platform for Water Quality Monitoring

1
Interdisciplinary Microsystems Group, Department of Electrical and Computer Engineering; University of Florida, Gainesville, FL 32611, USA
2
Institute of Food and Agricultural Sciences, Department of Agricultural and Biological Engineering; University of Florida, Gainesville, FL 32611, USA
*
Author to whom correspondence should be addressed.
Micromachines 2020, 11(1), 16; https://doi.org/10.3390/mi11010016
Received: 19 November 2019 / Revised: 11 December 2019 / Accepted: 19 December 2019 / Published: 22 December 2019
(This article belongs to the Special Issue Biosensors for Pathogen Detection)
The long-term aim of this work is to develop a biosensing system that rapidly detects bacterial targets of interest, such as Escherichia coli, in drinking and recreational water quality monitoring. For these applications, a standard sample size is 100 mL, which is quite large for magnetic separation microfluidic analysis platforms that typically function with <20 µL/s throughput. Here, we report the use of 1.5-µm-diameter magnetic microdisc to selectively tag target bacteria, and a high-throughput microfluidic device that can potentially isolate the magnetically tagged bacteria from 100 mL water samples in less than 15 min. Simulations and experiments show ~90% capture efficiencies of magnetic particles at flow rates up to 120 µL/s. Also, the platform enables the magnetic microdiscs/bacteria conjugates to be directly imaged, providing a path for quantitative assay. View Full-Text
Keywords: high-throughput; magnetic isolation; magnetic separation; magnetic microdiscs; microfluidics; bacteria; Escherichia coli; water quality high-throughput; magnetic isolation; magnetic separation; magnetic microdiscs; microfluidics; bacteria; Escherichia coli; water quality
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MDPI and ACS Style

Castillo-Torres, K.Y.; McLamore, E.S.; Arnold, D.P. A High-Throughput Microfluidic Magnetic Separation (µFMS) Platform for Water Quality Monitoring. Micromachines 2020, 11, 16.

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