Paper
13 February 2008 Interdigitated array microelectrode capacitive sensor for detection of paraffinophilic mycobacteria
Andrew M. Sampson, Erik T. K. Peterson, Ian Papautsky
Author Affiliations +
Abstract
Mycobacterium Avium Complex (MAC) is an opportunistic pathogen that threatens public health and has high clinical relevance. While culture-based and molecular biology techniques for identification are available, these methods are prone to error and require weeks to perform. There is a critical need for improved portable lab-on-a-chip sensor technology which will enable accurate and rapid point-of-care detection of these microorganisms. In this work, a new capacitive sensing strategy is explored utilizing interdigitated array (IDA) microelectrodes and exploiting the paraffinophilic nature of MAC. In this approach, paraffin wax is deposited over IDA microelectrodes to selectively extract these microorganisms from samples. As bacteria consume the dielectric paraffin layer, the charging current of the IDA capacitor changes to facilitate detection. Several IDA geometries were designed and simulated using CFD-ACE+ modeling software and compared with mathematical models. Capacitance of fabricated devices was determined using a charge-based capacitance measurement (CBCM) technique. Modeling and experimental results were in good agreement. Detection of femto-Farad changes in capacitance is possible, making this a feasible technique for sensing small changes in the paraffin for detection of paraffinophilic MAC.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrew M. Sampson, Erik T. K. Peterson, and Ian Papautsky "Interdigitated array microelectrode capacitive sensor for detection of paraffinophilic mycobacteria", Proc. SPIE 6886, Microfluidics, BioMEMS, and Medical Microsystems VI, 68860X (13 February 2008); https://doi.org/10.1117/12.768686
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Cited by 2 scholarly publications and 1 patent.
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KEYWORDS
Capacitance

Mathematical modeling

Sensors

Electrodes

Capacitors

Bacteria

Biosensors

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