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Design and modeling of electrode networks for code-division multiplexed resistive pulse sensing in microfluidic devices

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Abstract

A typical microfluidic device sorts, captures or fractionates sample constituents by exposing them to discriminating microenvironments. Direct electronic acquisition of such manipulation by a network of integrated sensors can provide a fast, integrated readout, replacing otherwise required microscopy. We have recently introduced a sensor technology, Microfluidic CODES, which allows us to multiplex resistive pulse sensors on a microfluidic device. Microfluidic CODES employs a network of micromachined coplanar electrodes such that particles passing over these electrodes produce distinguishable code sequences. In this paper, we explain the design process to specifically generate an orthogonal digital code set for an efficient and accurate demultiplexing of the sensor signals. We also introduce an equivalent circuit model for a network of code-multiplexed resistive pulse sensors by utilizing the Foster–Schwan model and conformal mapping, to model dynamic cell–electrode interaction in a non-uniform electric field. Our results closely match with both experimental measurements using cell lines and finite element analysis. The coding and modeling framework presented here will enable the design of code-division multiplexed resistive pulse sensors optimized to produce desired waveform patterns to ensure reliable and efficient decoding.

Graphical abstract: Design and modeling of electrode networks for code-division multiplexed resistive pulse sensing in microfluidic devices

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Publication details

The article was received on 21 May 2017, accepted on 30 Jun 2017 and first published on 30 Jun 2017


Article type: Paper
DOI: 10.1039/C7LC00545H
Citation: Lab Chip, 2017, Advance Article
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    Design and modeling of electrode networks for code-division multiplexed resistive pulse sensing in microfluidic devices

    R. Liu, W. Waheed, N. Wang, O. Civelekoglu, M. Boya, C. Chu and A. F. Sarioglu, Lab Chip, 2017, Advance Article , DOI: 10.1039/C7LC00545H

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