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MicroFludic Coulter Counter

Electrical impedance-based sensing, or the Coulter technique, provides a compact platform for cell and particle counting, but biomedical applications will be greatly expanded through computer-aided optimization. The Coulter technique enables rapid analysis of cells suspended in a stream for a variety of applications from fundamental biological research to drug development.  In this technique, the cells or particles are suspended in a conducting solution and produce a characteristic voltage signal when they interrupt the electrical path. Such electrical measurements promise a dramatically smaller and cheaper system than the competing technology of optical flow cytometry, in which the cell samples are classified according to their light-scattering properties. However, fundamental research is still needed for the Coulter microfluidic device to compete with the richness of data available through conventional optical flow cytometry.

To develop a technology base comparable to that of optical cytometry, we propose to model a microfluidic Coulter counter using computational fluid dynamics (CFD). The model will take into account particle motion, fluid flow, temperature-dependent viscosity, and mass/heat transfer to determine the spatial distribution of ions in the surrounding electrolyte during operation of the device. The ion distribution determines the shape of the conductivity waveform, so optimization will be directed at generating extreme changes in ion distribution when particles pass by the electrodes. The electrode and channel geometry affect the ion distribution, as does the presence of photothermal cell labels that absorb infrared or radio-frequency waves.

This work is in collaboration with other researchers from the electrical and computer engineering department and from medical school at the University of Louisville. Optical microscopy experiments with ion-reactive dye in devices provide verification and feedback to the model.  We use the design of experiment and response-surface techniques to identify the optimal configuration. Results will enable optimization of device geometry for high throughput and optimization of cell-labeling protocols for determining presence of specific disease markers from the electrical signal.

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