Simulation of Microelectrode Impedance Changes Due to Cell Growth

Huang, Xiaoqiu; Nguyen, Duc Khuong; Greve, David W.; Domach, Michael M.

doi:10.1109/jsen.2004.831302

Cited by 108 publications

(104 citation statements)

References 13 publications

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“…It can be appreciated how the presence of the cell changes the measured impedance, with the biggest change recorded at a frequency near to 10 5 Hz. This also corroborates the study carried out by (Huang, 2004). Another way of representing the impedance magnitude is to observe the impedance changes in the system with the cell on top with respect to the microelectrode system without cell.…”

Section: Comsol Simulationssupporting

confidence: 87%

“…It is difficult to find a theoretical value for K w , which in some works seems to be a parameter that is included in the model to adapt the model to experimental measurements (Huang, 2004). In other works, this impedance is not taken into account, because it is considered negligible for the materials and frequency range used in electrophysiological experiments (Joye, 2008).…”

Section: Warburg Impedance (Z W )mentioning

confidence: 99%

“…www.intechopen.com Figure 6 shows an example of a two-electrode impedance sensor useful for the ECIS technique: e 1 is called the sensing electrode and e 2 the reference electrode. Electrodes can be manufactured in CMOS process with metal layers (Huang, 2004) or using post-processing steps (Manickam, 2010). The cell location on top of e 1 must be detected.…”

Section: Comsol Simulationsmentioning

confidence: 99%

“…The cell location on top of e 1 must be detected. Circuit models developed to describe electrode-cell interfaces (Huang 2004, Joye 2008 contain technology process information and take the cell-electrode overlap area as their main parameter. The correct interpretation of these models gives information for: a) electrical simulation: parametrized models can be used to update the electrode circuit in terms of its overlap with cells, b) imaging reconstruction: electrical signals measured with sensors can be associated with a given overlap area, making it possible to obtain the actual covering on the electrode from experimental results.…”

Section: Comsol Simulationsmentioning

confidence: 99%

“…2), and the values for the conductivity and permittivity of the electrical double layer were calculated following the same expression as shown eq. (6), with the same values for K w and C I as those mentioned in (Huang, 2004). Conductivity of the cell and the medium was also set to 1.5 S/m in our work.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Cell Biometrics Based on Bio-Impedance Measurements

Yufera¹,

Olmo²,

Daza³

et al. 2011

Advanced Biometric Technologies

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Section: Comsol Simulationssupporting

confidence: 87%

Section: Warburg Impedance (Z W )mentioning

confidence: 99%

Section: Comsol Simulationsmentioning

confidence: 99%

Section: Comsol Simulationsmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Cell Biometrics Based on Bio-Impedance Measurements

Yufera¹,

Olmo²,

Daza³

et al. 2011

Advanced Biometric Technologies

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CMOS Impedance Sensor

2018

CMOS Integrated Lab‐on‐a‐Chip System for Personalized Biomedical Diagnosis

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Design and 3D modeling investigation of a microfluidic electrode array for electrical impedance measurement of single yeast cells

et al. 2021

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High‐resolution microscopic imaging may cause intensive image processing and potential impact of light irradiation on yeast replicative lifespan (RLS). Electrical impedance spectroscopy (EIS) could be alternatively used to perform high‐throughput and label‐free yeast RLS assays. Prior to fabricating EIS‐integrated microfluidic devices for yeast RLS determination, systematic modeling and theoretical investigation are crucial for device design and optimization. Here, we report three‐dimensional (3D) finite‐element modeling and simulations of EIS measurement in a microfluidic single yeast in situ impedance array (SYIIA), which is designed by patterning an electrode matrix underneath a cell‐trapping array. SYIIA was instantiated and modeled as a 5 × 5 sensing array comprising 25 units for cell immobilization, culturing, and time‐lapse EIS recording. Simulations of yeast growing and budding in a sensing unit demonstrated that EIS signals enable the characterization of cell growth and daughter‐cell dissections. In the 5 × 5 sensing array, simulation results indicated that when monitoring a target cell, daughter dissections in its surrounding traps may induce variations of the recorded EIS signals, which could cause mistakes in identifying target daughter‐cell dissections. To eliminate the mis‐identifications, electrode array pitch was optimized. Therefore, the results could conduct the design and optimization of microfluidic electrode‐array‐integrated devices for high‐throughput and accurate yeast RLS assays.

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Simulation of Microelectrode Impedance Changes Due to Cell Growth

Cited by 108 publications

References 13 publications

Cell Biometrics Based on Bio-Impedance Measurements

Cell Biometrics Based on Bio-Impedance Measurements

CMOS Impedance Sensor

Design and 3D modeling investigation of a microfluidic electrode array for electrical impedance measurement of single yeast cells

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