Unique and Unclonable Capacitive Sensors

Karuthedath, Cyril Baby; Schwesinger, Norbert

doi:10.1109/jsen.2018.2846358

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…Due to the appearance of non-overlapping semicircular curves in the Nyquist plots which have been shown in Figures 4 and 5, it can be directly estimated that the associated resistor (R) and capacitor (C) can be used for describing the physical structures of the biochips [20]. Based on this initial estimation and the experimental impedance data (Figure 8), the transferring of the equivalent circuits, based on the physical mechanism of the biochips (Figure 9a,c) to the ones based on the assumed associated resistor-capacitor RC pairs (Figure 9b,d), can be validated.…”

Section: Discussionmentioning

confidence: 99%

P-N Junction-Based Si Biochips with Ring Electrodes for Novel Biosensing Applications

Kiani

Vogel

et al. 2019

Biosensors

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In this work, we report on the impedance of p-n junction-based Si biochips with gold ring top electrodes and unstructured platinum bottom electrodes which allows for counting target biomaterial in a liquid-filled ring top electrode region. The systematic experiments on p-n junction-based Si biochips fabricated by two different sets of implantation parameters (i.e. biochips PS5 and BS5) are studied, and the comparable significant change of impedance characteristics in the biochips in dependence on the number of bacteria suspension, i.e., Lysinibacillus sphaericus JG-A12, in Deionized water with an optical density at 600 nm from OD600 = 4–16 in the electrode ring region is demonstrated. Furthermore, with the help of the newly developed two-phase electrode structure, the modeled capacitance and resistance parameters of the electrical equivalent circuit describing the p-n junction-based biochips depend linearly on the number of bacteria in the ring top electrode region, which successfully proves the potential performance of p-n junction-based Si biochips in observing the bacterial suspension. The proposed p-n junction-based biochips reveal perspective applications in medicine and biology for diagnosis, monitoring, management, and treatment of diseases.

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Section: Discussionmentioning

confidence: 99%

P-N Junction-Based Si Biochips with Ring Electrodes for Novel Biosensing Applications

Kiani

Vogel

et al. 2019

Biosensors

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“…The sensitivity of the capacitive pressure/force sensor is also impacted by the elastic coefficient of the deformation layer. The sensor covered with a PDMS (polydimethlysiloxane) membrane can perceive the tilt angle, which is caused by the pressure from the conductive balls upon the PDMS membrane [82]. (b) A metallic ball is placed in a plastic tube which is fixed on a capacitive sensor, and the tilt angle can be determined by the analysis from the capacitive variance trends and the capacitance variations [83].…”

Section: B Capacitive Displacement Sensing For Indirect Measurementsmentioning

confidence: 99%

“…With similar measurement method of capacitive force sensor mentioned above, Karuthedath and Schwesinger [82] used a capacitive sensor to perceive the tilt angle of the polydimethylsiloxane (PDMS) membrane (as shown in Figure 14(a)). Lee et al [83] proposed another tilt angle measurement approach (as shown in Figure 14(b)).…”

Section: B Capacitive Displacement Sensing For Indirect Measurementsmentioning

confidence: 99%

A Review on Applications of Capacitive Displacement Sensing for Capacitive Proximity Sensor

et al. 2020

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Capacitive proximity sensors (CPSs) are ubiquitous because of their simple design, low cost and low consumption. Capacitive displacement sensing, as one of the three sensing modalities, works for long distance and can be unitized to measure more physical quantities compared with capacitive volume and deformation sensing. In this paper, we firstly introduce the concept of capacitive displacement sensing. After that, we present applications of capacitive displacement sensing under three broad categories: distance measurements, indirect measurements, and the applications applied in smart environments. Finally, we discuss the challenges and possible solutions for CPSs development. We show that both the detection range and accuracy of CPS can be improved by multi-sensor fusion, and the application scenarios can be extensive through machine/deep learning approaches. We aim to provide a comprehensive, and state-of-theart review of the capacitive displacement sensing, and inspire more researchers and developers to find wide application perspectives.INDEX TERMS Capacitive proximity sensor (CPS), capacitive displacement sensing, distance measurement, indirect measurement, smart environment.

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Section: Modelingmentioning

confidence: 99%

“…The Nyquist plots of the biochips reveal two imperfect semicircles. Two CPEs are used to model these two imperfect semicircles with the center below the x-axis in Nyquist plot ( Figure 3a) [17]. CPE impedance is calculated as Z = 1/(Q0 (jω)n), where Q0 has the numerical value of admittance at ω = 1 rad/s with the unit S. The phase angle of the CPE impedance is frequency independent and it has a constant value of −(90 n) degrees and n is natural numbers.…”

Section: Modelingmentioning

confidence: 99%

Disturbing-Free Determination of Yeast Concentration in DI Water and in Glucose Using Impedance Biochips

Kiani

Vogel

et al. 2020

Biosensors

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Deionized water and glucose without yeast and with yeast (Saccharomyces cerevisiae) of optical density OD600 that ranges from 4 to 16 has been put in the ring electrode region of six different types of impedance biochips and impedance has been measured in dependence on the added volume (20, 21, 22, 23, 24, 25 µL). The measured impedance of two out of the six types of biochips is strongly sensitive to the addition of both liquid without yeast and liquid with yeast and modelled impedance reveals a linear relationship between the impedance model parameters and yeast concentration. The presented biochips allow for continuous impedance measurements without interrupting the cultivation of the yeast. A multiparameter fit of the impedance model parameters allows for determining the concentration of yeast (cy) in the range from cy = 3.3 × 107 to cy = 17 × 107 cells/mL. This work shows that independent on the liquid, i.e., DI water or glucose, the impedance model parameters of the two most sensitive types of biochips with liquid without yeast and with liquid with yeast are clearly distinguishable for the two most sensitive types of biochips.

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Unique and Unclonable Capacitive Sensors

Cited by 6 publications

References 24 publications

P-N Junction-Based Si Biochips with Ring Electrodes for Novel Biosensing Applications

P-N Junction-Based Si Biochips with Ring Electrodes for Novel Biosensing Applications

A Review on Applications of Capacitive Displacement Sensing for Capacitive Proximity Sensor

Disturbing-Free Determination of Yeast Concentration in DI Water and in Glucose Using Impedance Biochips

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