TY  - JOUR
AU  - Choudhury, Sagarika
AU  - Baishnab, Krishna Lal
AU  - Guha, Koushik
AU  - Jakšić, Zoran
AU  - Jakšić, Olga
AU  - Iannacci, Jacopo
PY  - 2023
UR  - https://cer.ihtm.bg.ac.rs/handle/123456789/7205
AB  - This study discusses the use of a triple material gate (TMG) junctionless tunnel field-effect transistor (JLTFET) as a biosensor to identify different protein molecules. Among the plethora of existing types of biosensors, FET/TFET-based devices are fully compatible with conventional integrated circuits. JLTFETs are preferred over TFETs and JLFETs because of their ease of fabrication and superior biosensing performance. Biomolecules are trapped by cavities etched across the gates. An analytical mathematical model of a TMG asymmetrical hetero-dielectric JLTFET biosensor is derived here for the first time. The TCAD simulator is used to examine the performance of a dielectrically modulated label-free biosensor. The voltage and current sensitivity of the device and the effects of the cavity size, bioanalyte electric charge, fill factor, and location on the performance of the biosensor are also investigated. The relative current sensitivity of the biosensor is found to be about 1013. Besides showing an enhanced sensitivity compared with other FET- and TFET-based biosensors, the device proves itself convenient for low-power applications, thus opening up numerous directions for future research and applications.
PB  - MDPI
T2  - Chemosensors
T1  - Modeling and Simulation of a TFET-Based Label-Free Biosensor with Enhanced Sensitivity
VL  - 11
IS  - 5
SP  - 312
DO  - 10.3390/chemosensors11050312
ER  - 

@article{
author = "Choudhury, Sagarika and Baishnab, Krishna Lal and Guha, Koushik and Jakšić, Zoran and Jakšić, Olga and Iannacci, Jacopo",
year = "2023",
abstract = "This study discusses the use of a triple material gate (TMG) junctionless tunnel field-effect transistor (JLTFET) as a biosensor to identify different protein molecules. Among the plethora of existing types of biosensors, FET/TFET-based devices are fully compatible with conventional integrated circuits. JLTFETs are preferred over TFETs and JLFETs because of their ease of fabrication and superior biosensing performance. Biomolecules are trapped by cavities etched across the gates. An analytical mathematical model of a TMG asymmetrical hetero-dielectric JLTFET biosensor is derived here for the first time. The TCAD simulator is used to examine the performance of a dielectrically modulated label-free biosensor. The voltage and current sensitivity of the device and the effects of the cavity size, bioanalyte electric charge, fill factor, and location on the performance of the biosensor are also investigated. The relative current sensitivity of the biosensor is found to be about 1013. Besides showing an enhanced sensitivity compared with other FET- and TFET-based biosensors, the device proves itself convenient for low-power applications, thus opening up numerous directions for future research and applications.",
publisher = "MDPI",
journal = "Chemosensors",
title = "Modeling and Simulation of a TFET-Based Label-Free Biosensor with Enhanced Sensitivity",
volume = "11",
number = "5",
pages = "312",
doi = "10.3390/chemosensors11050312"
}

Choudhury, S., Baishnab, K. L., Guha, K., Jakšić, Z., Jakšić, O.,& Iannacci, J.. (2023). Modeling and Simulation of a TFET-Based Label-Free Biosensor with Enhanced Sensitivity. in Chemosensors
MDPI., 11(5), 312.
https://doi.org/10.3390/chemosensors11050312

Choudhury S, Baishnab KL, Guha K, Jakšić Z, Jakšić O, Iannacci J. Modeling and Simulation of a TFET-Based Label-Free Biosensor with Enhanced Sensitivity. in Chemosensors. 2023;11(5):312.
doi:10.3390/chemosensors11050312 .

Choudhury, Sagarika, Baishnab, Krishna Lal, Guha, Koushik, Jakšić, Zoran, Jakšić, Olga, Iannacci, Jacopo, "Modeling and Simulation of a TFET-Based Label-Free Biosensor with Enhanced Sensitivity" in Chemosensors, 11, no. 5 (2023):312,
https://doi.org/10.3390/chemosensors11050312 . .

TY  - JOUR
AU  - Devi, Swagata
AU  - Guha, Koushik
AU  - Jakšić, Olga
AU  - Baishnab, Krishna Lal
AU  - Jakšić, Zoran
PY  - 2022
UR  - https://cer.ihtm.bg.ac.rs/handle/123456789/5373
AB  - This work is dedicated to parameter optimization for a self-biased amplifier to be used in preamplifiers for the diagnosis of seizures in neuro-diseases such as epilepsy. For the sake of maximum compactness, which is obligatory for all implantable devices, power is to be supplied by a piezoelectric nanogenerator (PENG). Several meta-heuristic optimization algorithms and an ANN (artificial neural network)-assisted goal attainment method were applied to the circuit, aiming to provide us with the set of optimal design parameters which ensure the minimal overall area of the preamplifier. These parameters are the slew rate, load capacitor, gain–bandwidth product, maximal input voltage, minimal input voltage, input voltage, reference voltage, and dissipation power. The results are re-evaluated and compared in the Cadence 180 nm SCL environment. It has been observed that, among the metaheuristic algorithms, the whale optimization technique reached the best values at low computational cost, decreased complexity, and the highest convergence speed. However, all metaheuristic algorithms were outperformed by the ANN-assisted goal attainment method, which produced a roughly 50% smaller overall area of the preamplifier. All the techniques described here are applicable to the design and optimization of wearable or implantable circuits.
PB  - Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)
T2  - Micromachines
T1  - Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method
VL  - 13
VL  - 7
SP  - 1104
DO  - 10.3390/mi13071104
ER  - 

@article{
author = "Devi, Swagata and Guha, Koushik and Jakšić, Olga and Baishnab, Krishna Lal and Jakšić, Zoran",
year = "2022",
abstract = "This work is dedicated to parameter optimization for a self-biased amplifier to be used in preamplifiers for the diagnosis of seizures in neuro-diseases such as epilepsy. For the sake of maximum compactness, which is obligatory for all implantable devices, power is to be supplied by a piezoelectric nanogenerator (PENG). Several meta-heuristic optimization algorithms and an ANN (artificial neural network)-assisted goal attainment method were applied to the circuit, aiming to provide us with the set of optimal design parameters which ensure the minimal overall area of the preamplifier. These parameters are the slew rate, load capacitor, gain–bandwidth product, maximal input voltage, minimal input voltage, input voltage, reference voltage, and dissipation power. The results are re-evaluated and compared in the Cadence 180 nm SCL environment. It has been observed that, among the metaheuristic algorithms, the whale optimization technique reached the best values at low computational cost, decreased complexity, and the highest convergence speed. However, all metaheuristic algorithms were outperformed by the ANN-assisted goal attainment method, which produced a roughly 50% smaller overall area of the preamplifier. All the techniques described here are applicable to the design and optimization of wearable or implantable circuits.",
publisher = "Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)",
journal = "Micromachines",
title = "Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method",
volume = "13, 7",
pages = "1104",
doi = "10.3390/mi13071104"
}

Devi, S., Guha, K., Jakšić, O., Baishnab, K. L.,& Jakšić, Z.. (2022). Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method. in Micromachines
Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)., 13, 1104.
https://doi.org/10.3390/mi13071104

Devi S, Guha K, Jakšić O, Baishnab KL, Jakšić Z. Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method. in Micromachines. 2022;13:1104.
doi:10.3390/mi13071104 .

Devi, Swagata, Guha, Koushik, Jakšić, Olga, Baishnab, Krishna Lal, Jakšić, Zoran, "Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method" in Micromachines, 13 (2022):1104,
https://doi.org/10.3390/mi13071104 . .