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Your search keyword '"Ouledabbes, Amaria"' showing total 3 results
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3 results on '"Ouledabbes, Amaria"'

1. High-sensitivity detection of SARS-CoV-2 using optimized carbon nanotube field-effect transistor (CNTFET) geometry: a numerical approach.

Author

Zeggai, Oussama, Belarbi, Mousaab, Bouhenna, Abdesslam, Khettaf, Sami, Mouloudj, Hadj, and Ouledabbes, Amaria

Subjects
FIELD-effect transistors, CARBON analysis, SARS-CoV-2, NUMERICAL analysis, COVID-19, BIOSENSORS
Abstract

This study presents a comprehensive numerical analysis of carbon nanotube (CNT)-based fieldeffect transistor (FET) sensors designed to detect SARS-CoV-2, the virus responsible for COVID-19. While graphene-based FETs have been extensively studied, our research emphasizes the unique advantages of CNTs, including enhanced sensitivity and seamless integration into existing technologies. Through numerical simulations, we evaluated the influence of CNT geometry, specifically length and diameter, on FET sensor performance. The results demonstrate that optimized CNT geometries significantly enhance sensor sensitivity and accuracy, providing superior capabilities for the rapid and precise detection of SARS-CoV-2. These findings underscore the potential for developing reliable, fast, and cost-effective CNT-based FET biosensors for effective pandemic response and broader public health applications. [ABSTRACT FROM AUTHOR]

Published
2024
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2. Advancing Cholesterol Detection: A Simulation Study on SrTiO3-Based BioFET Biosensors

Author

Bouhenna, Abdesslam, Zeggai, Oussama, Belarbi, Mousaab, Mouloudj, Hadj, Ouledabbes, Amaria, and Khettaf, Sami

Abstract

This study presents an analytical model of a strontium titanate (SrTiO3)-based biological field-effect transistor (BioFET) for cholesterol detection. Known for its high dielectric permittivity, surface charge regulation, and superior ionic and thermal conductivity, SrTiO3enhances the functionality of biosensors. The BioFET employs a gate functionalized with a cholesterol-specific enzyme, which facilitates potentiometric measurements of cholesterol concentrations. The model establishes a quantitative relationship between cholesterol concentration and gate voltage in enzyme-immobilized SrTiO3, demonstrating the high selectivity of SrTiO3-based BioFETs for cholesterol detection. This indicates their potential in developing diagnostic tools for cholesterol-related conditions and monitoring food quality. Additionally, the analytical model effectively predicts the behavior of the detection mechanism in electrochemical BioFET biosensors, underscoring its innovative application in fields such as microelectronics, sensors, and catalysis.

Published
2024
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