Modeling and performance analysis of Nanocavity Embedded Dopingless T-shaped Tunnel FET with high-K gate dielectric for biosensing applications

Priya, G. Lakshmi; Venkatesh, M.; Agarwal, Lucky; Samuel, T. S. Arun

doi:10.1007/s00339-022-06081-z

Cited by 6 publications

(2 citation statements)

References 35 publications

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“…This impact reduces the device's ambipolar tunnelling breadth even if just a slight alteration is made to the dielectric property of the target proteins (Refs. [36][37][38].…”

Section: Resultsmentioning

confidence: 99%

Surface Potential Analysis of Dual Material Gate Silicon-Based Ferroelectric TFET for Biosensing Application

Venkatesh,

Parthasarathy,

Arun Kumar

2024

ECS J. Solid State Sci. Technol.

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By means of a dielectric modulation method, this research offers the first ever 2D analytical model for the surface potential of a dual material gate Ferroelectric-tunnel-field effect transistor (DMG-Fe-TFET) device used in an enzyme-free biosensor. Compared to a device with a single material gate, the sensitivity of a device with a gate made of two distinct metals (M1-M2) is improved by an increase in tunnelling width at the secondary tunnelling junction. This model accounts for the change in surface potential caused by varying the value, position, and fill factor of the target biomolecules. Several distinct device architectures are used to enhance the efficiency of the envisaged Fe-TFET in the nanoscale range. The DMG-Fe-TFET is one of many cutting-edge FET topologies that can reduce the impact of short-channel effects because of its adaptability. The surface potential can be expressed by computing the two-dimensional Poisson's equation using the parabolic-potential approach. The critical voltage is determined by using the minimal surface potential model. The percent change in the threshold voltage is used to determine the sensitivity of the model. Researchers have investigated how the dimensions of the Nano cavity and other parts of the device affect its sensitivity.

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“…This impact reduces the device's ambipolar tunnelling breadth even if just a slight alteration is made to the dielectric property of the target proteins (Refs. [36][37][38].…”

Section: Resultsmentioning

confidence: 99%

Surface Potential Analysis of Dual Material Gate Silicon-Based Ferroelectric TFET for Biosensing Application

Venkatesh,

Parthasarathy,

Arun Kumar

2024

ECS J. Solid State Sci. Technol.

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“…Recently, researchers are looking towards non-volatile information devices with low power consumption, such as tunnel FETs [1][2][3][4] and negative capacitance FETs [5,6] for logic application and ferroelectric FETs (FeFETs) for memory application. FeFETs have been attracting much attention in non-volatile memory (NVM) application due to the advantages of the scalability and CMOS compatibility for hafniabased ferroelectric material [7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Temperature effects on the performance of ferroelectric FET with random grain phase variation for non-volatile memory application

Hsu

et al. 2023

Semicond. Sci. Technol.

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We report the temperature effects on the performance of ferroelectric field-effect transistor(FeFET) based non-volatile memory (NVM) considering random grain phase variation in the ferroelectric layer through simulation. Based on the FE temperature effect model that accounts for both the transistor and ferroelectric degradation, we demonstrate that: 1) at a certain temperature, the memory window (MW) decreases with pronounced effect on low threshold voltage shift and its variation increases as the FE phase decreases; 2) with the temperature increases, the MW decreases with pronounced effect on high threshold voltage shift. The random grain phase variation further exacerbates the MW distribution, thus degrading the sensing margin. These results may provide insights for device design of high-performance FeFET-based NVMs.

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Design and Modeling of Gate Engineered Tunnel Field-Effect Transistor

Venkatesh,

Andrew Roobert,

Mani

et al. 2024

Handbook of Emerging Materials for Semiconductor Industry

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Modeling and performance analysis of Nanocavity Embedded Dopingless T-shaped Tunnel FET with high-K gate dielectric for biosensing applications

Cited by 6 publications

References 35 publications

Surface Potential Analysis of Dual Material Gate Silicon-Based Ferroelectric TFET for Biosensing Application

Surface Potential Analysis of Dual Material Gate Silicon-Based Ferroelectric TFET for Biosensing Application

Temperature effects on the performance of ferroelectric FET with random grain phase variation for non-volatile memory application

Design and Modeling of Gate Engineered Tunnel Field-Effect Transistor

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