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Effectiveness of Graphene Nano-Ribbon Tunnel Field Effect Transistor for Bio-Molecular Identification
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This paper examines the Double gate Graphene Nano-ribbon Tunnel Field-Effect Transistor (DG GNR TFET) for bio-sensing applications. The biomolecules are Streptavidin, APTES, Biotin, DNA and protein. Differentiation between biomolecules is possible based on dielectric permittivity and charge concentration. The protein switching ratio ([Formula: see text]/[Formula: see text] is 25.7 times that of Streptavidin and around 300 times that without any biomolecule in the cavity. The maximum current sensitivity among the biomolecules is achieved by protein biomolecule for VGS = 0.7[Formula: see text]V. The sub-threshold swing obtained for a biomolecule in DG GNR TFET is 40 mV/dec compared to that of 80[Formula: see text]mV/dec for an empty cavity. The device characteristics reveal that the drain current is maximum with a biomolecule in a cavity compared to an empty cavity. Results obtained emphasize that double gate Graphene Nano-Ribbon TFET is suitable as a biosensor. The simulations are executed using Silvaco Technology Computer Aided Design (TCAD).
Title: Effectiveness of Graphene Nano-Ribbon Tunnel Field Effect Transistor for Bio-Molecular Identification
Description:
This paper examines the Double gate Graphene Nano-ribbon Tunnel Field-Effect Transistor (DG GNR TFET) for bio-sensing applications.
The biomolecules are Streptavidin, APTES, Biotin, DNA and protein.
Differentiation between biomolecules is possible based on dielectric permittivity and charge concentration.
The protein switching ratio ([Formula: see text]/[Formula: see text] is 25.
7 times that of Streptavidin and around 300 times that without any biomolecule in the cavity.
The maximum current sensitivity among the biomolecules is achieved by protein biomolecule for VGS = 0.
7[Formula: see text]V.
The sub-threshold swing obtained for a biomolecule in DG GNR TFET is 40 mV/dec compared to that of 80[Formula: see text]mV/dec for an empty cavity.
The device characteristics reveal that the drain current is maximum with a biomolecule in a cavity compared to an empty cavity.
Results obtained emphasize that double gate Graphene Nano-Ribbon TFET is suitable as a biosensor.
The simulations are executed using Silvaco Technology Computer Aided Design (TCAD).
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