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Analytical model and sensitivity analysis of a gate-engineered dielectric modulated junctionless nanowire transistor-based biosensor
- Publication Year :
- 2021
- Publisher :
- Elsevier, 2021.
-
Abstract
- In this chapter, we present the analytical model of a gate-engineered dielectric modulated junctionless nanowire transistor to efficiently detect biomolecules electrically and in a label-free manner. The change in the threshold voltage of the device due to the immobilization of the biomolecules in the nanogap cavity region has been considered the chief sensing metric for the detection of biomolecules. Per the principal of dielectric modulation, the presence of biomolecules in the nanogap cavity region causes a change in the surface potential and channel center potential of the device, which in turn causes a change in the threshold voltage of the device. In this chapter, an analytical model of channel center potential has been developed by solving two-dimensional Poisson’s equation in the channel region using the parabolic approximation method. The proposed model provides analytical expression of electrostatic potential distribution along the channel. Furthermore, an expression of threshold voltage of the device and expression of current in different regions has been obtained from this potential model developed. To efficiently detect the biomolecules, the variation of the threshold voltage as the sensitivity parameter has been analyzed. The results clearly reveal that a gate-engineered junctionless nanowire transistor provides higher sensitivity over its non-gate-engineered counterpart. Moreover, the effect of different device dimensional parameters and position of the nanogap cavity on the sensitivity of the biosensor has been investigated to study the changes in the permittivity of the dielectric region due to the presence of biomolecules in the nanocavity region. The results obtained from the analytical model have been verified and validated through comparison with TCAD device simulator results.
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi...........dfc7f916c468fcedc06106720ee47e1d
- Full Text :
- https://doi.org/10.1016/b978-0-323-85172-5.00008-3