Analytical Modeling of a Nanogap-Embedded FET for Application as a Biosensor

An analytical model of a nanogap-embedded field-effect transistor, which is termed here simply as a biotransistor, is developed in this study. A surface potential model is attained by solving a 2-D Poisson equation with approximation of a parabolic potential profile along the channel depth. The anal...

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Bibliographic Details
Published in:IEEE transactions on electron devices 2010-12, Vol.57 (12), p.3477-3484
Main Authors: CHOI, Ji-Min, HAN, Jin-Woo, CHOI, Sung-Jin, CHOI, Yang-Kyu
Format: Article
Language:English
Subjects:
2-D modeling
2-D Poisson equation
Applied sciences
Biological and medical sciences
Biosensors
Biotechnology
Biotransistor
Devices
Dielectric-modulated field-effect transistor (DMFET)
Electronics
Exact sciences and technology
FETs
field-effect transistor (FET)-type biosensor
Fundamental and applied biological sciences. Psychology
Mathematical analysis
Methods. Procedures. Technologies
Miscellaneous
Modeling
Nanocomposites
nanogap
nanogap-embedded FET
Nanomaterials
Nanostructure
Others
Poisson equation
Poisson equations
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Sensitivity
surface potential
Threshold voltage
Transistors
Various methods and equipments
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Summary:An analytical model of a nanogap-embedded field-effect transistor, which is termed here simply as a biotransistor, is developed in this study. A surface potential model is attained by solving a 2-D Poisson equation with approximation of a parabolic potential profile along the channel depth. The analytical threshold voltage is then derived from the surface potential model to comprise the unique feature of the biotransistor, which acts as a biosensor. A shift of the threshold voltage was used as a metric to ascertain the sensitivity after the biomolecule interacts with the biotransistor. Various device parameters were investigated in the developed analytical model. The characteristic trend is supported and verified via a simulation. Hence, the proposed model can provide a useful guideline for the optimal design and fabrication of a biotransistor.
ISSN:0018-9383
1557-9646
DOI:10.1109/TED.2010.2076152