LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

2-D Analytical Drain Current Model of Double-Gate Heterojunction TFETs With a SiO2/HfO2 Stacked Gate-Oxide Structure

Photo from wikipedia

A continuous 2-D analytical drain current model of double-gate (DG) heterojunction tunnel field-effect transistors (HJTFETs) with a SiO2/HfO2 stacked gate-oxide structures has been presented in this paper. The surface potential… Click to show full abstract

A continuous 2-D analytical drain current model of double-gate (DG) heterojunction tunnel field-effect transistors (HJTFETs) with a SiO2/HfO2 stacked gate-oxide structures has been presented in this paper. The surface potential model has been developed by considering the effect of accumulation/inversion charges and depletion region at source/channel and drain/channel junctions. The electric field-dependent band-to-band tunneling generation rate has been derived from the surface potential model. The tangent line approximation method has been used to calculate the drain current of DG HJTFETs. The developed model is valid for all regions (subthreshold to strong accumulation/inversion region) of operation. The model has been developed for Si/Ge hetero and Si homojunction-based tunnel field-effect transistor devices. The model is also applicable for other structures such as III–V materials-based InAs/GaSb DG HJTFET and silicon-on-insulator-based HJTFET. The analytical model results are validated by 2-D ATLAS simulation data.

Keywords: analytical drain; drain; model double; current model; model; drain current

Journal Title: IEEE Transactions on Electron Devices
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.