Compact Terahertz SPICE/ADS Model

We describe a compact terahertz (THz) SPICE/advanced design system (ADS) model based on the extended Enz-Krummenacher-Vittoz (EKV) MOSFET model with channel segmentation but accounting for the new physics of the electron transport at THz frequencies. The model includes the distributed Drude inductan...

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Bibliographic Details
Published inIEEE transactions on electron devices Vol. 66; no. 6; pp. 2496 - 2501
Main Authors Liu, Xueqing, Ytterdal, Trond, Kachorovskii, Valentin Yu, Shur, Michael S.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:We describe a compact terahertz (THz) SPICE/advanced design system (ADS) model based on the extended Enz-Krummenacher-Vittoz (EKV) MOSFET model with channel segmentation but accounting for the new physics of the electron transport at THz frequencies. The model includes the distributed Drude inductance representing the electron inertia. The channel segmentation allows reproducing the nonuniformity in the electron density excitations and the plasmonic oscillations at THz frequencies. The model was validated by comparing the simulation results with the analytical THz detection theory and experimental data for silicon MOSFETs and FinFETs with gate lengths ranging from 60 to 800 nm. The good agreement between the simulated and analytical results and experimental data revealed the significance of the electron inertia and demonstrated the improved validity of the model at higher frequencies with an increase in the number of segments. The model was used to simulate a novel TeraFET THz spectrometer and the resonant TeraFET THz detector. These results show the model utility for device and circuit simulations at sub-THz and THz frequencies. An important application of the THz spectrometer simulation is in the design of a single field-effect transistor (FET) THz vector detector that could be extremely useful for 5G (and beyond) line-of-sight applications.
ISSN:0018-9383
1557-9646
DOI:10.1109/TED.2019.2911485