Time-dependent simulation of particle and displacement currents in THz graphene transistors

TL;DR

This paper investigates the THz noise in dual-gate graphene transistors through time-dependent simulations of particle and displacement currents, revealing how Klein tunneling and energy injection affect noise and signal-to-noise ratio.

Contribution

It introduces a detailed time-dependent simulation approach for THz currents in graphene transistors, analyzing noise sources and proposing a new strategy to optimize their cut-off frequency.

Findings

Klein tunneling increases noise without raising current.

Shorter vertical height enhances maximum frequency of the PSD.

Positive-negative energy injection degrades the signal-to-noise ratio.

Abstract

Although time-independent models provide very useful dynamical information with a reduced computational burden, going beyond the quasi-static approximation provides enriched information when dealing with TeraHertz (THz) frequencies. In this work, the THz noise of dual-gate graphene transistors with DC polarization is analyzed from a careful simulation of the time-dependent particle and displacement currents. From such currents, the power spectral density (PSD) of the total current fluctuations are computed at the source, drain and gate contacts. The role of the lateral dimensions of the transistors, the Klein tunneling and the positive-negative energy injection on the PSD are analyzed carefully. Through the comparison of the PSD with and without Band-to-Band tunneling and graphene injection, it is shown that the unavoidable Klein tunneling and positive-negative energy injection in graphene structures imply an increment of noise without similar increment on the current, degrading the (either low or high frequency) signal-to-noise ratio. Finally, it is shown that the shorter the vertical height (in comparison with the length of the active region in the transport direction), the larger the maximum frequency of the PSD. As a byproduct of this result, an alternative strategy (without length scaling) to optimize the intrinsic cut-off frequency of graphene transistors is envisioned.