This paper investigates the electrical performance
improvements induced by appropriate strain conditions in n-type InAs nanowire tunnel FETs in the context of a systematic comparison with strained silicon MOSFETs. To this purpose, we exploited
a 3-D simulator based on an eight-band k · p Hamiltonian
within the nonequilibrium Green function formalism. Our model accounts for arbitrary crystal orientations and describes the strain
implicitly by a modification of the band structure. The effect of acoustic- and optical-phonon scattering is also accounted for in the self-consistent Born approximation. Our results show that appropriate strain conditions in n-type InAs tunnel FETs induce a remarkable enhancement of Ion with a small degradation of the subthreshold slope, as well as large improvements in the Ioff versus Ion tradeoff for low Ioff and VDD values. Hence, an important widening of the range of Ioff and VDD values where tunnel FETs can compete with strained silicon MOSFETs is obtained
We present the first computational study employing a full quantum transport model to investigate the effect of interface traps in nanowire InAs Tunnel FETs and MOSFETs. To this purpose, we introduced a description of interface traps in a simulator based on the NEGF formalism and on a 8×8 k·p Hamiltonian and accounting for phonon scattering. Our results show that: (a) even a single trap can detereorate the inverse sub-threshold slope (SS) of a nanowire InAs Tunnel FET; (b) the inelastic phonon assisted tunneling (PAT) through interface traps results in a temperature dependence of the Tunnel FETs IV characteristics; (c) the impact of interface traps on I of f is larger in Tunnel FETs than in MOSFETs; (d) interface traps represent a sizable source of device variability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.