Impact of Contact Resistance on the fT and fmax of Graphene vs. MoS2 Transistors
Source abstract
Abstract
A key challenge in making 2-D materials viable for electronics is reducing the contact resistance ρ C of the source and drain, which can otherwise severely curtail performance. We consider the impact of contact resistance on the performance of transistors made with single-layer graphene and MoS 2 , two of the most popular 2-D materials presently under consideration for radiofrequency (RF) applications. While our focus is on the impact of ρ C , we include the impact of all the device parasitics. We consider a device structure based on the 7-nm node of the ITRS and use the unity-current-gain and unity-power-gain frequencies (f T and f max ) found from quantum-mechanical simulations, ballistic for graphene and with scattering for MoS 2 , as indicators of RF performance. We quantify our results in terms of the values of ρ C needed to reach specific values of f T and f max . In terms of peak performance (over all bias conditions), we show that graphene retains a significant edge over MoS 2 , despite graphene's poor output conductance, with MoS 2 only being able to bridge the gap if considerably better contact resistances can be realized. However, with the bias current restricted to a technologically relevant value, we show that graphene loses much of its advantage, primarily due to a reduction in its transconductance g m , and we show that MoS 2 can then meet or exceed the performance of graphene via the realization of contact resistances already achieved in multilayer structures. Our values of f T for short-channel devices (around the 7-nm ITRS node) are shown to be consistent with experimental data for present-day long-channel devices, supporting our approach and conclusions.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Graphene research and applications · 2D Materials and Applications · Advancements in Semiconductor Devices and Circuit Design
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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