Optimum Channel Design of Extremely-Thin-Body nMOSFETs Utilizing Anisotropic Valley-Robust to Surface Roughness Scattering

Extremely thin-body (ETB) nanosheet channels are considered as the most promising structure of complementary metal-oxide-semiconductor devices in future technology nodes. However, mobility degradation due to surface roughness scattering is a critical challenge. In this article, we propose that an an...

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Bibliographic Details
Published in:IEEE transactions on electron devices 2022-04, Vol.69 (4), p.2115-2121
Main Authors: Sumita, Kei, Chen, Chia-Tsong, Toprasertpong, Kasidit, Takenaka, Mitsuru, Takagi, Shinichi
Format: Article
Language:English
Subjects:
Anisotropy
Channels
CMOS
Electron mobility
Extremely thin-body (ETB)
Germanium
mobility
MOSFET
MOSFETs
nanosheet
Rapid prototyping
Robustness
Rough surfaces
Scattering
Semiconductor devices
Silicon
Stationary state
Surface roughness
surface roughness scattering
Surface waves
Two dimensional materials
Valleys
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Summary:Extremely thin-body (ETB) nanosheet channels are considered as the most promising structure of complementary metal-oxide-semiconductor devices in future technology nodes. However, mobility degradation due to surface roughness scattering is a critical challenge. In this article, we propose that an anisotropic valley with a heavy confinement mass is very robust to surface roughness scattering in ETB channels. Our revised physical model of surface roughness scattering allows us to predict the mobility in ETB channels quantitatively. Our model is in good agreement with the experimental mobility under directly measured roughness parameters. Based on this model, we assessed the optimum ETB channels of (100) Si, (100) and (111) Ge, and (111) InAs down to 2 nm. Simulation results showed that the (111) Ge-on-insulator (GOI) is the most promising because of the strong anisotropy of the L valley and excellent electron mobility even in the 2-nm-thick channels, which is an advantage over Si and 2-D materials.
ISSN:0018-9383
1557-9646
DOI:10.1109/TED.2022.3143484