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Simulations of Statistical Variability in n-Type FinFET, Nanowire, and Nanosheet FETs
IEEE Electron Device Letters, Volume: 42, Issue: 10, Pages: 1416 - 1419
Swansea University Author: Karol Kalna
PDF | Accepted Manuscript
Four sources of variability, metal grain granularity (MGG), line-edge roughness (LER), gate-edge roughness (GER), and random discrete dopants (RDD), affecting the performance of state-of-the-art FinFET, nanosheet (NS), and nanowire (NW) FETs, are analysed via our in-house 3D finite-element drift-dif...
|Published in:||IEEE Electron Device Letters|
Institute of Electrical and Electronics Engineers (IEEE)
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Four sources of variability, metal grain granularity (MGG), line-edge roughness (LER), gate-edge roughness (GER), and random discrete dopants (RDD), affecting the performance of state-of-the-art FinFET, nanosheet (NS), and nanowire (NW) FETs, are analysed via our in-house 3D finite-element drift-diffusion/Monte Carlo simulator that includes 2D Schrödinger equation quantum corrections. The MGG and LER are the sources of variability that influence device performance of the three multi-gate architectures the most. The FinFET and the NS FET are similarly affected by the MGG variations with threshold voltage and on-current standard deviations significantly lower (at least 20 %) than those of the NW FET. The LER variability has a negligible influence in the NS FET performance with σVT values around 12 and 42 times lower than those of the FinFET and the NW FET. The three architectures are equally affected by the RDD (σVT= 8 mV) and minimally influenced by the GER (σVT ≈ 4 mV). The variability of NS FETs makes them strong candidates to replace FinFETs.
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