Simulations of Statistical Variability in n-type FinFET, Nanowire and Nanosheet FETs

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Abstract

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 σ VT 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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Seoane, N. Fernandez, J. G., Kalna, K., Comesaña, E., and García-Loureiro, A. (2021). Simulations of Statistical Variability in n-Type FinFET, Nanowire, and Nanosheet FETs. “IEEE Electron Device Letters”, vol. 42(10), 1416-1419. doi: 10.1109/LED.2021.3109586.

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Attribution-NonCommercial-NoDerivatives 4.0 International