Analytical Model to Estimate FinFET’s ${\text I}_{\text {ON}}$ , ${\text I}_{\text{OFF}}$ , SS, and ${\rm V}_{T}$ Distribution Due to FER

Abstract

In our earlier work, we presented a percolation theory-based analytical model to estimate FinFET’s <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V}_{T}$ </tex-math></inline-formula> distribution due to fin edge roughness. The earlier models in the literature were based on minimum fin width, the limitations of which were discussed in detail. In this paper, we advance the percolation theory-based model to capture the variability in all key-device parameters, viz. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> , subthreshold slope, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V}_{T}$ </tex-math></inline-formula> . The entire distribution of these parameters obtained by the model is presented and compared against stochastic TCAD to demonstrate excellent match. The model reduces rms error in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> of various parameters by 5%–60%, and 20%–50% in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> with respect to the minimum fin width-based models present in the literature.