In our earlier work, we presented a percolation theory-based analytical model to estimate FinFET's V-T 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. ION, I-OFF, subthreshold slope, and VT. 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 mu of various parameters by 5%-60%, and 20%-50% in sigma with respect to the minimum fin width-based models present in the literature
A simple device-level characterization method to decompose the amplitudes of different random variat...
Extensive numerical simulations of FinFET structures have been carried out using commercial TCAD too...
A simple device-level characterization approach to quantitatively evaluate the impacts of different ...
Line-edge roughness induced fin-edge roughness (FER) is the primary source of V-T variation in FinFE...
Line edge roughness (LER) is a critical variability source in scaled FinFETs. LER produces line widt...
We report the first compact model to estimate the V-T distribution of double gate-FinFET due to line...
A compact model is developed to study the fin-width roughness (FWR) induced device variability and i...
In this paper, a generalized model to predict fin-width roughness (FWR) induced FinFET device variab...
A compact model to correlate FinFET device variability to the spatial fluctuation of fin-width is de...
Threshold voltage ðVT Þ and drive current ðIONÞ variability of low stand-by power (LSTP)-32 nm FinFE...
The impact of fin line-edge roughness on threshold voltage and drive current of LSTP-32nm Fin-FETs i...
This paper developed a full three-dimensional (3-D) statistical simulation approach to investigate F...
Predictive compact models for two key variability sources in FinFET technology, the gate edge roughn...
Predictive compact models for two key variability sources in FinFET technology, the gate edge roughn...
Metal gate granularity (MGG)-induced threshold voltage variability is the dominant source of variabi...
A simple device-level characterization method to decompose the amplitudes of different random variat...
Extensive numerical simulations of FinFET structures have been carried out using commercial TCAD too...
A simple device-level characterization approach to quantitatively evaluate the impacts of different ...
Line-edge roughness induced fin-edge roughness (FER) is the primary source of V-T variation in FinFE...
Line edge roughness (LER) is a critical variability source in scaled FinFETs. LER produces line widt...
We report the first compact model to estimate the V-T distribution of double gate-FinFET due to line...
A compact model is developed to study the fin-width roughness (FWR) induced device variability and i...
In this paper, a generalized model to predict fin-width roughness (FWR) induced FinFET device variab...
A compact model to correlate FinFET device variability to the spatial fluctuation of fin-width is de...
Threshold voltage ðVT Þ and drive current ðIONÞ variability of low stand-by power (LSTP)-32 nm FinFE...
The impact of fin line-edge roughness on threshold voltage and drive current of LSTP-32nm Fin-FETs i...
This paper developed a full three-dimensional (3-D) statistical simulation approach to investigate F...
Predictive compact models for two key variability sources in FinFET technology, the gate edge roughn...
Predictive compact models for two key variability sources in FinFET technology, the gate edge roughn...
Metal gate granularity (MGG)-induced threshold voltage variability is the dominant source of variabi...
A simple device-level characterization method to decompose the amplitudes of different random variat...
Extensive numerical simulations of FinFET structures have been carried out using commercial TCAD too...
A simple device-level characterization approach to quantitatively evaluate the impacts of different ...