A comprehensive Pelgrom-based on-current variability model for FinFET, NWFET and NSFET
We present a novel Pelgrom-based predictive (PBP) model to estimate the impact of variability on the on-current of
different state-of-the-art semiconductor devices. In this work, we focus on two of the most problematic sources of
variability, the metal grain granularity (MGG) and the line edge roughness (LER). This model allows us to make an
accurate prediction of the on-current standard deviation σI on , being the relative error of the predicted data lower than
8% in 92% of the studied cases. The PBP model entails an immense reduction in the computational cost since once it
is calibrated for an architecture, the prediction of the impact of a variability on devices with any given dimension can
be made without any further simulations. This model could be useful for predicting the effect of variability on future
technology nodes.
keywords:
Publication: Congress
1675164930123
January 31, 2023
/research/publications/a-comprehensive-pelgrom-based-on-current-variability-model-for-finfet-nwfet-and-nsfet2
We present a novel Pelgrom-based predictive (PBP) model to estimate the impact of variability on the on-current of
different state-of-the-art semiconductor devices. In this work, we focus on two of the most problematic sources of
variability, the metal grain granularity (MGG) and the line edge roughness (LER). This model allows us to make an
accurate prediction of the on-current standard deviation σI on , being the relative error of the predicted data lower than
8% in 92% of the studied cases. The PBP model entails an immense reduction in the computational cost since once it
is calibrated for an architecture, the prediction of the impact of a variability on devices with any given dimension can
be made without any further simulations. This model could be useful for predicting the effect of variability on future
technology nodes. - Julian G. Fernandez, Natalia Seoane, Enrique Comesaña, Antonio Garcia-Loureiro
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