Variability Predictions for the Next Technology Generations of <i>n</i>-type Si_<i>x</i>Ge_1−<i>x</i> Nanowire MOSFETs

Abstract

Using a state-of-the-art quantum transport simulator based on the effective mass approximation, we have thoroughly studied the impact of variability on Si x Ge 1 − x channel gate-all-around nanowire metal-oxide-semiconductor field-effect transistors (NWFETs) associated with random discrete dopants, line edge roughness, and metal gate granularity. Performance predictions of NWFETs with different cross-sectional shapes such as square, circle, and ellipse are also investigated. For each NWFETs, the effective masses have carefully been extracted from s p 3 d 5 s ∗ tight-binding band structures. In total, we have generated 7200 transistor samples and performed approximately 10,000 quantum transport simulations. Our statistical analysis reveals that metal gate granularity is dominant among the variability sources considered in this work. Assuming the parameters of the variability sources are the same, we have found that there is no significant difference of variability between SiGe and Si channel NWFETs.

Keywords

• line edge roughness
• metal gate granularity
• nanowire
• non-equilibrium Green’s function
• random discrete dopants
• SiGe
• variability