This paper presents results of statistical analysis of RTN in highly scaled HKMG FETs. A robust algorithm to extract multiple-trap RTN is proposed and applied to show that RTN can cause serious variation even when HKMG and undoped channel are introduced. We further focus on hysteretic behavior caused by RTN with time constants much longer than the circuit timescale. This reveals that RTN also induces novel instabilities such as short-term BTI and logic delay uncertainty. Extraction of RTN in SRAM arrays is also presented to discuss its impact on operational stability.
This work demonstrates the close relationship between device scaling and the threshold voltage variation (ΔV th ) of random telegraph noise (RTN) in high-κ and metal gate (HK / MG) stacks. Statistical analysis clarifies that high temperature forming gas annealing can suppress the RTN ΔV th . And properly annealed HK FETs have smaller RTN ΔV th than SiON FETs, due mostly to fewer traps and partly to thinner inversion thickness in HK / MG stacks. Consequently, the influence of RTN on HK / MG gate stacks is less than that of random dopant fluctuation in the 22 nm generation. However, RTN may pose a difficult challenge for the 15 nm generation. In addition to the scaling dependence, we also find that characterizing hysteretic RTN behaviors due to RTN dependence on bias is essential to determine whether the observed RTN has an impact on SRAM operation or not.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.