Drain current local variability analysis in nanoscale junctionless FinFETs utilizing a compact model. (August 2020)

• Record Type: Journal Article
• Authors: Oproglidis, T.A.; Tassis, D.H.; Tsormpatzoglou, A.; Ghibaudo, G.; Dimitriadis, C.A.
• Is Part Of: Solid-state electronics. Volume 170(2020)
• Publication Date: 2020-08
• Subjects: Junctionless triple-gate FinFETs -- Local variability -- Compact modeling -- Monte Carlo simulation -- Variability sources; Semiconductors -- Periodicals; Semiconducteurs -- Périodiques; 621.38152
• DOI: 10.1016/j.sse.2020.107835
• Languages: English
• ISSNs: 0038-1101

Abstract

Highlights: Utilization of a symmetric and continuous compact model to assess local variability. Device parameter extraction of local pairs and statistical analysis. Successful reproduction of local variability using Monte Carlo simulations. Decomposition of the total variability and detection of process variability sources. Abstract: This paper investigates the local variability in nanoscale triple-gate junctionless FinFETs utilizing an analytical symmetric and continuous compact model combined with Monte Carlo simulations. Initially, the device parameters are extracted from the experimental transfer characteristics, such as threshold voltage, ideality factor, low-field mobility, source-drain series resistance, channel length modulation factor and mobility degradation factor. Then, statistical analysis is performed to calculate the mean values and standard deviations of the differences of the aforementioned parameters for the local pairs and large number of devices with reference to the mean value of all dies. Monte Carlo simulations allow the compact model to reproduce successfully the drain current local variability. Most important process parameters have been considered and assessed as variability sources, by using the error propagation formula and exploiting the proposed drain current compact model. Successful application to experimental data, revealed the extent of the variabilities in most important process parameters of the devices (sources of variability).