Variability analysis of FinFET AC/RF performances through efficient physics-based simulations for the optimization of RF CMOS stages

A nearly insatiable appetite for the latest electronic device enables the electronic technology sector to maintain research momentum. The necessity for advancement with miniaturization of electronic devices is the need of the day. Aggressive downscaling of electronic devices face some fundamental limits and thus, buoy up the change in device geometry. MOSFETs have been the leading contender in the electronics industry for years, but the dire need for miniaturization is forcing MOSFET to be scaled to nano-scale and in sub-50 nm scale. Short channel effects (SCE) become dominant and adversely affect the performance of the MOSFET. So, the need for a novel structure was felt to suppress SCE to an acceptable level. Among the proposed devices, FinFETs (Fin Field Effect Transistors) were found to be most effective to counter-act SCE in electronic devices. Today, many industries are working on electronic circuits with FinFETs as their primary element.One of limitation which FinFET faces is device variability. The purpose of this work was to study the effect that different sources of parameter fluctuations have on the behavior and characteristics of FinFETs. With deep literature review, we have gained insight into key sources of variability. Different sources of variations, like random dopant fluctuation, line edge roughness, fin variations, workfunction variations, oxide thickness variation, and source/drain doping variations, were studied and their impact on the performance of the device was studied as well. The adverse effect of these variations fosters the great amount of research towards variability modeling. A proper modeling of these variations is required to address the device performance metric before the fabrication of any new generation of the device on the commercial scale. The conventional methods to address the characteristics of a device under variability are Monte-Carlo-like techniques. In Monte Carlo analysis, all process parameters can be varied individually or simultaneously in a more realistic approach. The Monte Carlo algorithm takes a random value within the range of each process parameter and performs circuit simulations repeatedly. The statistical characteristics are estimated from the responses. This technique is accurate but requires high computational resources and time. Thus, efforts are being put by different research groups to find alternative tools. If the variations are small, Green’s Function (GF) approach can be seen as a breakthrough methodology. One of the most open research fields regards "Variability of FinFET AC performances". One reason for the limited AC variability investigations is the lack of commercially available efficient simulation tools, especially those based on accurate physics-based analysis: in fact, the only way to perform AC variability analysis through commercial TCAD tools like Synopsys Sentaurus is through the so-called Monte Carlo approach, that when variations are deterministic, is more properly referred to as incremental analysis, i.e., repeated solutions of the device model with varying physical parameters. For each selected parameter, the model must be solved first in DC operating condition (working point, WP) and then linearized around the WP, hence increasing severely the simulation time. In this work, instead, we used GF approach, using our in-house Simulator "POLITO", to perform AC variability analysis, provided that variations are small, alleviating the requirement of double linearization and reducing the simulation time significantly with a slight trade-off in accuracy. Using this tool we have, for the first time addressed the dependency of FinFET AC parameters on the most relevant process variations, opening the way to its application to RF circuits. This work is ultimately dedicated to the successful implementation of RF stages in commercial applications by incorporating variability effects and controlling the degradation of AC parameters due to variability. We exploited the POLITO (in-house simulator) limited to 2D structures, but this work can be extended to the variability analysis of 3D FinFET structure. Also variability analysis of III-V Group structures can be addressed. There is also potentiality to carry out the sensitivity analysis for the other source of variations, e.g., thermal variations

Multi-gate FinFET Mixer Variability assessment through physics-based simulation

In this paper we show that innovative physics-based simulations can be used for a comprehensive analysis of RF stages subject to random variations of technological parameters, including the computation of the average (deterministic) RF performance along with their statistical deviation. The variability analysis is addressed by means of the recently developed physicsbased sensitivity analysis of AC parameters through Green’s functions [1], [2]. To demonstrate the technique, we address the analysis of a FinFET mixer exploiting an innovative Independent Gates topology, showing that a careful design allows to maximize the mixer conversion gain while minimizing its variability vs. several physical parameters, such as the gate length, oxide thickness and fin width

Physics-based modeling of FinFET RF variability

This paper presents the physics-based variability analysis of multi-fin double-gate (DG) MOSFETs, representing the core structure of FinFETs for RF applications. The variability of the AC parameters as a function of relevant geometrical and physical parameters, such as the fin width, the fin separation, the source (drain)-gate distance and the doping level is investigated. The analysis exploits a numerically efficient Green's Function technique [1]-[2], extending to the RF case the linearized approach well known from DC variability analysis. The variability of a single fin DG-MOS transistor is compared to a more realistic structure with two fins and raised source/drain contacts, i.e. including both the active part of the FinFET and a significant amount of passive (parasitic) components at the device level. Although presently implemented in a 2D in-house software, the technique can be easily exported to standard 3D TCAD tools, e.g. for tri-gate FinFETs analysis

Variability of FinFET AC parameters: A physics-based insight

This paper presents a fully physics-based variability analysis of single-fin double-gate Metal Oxide Semiconductor FET (MOSFET) AC parameters, without resorting to any approximated quasi-static analysis based on the variations of theDCdrain current or charge.Variations of theACparameters have been investigated as a function of all the relevant geometrical and physical parameters, with emphasis on the ones affecting the device parasitics, especially important for high-frequency analog applications. A numerically efficient Green's function technique is applied to reduce the simulation time to a few percent of the time required for standard Monte Carlo–based variability analysis. The Green's function approach especially allows for a deep insight into the so-called local variability source, highlighting the regions of the device where physical variations most significantly affect the output AC performances and opening the way for possible structure optimization. Although presently implemented in a 2D in-house software, the technique can be easily exported to standard 3D Technology Computer-Aided Design (TCAD) tools, eg, for tri-gate FinFET analysi

Physics-based modeling of FinFET RF variability under Shorted- and Independent-Gates bias

FinFETs operated with varying bias, and in particular with Short-circuited Gates (SG) or Independent Gates (IG), are actively investigated for RF analog applications. The device process variability is known to vary, at least for DC performances, according to the FINFET bias. This paper presents a novel, comprehensive physics-based variability analysis focused on AC parameters for a double-gate (DG) MOSFET (FinFET) both in SG and IG conditions. The analysis is carried out with a numerically efficient Green's Function technique [1], [2], that exploits a nonlinear variability analysis tool in quasi-linear condition. The AC variability analysis of the FinFET includes selected geometrical and physical parameters, such as the fin width, the source/drain-gate distance and the doping level, whose role is especially relevant for the extraction of the device parasitics' variations. We demonstrate that the sensitivity of the AC parameters differs in the IG and SG case, especially concerning gate capacitances