Simulation study of scaling design, performance characterization, statistical variability and reliability of decananometer MOSFETs

This thesis describes a comprehensive, simulation based scaling study – including device design, performance characterization, and the impact of statistical variability – on deca-nanometer bulk MOSFETs. After careful calibration of fabrication processes and electrical characteristics for n- and p-MOSFETs with 35 nm physical gate length, 1 nm EOT and stress engineering, the simulated devices closely match the performance of contemporary 45 nm CMOS technologies. Scaling to 25 nm, 18 nm and 13 nm gate length n and p devices follows generalized scaling rules, augmented by physically realistic constraints and the introduction of high-k/metal-gate stacks. The scaled devices attain the performance stipulated by the ITRS. Device a.c. performance is analyzed, at device and circuit level. Extrinsic parasitics become critical to nano-CMOS device performance. The thesis describes device capacitance components, analyzes the CMOS inverter, and obtains new insights into the inverter propagation delay in nano-CMOS. The projection of a.c. performance of scaled devices is obtained. The statistical variability of electrical characteristics, due to intrinsic parameter fluctuation sources, in contemporary and scaled decananometer MOSFETs is systematically investigated for the first time. The statistical variability sources: random discrete dopants, gate line edge roughness and poly-silicon granularity are simulated, in combination, in an ensemble of microscopically different devices. An increasing trend in the standard deviation of the threshold voltage as a function of scaling is observed. The introduction of high-k/metal gates improves electrostatic integrity and slows this trend. Statistical evaluations of variability in Ion and Ioff as a function of scaling are also performed. For the first time, the impact of strain on statistical variability is studied. Gate line edge roughness results in areas of local channel shortening, accompanied by locally increased strain, both effects increasing the local current. Variations are observed in both the drive current, and in the drive current enhancement normally expected from the application of strain. In addition, the effects of shallow trench isolation (STI) on MOSFET performance and on its statistical variability are investigated for the first time. The inverse-narrow-width effect of STI enhances the current density adjacent to it. This leads to a local enhancement of the influence of junction shapes adjacent to the STI. There is also a statistical impact on the threshold voltage due to random STI induced traps at the silicon/oxide interface

Statistical modelling of nano CMOS transistors with surface potential compact model PSP

The development of a statistical compact model strategy for nano-scale CMOS transistors is presented in this thesis. Statistical variability which arises from the discreteness of charge and granularity of matter plays an important role in scaling of nano CMOS transistors especially in sub 50nm technology nodes. In order to achieve reasonable performance and yield in contemporary CMOS designs, the statistical variability that affects the circuit/system performance and yield must be accurately represented by the industry standard compact models. As a starting point, predictive 3D simulation of an ensemble of 1000 microscopically different 35nm gate length transistors is carried out to characterize the impact of statistical variability on the device characteristics. PSP, an advanced surface potential compact model that is selected as the next generation industry standard compact model, is targeted in this study. There are two challenges in development of a statistical compact model strategy. The first challenge is related to the selection of a small subset of statistical compact model parameters from the large number of compact model parameters. We propose a strategy to select 7 parameters from PSP to capture the impact of statistical variability on current-voltage characteristics. These 7 parameters are used in statistical parameter extraction with an average RMS error of less than 2.5% crossing the whole operation region of the simulated transistors. Moreover, the accuracy of statistical compact model extraction strategy in reproducing the MOSFET electrical figures of merit is studied in detail. The results of the statistical compact model extraction are used for statistical circuit simulation of a CMOS inverter under different input-output conditions and different number of statistical parameters. The second challenge in the development of statistical compact model strategy is associated with statistical generation of parameters preserving the distribution and correlation of the directly extracted parameters. By using advanced statistical methods such as principal component analysis and nonlinear power method, the accuracy of parameter generation is evaluated and compared to directly extracted parameter sets. Finally, an extension of the PSP statistical compact model strategy to different channel width/length devices is presented. The statistical trends of parameters and figures of merit versus channel width/length are characterized

Statistical circuit simulations - from ‘atomistic’ compact models to statistical standard cell characterisation

This thesis describes the development and application of statistical circuit simulation methodologies to analyse digital circuits subject to intrinsic parameter fluctuations. The specific nature of intrinsic parameter fluctuations are discussed, and we explain the crucial importance to the semiconductor industry of developing design tools which accurately account for their effects. Current work in the area is reviewed, and three important factors are made clear: any statistical circuit simulation methodology must be based on physically correct, predictive models of device variability; the statistical compact models describing device operation must be characterised for accurate transient analysis of circuits; analysis must be carried out on realistic circuit components. Improving on previous efforts in the field, we posit a statistical circuit simulation methodology which accounts for all three of these factors. The established 3-D Glasgow atomistic simulator is employed to predict electrical characteristics for devices aimed at digital circuit applications, with gate lengths from 35 nm to 13 nm. Using these electrical characteristics, extraction of BSIM4 compact models is carried out and their accuracy in performing transient analysis using SPICE is validated against well characterised mixed-mode TCAD simulation results for 35 nm devices. Static d.c. simulations are performed to test the methodology, and a useful analytic model to predict hard logic fault limitations on CMOS supply voltage scaling is derived as part of this work. Using our toolset, the effect of statistical variability introduced by random discrete dopants on the dynamic behaviour of inverters is studied in detail. As devices scaled, dynamic noise margin variation of an inverter is increased and higher output load or input slew rate improves the noise margins and its variation. Intrinsic delay variation based on CV/I delay metric is also compared using ION and IEFF definitions where the best estimate is obtained when considering ION and input transition time variations. Critical delay distribution of a path is also investigated where it is shown non-Gaussian. Finally, the impact of the cell input slew rate definition on the accuracy of the inverter cell timing characterisation in NLDM format is investigated

Statistical compact model strategies for nano CMOS transistors subject of atomic scale variability

One of the major limiting factors of the CMOS device, circuit and system simulation in sub 100nm regimes is the statistical variability introduced by the discreteness of charge and granularity of matter. The statistical variability cannot be eliminated by tuning the layout or by tightening fabrication process control. Since the compact models are the key bridge between technology and design, it is necessary to transfer reliably the MOSFET statistical variability information into compact models to facilitate variability aware design practice. The aim of this project is the development of a statistical extraction methodology essential to capture statistical variability with optimum set of parameters particularly in industry standard compact model BSIM. This task is accomplished by using a detailed study on the sensitivity analysis of the transistor current in respect to key parameters in compact model in combination with error analysis of the fitted Id-Vg characteristics. The key point in the developed direct statistical compact model strategy is that the impacts of statistical variability can be captured in device characteristics by tuning a limited number of parameters and keeping the values for remaining major set equal to their default values obtained from the “uniform” MOSFET compact model extraction. However, the statistical compact model extraction strategies will accurately represent the distribution and correlation of the electrical MOSFET figures of merit. Statistical compact model parameters are generated using statistical parameter generation techniques such as uncorrelated parameter distributions, principal component analysis and nonlinear power method. The accuracy of these methods is evaluated in comparison with the results obtained from ‘atomistic’ simulations. The impact of the correlations in the compact model parameters has been analyzed along with the corresponding transistor figures of merit. The accuracy of the circuit simulations with different statistical compact model libraries has been studied. Moreover, the impact of the MOSFET width/length on the statistical trend of the optimum set of statistical compact model parameters and electrical figures of merit has been analyzed with two methods to capture geometry dependencies in proposed statistical models

Intrinsic variability of nanoscale CMOS technology for logic and memory.

The continuous downscaling of CMOS technology, the main engine of development of the semiconductor Industry, is limited by factors that become important for nanoscale device size, which undermine proper device operation completely offset gains from scaling. One of the main problems is device variability: nominally identical devices are different at the microscopic level due to fabrication tolerance and the intrinsic granularity of matter. For this reason, structures, devices and materials for the next technology nodes will be chosen for their robustness to process variability, in agreement with the ITRS (International Technology Roadmap for Semiconductors). Examining the dispersion of various physical and geometrical parameters and the effect these have on device performance becomes necessary. In this thesis, I focus on the study of the dispersion of the threshold voltage due to intrinsic variability in nanoscale CMOS technology for logic and for memory. In order to describe this, it is convenient to have an analytical model that allows, with the assistance of a small number of simulations, to calculate the standard deviation of the threshold voltage due to the various contributions

Oxygen-insertion Technology for CMOS Performance Enhancement

Until 2003, the semiconductor industry followed Dennard scaling rules to improve complementary metal-oxide-semiconductor (CMOS) transistor performance. However, performance gains with further reductions in transistor gate length are limited by physical effects that do not scale commensurately with device dimensions: short-channel effects (SCE) due to gate-leakage-limited gate-oxide thickness scaling, channel mobility degradation due to enhanced vertical electric fields, increased parasitic resistances due to reductions in source/drain (S/D) contact area, and increased variability in transistor performance due to random dopant fluctuation (RDF) effects and gate work function variations (WFV). These emerging scaling issues, together with increased process complexity and cost, pose severe challenges to maintaining the exponential scaling of transistor dimensions. This dissertation discusses the benefits of oxygen-insertion (OI) technology, a CMOS performance booster, for overcoming these challenges. The benefit of OI technology to mitigate the increase in sheet resistance ($R_{sh}$) with decreasing junction depth ($X_J$) for ultra-shallow-junctions (USJs) relevant for deep-sub-micron planar CMOS transistors is assessed through the fabrication of $R_{sh}$ test structures, electrical characterization, and technology computer-aided design (TCAD) simulations. Experimental and secondary ion mass spectroscopy (SIMS) analyses indicate that OI technology can facilitate low-resistivity USJ formation by reducing $R_{sh}$ and $X_J$ due to retarded transient-enhanced-diffusion (TED) effects and enhanced dopant retention during post-implantation thermal annealing. It is also shown that a low-temperature-oxide (LTO) capping can increase $R_{sh}$ unfavorably due to lower dopant activation levels, which can be alleviated by OI technology. This dissertation extends the evaluation of OI technology to advanced FinFET technology, targeting 7/8-nm low power technology node. A bulk-Si FinFET design comprising a super-steep retrograde (SSR) fin channel doping profile achievable with OI technology is studied by three-dimensional (3-D) TCAD simulations. As compared with the conventional bulk-Si (control) FinFET design with a heavily-doped fin channel doping profile, SSR FinFETs can achieve higher $I_{on}/I_{off}$ ratios and reduce the sensitivity of device performance to variations due to the lightly doped fin channel. As compared with the SOI FinFET design, SSR FinFETs can achieve similarly low $V_{DD,min}$ for 6T-SRAM cell yield estimation. Both SSR and SOI design can provide for as much as 100 mV reduction in $V_{DD,min}$ compared with the control FinFET design. Overall, the SSR FinFET design that can be achieved with OI technology is demonstrated to be a cheaper alternative to the SOI FinFET technology for extending CMOS scaling beyond the 10-nm node. Finally, this dissertation investigates the benefits of OI technology for reducing the Schottky barrier height ($\Phi_{Bp}$) of a Pt/Ti/p-type Si metal-semiconductor (M/S) contact, which can be expected to help reduce the specific contact resistivity for a p-type silicon contact. Electrical measurements of back-to-back Schottky diodes, SIMS, and X-ray photoelectron spectroscopy (XPS) show that the reduction in $\Phi_{Bp}$ is associated with enhanced Ti 2p and Si 2p core energy level shifts. OI technology is shown to favor low-$\Phi_{Bp}$ Pt monosilicide formation during forming gas anneal (FGA) by suppressing the grain boundary diffusion of Pt atoms into the crystalline Si substrate

Architectural level delay and leakage power modelling of manufacturing process variation

PhD ThesisThe effect of manufacturing process variations has become a major issue regarding the estimation of circuit delay and power dissipation, and will gain more importance in the future as device scaling continues in order to satisfy market place demands for circuits with greater performance and functionality per unit area. Statistical modelling and analysis approaches have been widely used to reflect the effects of a variety of variational process parameters on system performance factor which will be described as probability density functions (PDFs). At present most of the investigations into statistical models has been limited to small circuits such as a logic gate. However, the massive size of present day electronic systems precludes the use of design techniques which consider a system to comprise these basic gates, as this level of design is very inefficient and error prone. This thesis proposes a methodology to bring the effects of process variation from transistor level up to architectural level in terms of circuit delay and leakage power dissipation. Using a first order canonical model and statistical analysis approach, a statistical cell library has been built which comprises not only the basic gate cell models, but also more complex functional blocks such as registers, FIFOs, counters, ALUs etc. Furthermore, other sensitive factors to the overall system performance, such as input signal slope, output load capacitance, different signal switching cases and transition types are also taken into account for each cell in the library, which makes it adaptive to an incremental circuit design. The proposed methodology enables an efficient analysis of process variation effects on system performance with significantly reduced computation time compared to the Monte Carlo simulation approach. As a demonstration vehicle for this technique, the delay and leakage power distributions of a 2-stage asynchronous micropipeline circuit has been simulated using this cell library. The experimental results show that the proposed method can predict the delay and leakage power distribution with less than 5% error and at least 50,000 times faster computation time compare to 5000-sample SPICE based Monte Carlo simulation. The methodology presented here for modelling process variability plays a significant role in Design for Manufacturability (DFM) by quantifying the direct impact of process variations on system performance. The advantages of being able to undertake this analysis at a high level of abstraction and thus early in the design cycle are two fold. First, if the predicted effects of process variation render the circuit performance to be outwith specification, design modifications can be readily incorporated to rectify the situation. Second, knowing what the acceptable limits of process variation are to maintain design performance within its specification, informed choices can be made regarding the implementation technology and manufacturer selected to fabricate the design

Gate leakage variability in nano-CMOS transistors

Gate leakage variability in nano-scale CMOS devices is investigated through advanced modelling and simulations of planar, bulk-type MOSFETs. The motivation for the work stems from the two of the most challenging issues in front of the semiconductor industry - excessive leakage power, and device variability - both being brought about with the aggressive downscaling of device dimensions to the nanometer scale. The aim is to deliver a comprehensive tool for the assessment of gate leakage variability in realistic nano-scale CMOS transistors. We adopt a 3D drift-diffusion device simulation approach with density-gradient quantum corrections, as the most established framework for the study of device variability. The simulator is first extended to model the direct tunnelling of electrons through the gate dielectric, by means of an improved WKB approximation. A study of a 25 nm square gate n-type MOSFET demonstrates that combined effect of discrete random dopants and oxide thickness variation lead to starndard deviation of up to 50% (10%) of the mean gate leakage current in OFF(ON)-state of the transistor. There is also a 5 to 6 times increase of the magnitude of the gate current, compared to that simulated of a uniform device. A significant part of the research is dedicated to the analysis of the non-abrupt bandgap and permittivity transition at the Si/SiO2 interface. One dimensional simulation of a MOS inversion layer with a 1nm SiO2 insulator and realistic band-gap transition reveals a strong impact on subband quantisation (over 50mV reduction in the delta-valley splitting and over 20% redistribution of carriers from the delta-2 to the delta-4 valleys), and enhancement of capacitance (over 10%) and leakage (about 10 times), relative to simulations with an abrupt band-edge transition at the interface

Impact of atomistic device variability on analogue circuit design

Scaling of complementary metal-oxide-semiconductor (CMOS) technology has benefited the semiconductor industry for almost half a century. For CMOS devices with a physical gate-length in the sub-100 nm range, extreme device variability is introduced and has become a major stumbling block for next generation analogue circuit design. Both opportunities and challenges have therefore confronted analogue circuit designers. Small geometry device can enable high-speed analogue circuit designs, such as data conversion interfaces that can work in the radio frequency range. These designs can be co-integrated with digital systems to achieve low cost, high-performance, single-chip solutions that could only be achieved using multi-chip solutions in the past. However, analogue circuit designs are extremely vulnerable to device mismatch, since a large number of symmetric transistor pairs and circuit cells are required. The increase in device variability from sub-100 nm processes has therefore significantly reduced the production yield of the conventional designs. Mismatch models have been developed to analytically evaluate the magnitude of random variations. Based on measurements from custom designed test structures, the statistics of process variation can be estimated using design related parameters. However, existing models can no longer accurately estimate the magnitude of mismatch for sub-100 nm “atomistic” devices, since short-channel effects have become important. In this thesis, a new mismatch model for small geometry devices will be proposed to address this problem. Based on knowledge of the matching performance obtained from the mismatch model, design solutions are desired at different design levels for a variety of circuit topologies. In this thesis, transistor level compensation solutions have been investigated and closed-loop compensation circuits have been proposed. At circuit level, a latch-based comparator has been used to develop a compensation solution because this type of comparator is extremely sensitive to the device mismatch. These comparators are also used as the fundamental building block for the analogue-to-digital converters (ADC). The proposed comparator compensation scheme is used to improve the performance of a high-speed flash ADC

Analyse et modélisation des phénomènes de mismatch des transistors MOSFET avancées

For correct operation, certain analog and digital circuits, such as current mirrors or SRAM, require pairs of MOS transistors that are electrically identical. Real devices, however, suffer from random local variations in the electrical parameters, a problem referred to as mismatch. The aim of this thesis is to understand the physical causes of mismatch, to quantify this phenomenon, and to propose solutions that enable to reduce its effects. In this context, four major areas are treated. The first one focuses on the optimization of mismatch measurement methodologies. A new technique for the measurement of Vt and β mismatch and an ID mismatch model are proposed, analyzed and applied to experimental data for 28 nm Bulk and FD SOI technologies. The second area focuses on the characterization of different configurations of MOS transistors in order to propose design architectures that are optimized for certain applications. Specifically, the possibility of replacing LDEMOS with transistors in cascode configuration is analyzed. The third area focuses on the analysis and modeling of mismatch phenomena in advanced Bulk and SOI transistors. Three aspects are analyzed: 1) the impact of the introduction of germanium in P channel of 28nm BULK transistors; 2) the elimination of the metal gate contribution to Vt mismatch by using 20nm Gate-last Bulk technology; 3) a descriptive study of the principal contributions to Vt, β and ID mismatch in 28 and 14 nm FD SOI technologies. The last area treats the mismatch trends with transistor aging. NBTI stress tests were applied to PMOS 28nm FD SOI transistors. Models of the Vt and β mismatch trends as a function of the induced interface traps and fixed charges at the Si/SiO2 interface and in the oxide were developed and discussed.Afin de réaliser correctement leur fonction, certains blocs analogiques ou numériques comme les miroirs de courant ou les SRAM, nécessitent des paires de transistors MOS électriquement identiques. Cependant, les dispositifs sur silicium, même appariés, subissent des variations locales aléatoires ce qui fait varier leurs performances électriques. Ce phénomène est connu sous le nom désappariement. L'objectif de cette thèse est de comprendre les causes physiques de ce désappariement, de le quantifier et de proposer des solutions pour le réduire. Dans ce contexte, quatre thèmes principaux sont développés. Le premier thème se focalise sur l'optimisation des méthodologies de mesures des phénomènes de désappariement. Une nouvelle méthode de mesure du désappariement de Vt et de β ainsi qu'un nouveau modèle de désappariement de ID sont proposés, analysés et appliqués à des données mesurées sur des technologies 28nm Bulk et FD SOI. Le second thème se concentre sur la caractérisation des différentes configurations de transistor MOS afin de proposer l'architecture optimale en fonction des applications visées. Ainsi, la possibilité de remplacer le LDEMOS par une configuration cascode est analysée en détail. Le troisième thème se focalise sur l'analyse et la modélisation des phénomènes de désappariement des transistors MOS avancés. Trois aspects sont analysés : 1) l'introduction du Ge dans le canal P des technologies 28nm BULK, 2) la suppression de la contribution de la grille sur le désappariement de Vt en utilisant la technologie 20 nm métal-Gate-Last 3) un descriptif des principaux contributeurs au désappariement de Vt, β et ID dans les technologies 28 et 14nm FD SOI. Le dernier thème traite du comportement du désappariement des transistors MOS après vieillissement. Un vieillissement NBTI a été appliqué sur des PMOS de la technologie 28nm FD SOI. Des modèles de comportement de Vt et de β en fonction du nombre de charges fixes ou d'états d'interfaces induits à l'interface Si/SiO2 ou dans l'oxyde sont proposés et analysés