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

Simulation of charge-trapping in nano-scale MOSFETs in the presence of random-dopants-induced variability

The growing variability of electrical characteristics is a major issue associated with continuous downscaling of contemporary bulk MOSFETs. In addition, the operating conditions brought about by these same scaling trends have pushed MOSFET degradation mechanisms such as Bias Temperature Instability (BTI) to the forefront as a critical reliability threat. This thesis investigates the impact of this ageing phenomena, in conjunction with device variability, on key MOSFET electrical parameters. A three-dimensional drift-diffusion approximation is adopted as the simulation approach in this work, with random dopant fluctuations—the dominant source of statistical variability—included in the simulations. The testbed device is a realistic 35 nm physical gate length n-channel conventional bulk MOSFET. 1000 microscopically different implementations of the transistor are simulated and subjected to charge-trapping at the oxide interface. The statistical simulations reveal relatively rare but very large threshold voltage shifts, with magnitudes over 3 times than that predicted by the conventional theoretical approach. The physical origin of this effect is investigated in terms of the electrostatic influences of the random dopants and trapped charges on the channel electron concentration. Simulations with progressively increased trapped charge densities—emulating the characteristic condition of BTI degradation—result in further variability of the threshold voltage distribution. Weak correlations of the order of 10-2 are found between the pre-degradation threshold voltage and post-degradation threshold voltage shift distributions. The importance of accounting for random dopant fluctuations in the simulations is emphasised in order to obtain qualitative agreement between simulation results and published experimental measurements. Finally, the information gained from these device-level physical simulations is integrated into statistical compact models, making the information available to circuit designers

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

Design, Modeling and Analysis of Non-classical Field Effect Transistors

Transistor scaling following per Moore\u27s Law slows down its pace when entering into nanometer regime where short channel effects (SCEs), including threshold voltage fluctuation, increased leakage current and mobility degradation, become pronounced in the traditional planar silicon MOSFET. In addition, as the demand of diversified functionalities rises, conventional silicon technologies cannot satisfy all non-digital applications requirements because of restrictions that stem from the fundamental material properties. Therefore, novel device materials and structures are desirable to fuel further evolution of semiconductor technologies. In this dissertation, I have proposed innovative device structures and addressed design considerations of those non-classical field effect transistors for digital, analog/RF and power applications with projected benefits. Considering device process difficulties and the dramatic fabrication cost, application-oriented device design and optimization are performed through device physics analysis and TCAD modeling methodology to develop design guidelines utilizing transistor\u27s improved characteristics toward application-specific circuit performance enhancement. Results support proposed device design methodologies that will allow development of novel transistors capable of overcoming limitation of planar nanoscale MOSFETs. In this work, both silicon and III-V compound devices are designed, optimized and characterized for digital and non-digital applications through calibrated 2-D and 3-D TCAD simulation. For digital functionalities, silicon and InGaAs MOSFETs have been investigated. Optimized 3-D silicon-on-insulator (SOI) and body-on-insulator (BOI) FinFETs are simulated to demonstrate their impact on the performance of volatile memory SRAM module with consideration of self-heating effects. Comprehensive simulation results suggest that the current drivability degradation due to increased device temperature is modest for both devices and corresponding digital circuits. However, SOI FinFET is recommended for the design of low voltage operation digital modules because of its faster AC response and better SCEs management than the BOI structure. The FinFET concept is also applied to the non-volatile memory cell at 22 nm technology node for low voltage operation with suppressed SCEs. In addition to the silicon technology, our TCAD estimation based on upper projections show that the InGaAs FinFET, with superior mobility and improved interface conditions, achieve tremendous drive current boost and aggressively suppressed SCEs and thereby a strong contender for low-power high-performance applications over the silicon counterpart. For non-digital functionalities, multi-fin FETs and GaN HEMT have been studied. Mixed-mode simulations along with developed optimization guidelines establish the realistic application potential of underlap design of silicon multi-Fin FETs for analog/RF operation. The device with underlap design shows compromised current drivability but improve analog intrinsic gain and high frequency performance. To investigate the potential of the novel N-polar GaN material, for the first time, I have provided calibrated TCAD modeling of E-mode N-polar GaN single-channel HEMT. In this work, I have also proposed a novel E-mode dual-channel hybrid MIS-HEMT showing greatly enhanced current carrying capability. The impact of GaN layer scaling has been investigated through extensive TCAD simulations and demonstrated techniques for device optimization

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

A statistical study of time dependent reliability degradation of nanoscale MOSFET devices

Charge trapping at the channel interface is a fundamental issue that adversely affects the reliability of metal-oxide semiconductor field effect transistor (MOSFET) devices. This effect represents a new source of statistical variability as these devices enter the nano-scale era. Recently, charge trapping has been identified as the dominant phenomenon leading to both random telegraph noise (RTN) and bias temperature instabilities (BTI). Thus, understanding the interplay between reliability and statistical variability in scaled transistors is essential to the implementation of a ‘reliability-aware’ complementary metal oxide semiconductor (CMOS) circuit design. In order to investigate statistical reliability issues, a methodology based on a simulation flow has been developed in this thesis that allows a comprehensive and multi-scale study of charge-trapping phenomena and their impact on transistor and circuit performance. The proposed methodology is accomplished by using the Gold Standard Simulations (GSS) technology computer-aided design (TCAD)-based design tool chain co-optimization (DTCO) tool chain. The 70 nm bulk IMEC MOSFET and the 22 nm Intel fin-shape field effect transistor (FinFET) have been selected as targeted devices. The simulation flow starts by calibrating the device TCAD simulation decks against experimental measurements. This initial phase allows the identification of the physical structure and the doping distributions in the vertical and lateral directions based on the modulation in the inversion layer’s depth as well as the modulation of short channel effects. The calibration is further refined by taking into account statistical variability to match the statistical distributions of the transistors’ figures of merit obtained by measurements. The TCAD simulation investigation of RTN and BTI phenomena is then carried out in the presence of several sources of statistical variability. The study extends further to circuit simulation level by extracting compact models from the statistical TCAD simulation results. These compact models are collected in libraries, which are then utilised to investigate the impact of the BTI phenomenon, and its interaction with statistical variability, in a six transistor-static random access memory (6T-SRAM) cell. At the circuit level figures of merit, such as the static noise margin (SNM), and their statistical distributions are evaluated. The focus of this thesis is to highlight the importance of accounting for the interaction between statistical variability and statistical reliability in the simulation of advanced CMOS devices and circuits, in order to maintain predictivity and obtain a quantitative agreement with a measured data. The main findings of this thesis can be summarised by the following points: Based on the analysis of the results, the dispersions of VT and ΔVT indicate that a change in device technology must be considered, from the planar MOSFET platform to a new device architecture such as FinFET or SOI. This result is due to the interplay between a single trap charge and statistical variability, which has a significant impact on device operation and intrinsic parameters as transistor dimensions shrink further. The ageing process of transistors can be captured by using the trapped charge density at the interface and observing the VT shift. Moreover, using statistical analysis one can highlight the extreme transistors and their probable effect on the circuit or system operation. The influence of the passgate (PG) transistor in a 6T-SRAM cell gives a different trend of the mean static noise margin

A novel deep submicron bulk planar sizing strategy for low energy subthreshold standard cell libraries

Engineering andPhysical Science ResearchCouncil (EPSRC) and Arm Ltd for providing funding in the form of grants and studentshipsThis work investigates bulk planar deep submicron semiconductor physics in an attempt to improve standard cell libraries aimed at operation in the subthreshold regime and in Ultra Wide Dynamic Voltage Scaling schemes. The current state of research in the field is examined, with particular emphasis on how subthreshold physical effects degrade robustness, variability and performance. How prevalent these physical effects are in a commercial 65nm library is then investigated by extensive modeling of a BSIM4.5 compact model. Three distinct sizing strategies emerge, cells of each strategy are laid out and post-layout parasitically extracted models simulated to determine the advantages/disadvantages of each. Full custom ring oscillators are designed and manufactured. Measured results reveal a close correlation with the simulated results, with frequency improvements of up to 2.75X/2.43X obs erved for RVT/LVT devices respectively. The experiment provides the first silicon evidence of the improvement capability of the Inverse Narrow Width Effect over a wide supply voltage range, as well as a mechanism of additional temperature stability in the subthreshold regime. A novel sizing strategy is proposed and pursued to determine whether it is able to produce a superior complex circuit design using a commercial digital synthesis flow. Two 128 bit AES cores are synthesized from the novel sizing strategy and compared against a third AES core synthesized from a state-of-the-art subthreshold standard cell library used by ARM. Results show improvements in energy-per-cycle of up to 27.3% and frequency improvements of up to 10.25X. The novel subthreshold sizing strategy proves superior over a temperature range of 0 °C to 85 °C with a nominal (20 °C) improvement in energy-per-cycle of 24% and frequency improvement of 8.65X. A comparison to prior art is then performed. Valid cases are presented where the proposed sizing strategy would be a candidate to produce superior subthreshold circuits

Cross-Layer Resiliency Modeling and Optimization: A Device to Circuit Approach

The never ending demand for higher performance and lower power consumption pushes the VLSI industry to further scale the technology down. However, further downscaling of technology at nano-scale leads to major challenges. Reduced reliability is one of them, arising from multiple sources e.g. runtime variations, process variation, and transient errors. The objective of this thesis is to tackle unreliability with a cross layer approach from device up to circuit level