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

Efficient Estimation of Reliability Metrics for Circuits in Deca-Nanometer Nodes

51 σ.Καθώς η τεχνολογία οδηγεί στη κατασκευή τρανζίστορ ολοένα και μικρότερων διαστάσεων, έχουν εμφανιστεί αρκετά φαινόμενα που επηρεάζουν την αξιοπιστία των ολοκληρωμένων κυκλωμάτων. Ένα από αυτά τα φαινόμενα ονομάζεται "Bias Temperature Instability", αποτελεί σημαντικό κίνδυνο για την αξιοπιστία των ολοκληρωμένων κυκλωμάτων και έχει παρατηρηθεί εδώ και πάνω από 30 χρόνια. Το πρώτο μοντέλο που προσπάθησε να εξηγήσει αυτό το φαινόμενο εμφανίστηκε πριν από 30 περίπου χρόνια, βασίστηκε στη διάχυση υδρογόνου και ως εκ τούτου ονομάστηκε "Reaction-Diffusion model". Πριν από μερικά χρόνια δημιουργήθηκε ένα νέο ατομιστικό μοντέλο το οποίο βασίζεται κυρίως στην εμφάνιση ελαττωμάτων στο διηλεκτρικό μεταξύ της πύλης και του καναλιού των FET τρανζίστορ. Μελετώντας κανείς τη βιβλιογραφία που αφορά στο ατομιστικό αυτό μοντέλο, μπορεί να συναντήσει εργαλεία που προσομοιώνουν με ακρίβεια το μοντέλο αλλά δυστυχώς απαιτούν αρκετό χρόνο για να εκτελεστούν, κάτι το οποίο τα καθιστά απαγορευτικά για εκτενή χρήση. Παράλληλα, υπάρχουν εργαλεία βασισμένα στο μοντέλο της διάχυσης τα οποία βέβαια αδυνατούν να παράξουν σωστά και λεπτομερή αποτελέσματα, κυρίως σε τεχνολογίες μικρών διαστάσεων. Η παρούσα λοιπόν διπλωματική εργασία παρουσιάζει τα αποτελέσματα ενός νέου και καινοτόμου εργαλείου το οποίο βασίζεται στο ατομιστικό μοντέλο, ωστόσο προσομοιώνει αποδοτικά αλλά και με ακρίβεια το φαινόμενο της γήρανσης. Ένα αντιπροσωπευτικό μονοπάτι στατικής μνήμης (SRAM) θα χρησιμοποιηθεί ως παράδειγμα της λειτουργίας του μοντέλου ενώ παράλληλα θα υπολογισθούν, με βάση τα αποτελέσματα των προσομοιώσεων αυτών, μετρικές, σημαντικές για το χαρακτηρισμό της απόδοσης και αξιοπιστίας του κυκλώματος, ενώ παράλληλα θα μελετηθούν λεπτομερώς και οι σχέσεις που τις συνδέουν.In modern technologies of integrated circuits (IC) and with the downscaling of device dimensions, various degradation modes constitute major reliability concerns. Bias Temperature Instability (BTI) is a representative example, posing as a significant reliability threat in Field-Effect Transistor (FET) technologies and has been known for more than 30 years. At first, the model that tried to explain this phenomenon was based on the Reaction-Diffusion (RD) theory and was developed nearly 30 years ago. Recently, an atomistic model has been proposed, that enables the modeling of BTI in modern technologies. By observing the amount of software designed to simulate the BTI degradation, tools can be found that are based on the atomistic theory but are computationally prohibitive when it comes to simulating complex circuits consisting of a large number of devices. Tools based on the RD model are unable to accurately capture the BTI-induced degradation, especially in devices with small dimensions. The current thesis is appropriately positioned since it discusses a novel simulation framework that is efficient yet highly accurate. A subset of an embedded Static Random Access Memory (SRAM) is used for verification purposes. The estimation of the functional yield of the circuit over three years of operation will be examined as well as other reliability metrics, such as defects per million (DPM), mean time to failure (MTTF) and failures in time (FIT rate). Finally, the interplay between these metrics is discussed and efficient computation methods are proposed for each one.Μιχαήλ Α. Νόλτση

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

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

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

ランダム・テレグラフ・ノイズの微細MOSFETへの影響に関する研究

筑波大学 (University of Tsukuba)201

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

Impact of intrinsic parameter fluctuations in ultra-thin body silicon-on-insulator MOSFET on 6-transistor SRAM cell

As CMOS device dimensions are being aggressively scaled, the device characteristic must be assessed against fundamental physical limits. Nanoscale device modelling and statistical circuit analysis is needed to provide designer with ability to explore innovative new MOSFET devices as well as understanding the limits of the scaling process. This work introduces a systematic simulation methodology to investigate the impact of intrinsic parameter fluctuation for a novel Ultra-Thin-Body (UTB) Silicon-on-Insulator (SOI) transistor on the corresponding device and circuits. It provides essential link between physical device-level numerical simulation and circuit-level simulation. A systematic analysis of the effects of random discrete dopants, body thickness variations and line edge roughness on a well scaled 10 nm, 7.5 nm and 5 nm channel length UTB-SOI MOSFET is performed. To fully realise the performance benefits of UTB-SOI based SRAM cells a statistical circuit simulation methodology which can fully capture intrinsic parameter fluctuations information into the compact model is developed. The impact of intrinsic parameter fluctuations on the stability and performance of 6T SRAM has been investigated. A comparison with the behaviour of a 6T SRAM based on a conventional 35 nm MOSFET is also presented

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

Study of Radiation Tolerant Storage Cells for Digital Systems

Single event upsets (SEUs) are a significant reliability issue in semiconductor devices. Fully Depleted Silicon-on-Insulator (FDSOI) technologies have been shown to exhibit better SEU performance compared to bulk technologies. This is attributed to the thin Silicon (Si) layer on top of a Buried Oxide (BOX) layer, which allows each transistor to function as an insulated Si island, thus reducing the threat of charge-sharing. Moreover, the small volume of the Si in FDSOI devices results in a reduction of the amount of charge induced by an ion strike. The effects of Total Ionizing Dose (TID) on integrated circuits (ICs) can lead to changes in gate propagation delays, leakage currents, and device functionality. When IC circuits are exposed to ionizing radiation, positive charges accumulate in the gate oxide and field oxide layers, which results in reduced gate control and increased leakage current. TID effects in bulk technologies are usually simpler due to the presence of only one gate oxide layer, but FDSOI technologies have a more complex response to TID effects because of the additional BOX layer. In this research, we aim to address the challenges of developing cost-effective electronics for space applications by bridging the gap between expensive space-qualified components and high-performance commercial technologies. Key research questions involve exploring various radiation-hardening-by-design (RHBD) techniques and their trade-offs, as well as investigating the feasibility of radiation-hardened microcontrollers. The effectiveness of RHBD techniques in mitigating soft errors is well-established. In our study, a test chip was designed using the 22-nm FDSOI process, incorporating multiple RHBD Flip-Flop (FF) chains alongside a conventional FF chain. Three distinct types of ring oscillators (ROs) and a 256 kbit SRAM was also fabricated in the test chip. To evaluate the SEU and TID performance of these designs, we conducted multiple irradiation experiments with alpha particles, heavy ions, and gamma-rays. Alpha particle irradiation tests were carried out at the University of Saskatchewan using an Americium-241 alpha source. Heavy ion experiments were performed at the Texas A&M University Cyclotron Institute, utilizing Ne, Ar, Cu, and Ag in a 15 MeV/amu cocktail. Lastly, TID experiments were conducted using a Gammacell 220 Co-60 chamber at the University of Saskatchewan. By evaluating the performance of these designs under various irradiation conditions, we strive to advance the development of cost-effective, high-performance electronics suitable for space applications, ultimately demonstrating the significance of this project. When exposed to heavy ions, radiation-hardened FFs demonstrated varying levels of improvement in SEU performance, albeit with added power and timing penalties compared to conventional designs. Stacked-transistor DFF designs showed significant enhancement, while charge-cancelling and interleaving techniques further reduced upsets. Guard-gate (GG) based FF designs provided additional SEU protection, with the DFR-FF and GG-DICE FF designs showing zero upsets under all test conditions. Schmitt-trigger-based DFF designs exhibited improved SEU performance, making them attractive choices for hardening applications. The 22-nm FDSOI process proved more resilient to TID effects than the 28-nm process; however, TID effects remained prominent, with increased leakage current and SRAM block degradation at high doses. These findings offer valuable insights for designers aiming to meet performance and SER specifications for circuits in radiation environments, emphasizing the need for additional attention during the design phase for complex radiation-hardened circuits