566 research outputs found

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

    Get PDF
    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

    CMOS camera employing a double junction active pixel

    Get PDF

    Detector Technologies for CLIC

    Full text link
    The Compact Linear Collider (CLIC) is a high-energy high-luminosity linear electron-positron collider under development. It is foreseen to be built and operated in three stages, at centre-of-mass energies of 380 GeV, 1.5 TeV and 3 TeV, respectively. It offers a rich physics program including direct searches as well as the probing of new physics through a broad set of precision measurements of Standard Model processes, particularly in the Higgs-boson and top-quark sectors. The precision required for such measurements and the specific conditions imposed by the beam dimensions and time structure put strict requirements on the detector design and technology. This includes low-mass vertexing and tracking systems with small cells, highly granular imaging calorimeters, as well as a precise hit-time resolution and power-pulsed operation for all subsystems. A conceptual design for the CLIC detector system was published in 2012. Since then, ambitious R&D programmes for silicon vertex and tracking detectors, as well as for calorimeters have been pursued within the CLICdp, CALICE and FCAL collaborations, addressing the challenging detector requirements with innovative technologies. This report introduces the experimental environment and detector requirements at CLIC and reviews the current status and future plans for detector technology R&D.Comment: 152 pages, 116 figures; published as CERN Yellow Report Monograph Vol. 1/2019; corresponding editors: Dominik Dannheim, Katja Kr\"uger, Aharon Levy, Andreas N\"urnberg, Eva Sickin

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

    Get PDF
    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

    A surface-potential-based compact model for partially-depleted silicon-on-insulator MOSFETs

    No full text
    With the continuous scaling of CMOS technologies, Silicon-on-Insulator (SOI) technologies have become more competitive compared to bulk, due to their lower parasitic capacitances and leakage currents. The shift towards high frequency, low power circuitry, coupled with the increased maturity of SOI process technologies, have made SOI a genuinely costeffective solution for leading edge applications. The original STAG2 model, developed at the University of Southampton, UK, was among the first compact circuit simulation models to specifically model the behaviour of Partially-Depleted (PD) SOI devices. STAG2 was a robust, surface-potential based compact model, employing closed-form equations to minimise simulation times for large circuits. It was able to simulate circuits in DC, small signal, and transient modes, and particular care was taken to ensure that convergence problems were kept to a minimum. In this thesis, the ongoing development of the STAG model, culminating in the release of a new version, STAG3, is described. STAG3 is intended to make the STAG model applicable to process technologies down to 100nm. To this end, a number of major model improvements were undertaken, including: a new core surface potential model, new vertical and lateral field mobility models, quantum mechanical models, the ability to model non-uniform vertical doping profiles, and other miscellaneous effects relevant to deep submicron devices such as polysilicon depletion, velocity overshoot, and the reverse short channel effect.As with the previous versions of STAG, emphasis has been placed on ensuring that model equations are numerically robust, as well as closed-form wherever possible, in order to minimise convergence problems and circuit simulation times. The STAG3 model has been evaluated with devices manufactured in PD-SOI technologies down to 0.25?m, and was found to give good matching to experimental data across a range of device sizes and biases, whilst requiring only a single set of model parameters

    Digital CMOS ISFET architectures and algorithmic methods for point-of-care diagnostics

    Get PDF
    Over the past decade, the surge of infectious diseases outbreaks across the globe is redefining how healthcare is provided and delivered to patients, with a clear trend towards distributed diagnosis at the Point-of-Care (PoC). In this context, Ion-Sensitive Field Effect Transistors (ISFETs) fabricated on standard CMOS technology have emerged as a promising solution to achieve a precise, deliverable and inexpensive platform that could be deployed worldwide to provide a rapid diagnosis of infectious diseases. This thesis presents advancements for the future of ISFET-based PoC diagnostic platforms, proposing and implementing a set of hardware and software methodologies to overcome its main challenges and enhance its sensing capabilities. The first part of this thesis focuses on novel hardware architectures that enable direct integration with computational capabilities while providing pixel programmability and adaptability required to overcome pressing challenges on ISFET-based PoC platforms. This section explores oscillator-based ISFET architectures, a set of sensing front-ends that encodes the chemical information on the duty cycle of a PWM signal. Two initial architectures are proposed and fabricated in AMS 0.35um, confirming multiple degrees of programmability and potential for multi-sensing. One of these architectures is optimised to create a dual-sensing pixel capable of sensing both temperature and chemical information on the same spatial point while modulating this information simultaneously on a single waveform. This dual-sensing capability, verified in silico using TSMC 0.18um process, is vital for DNA-based diagnosis where protocols such as LAMP or PCR require precise thermal control. The COVID-19 pandemic highlighted the need for a deliverable diagnosis that perform nucleic acid amplification tests at the PoC, requiring minimal footprint by integrating sensing and computational capabilities. In response to this challenge, a paradigm shift is proposed, advocating for integrating all elements of the portable diagnostic platform under a single piece of silicon, realising a ``Diagnosis-on-a-Chip". This approach is enabled by a novel Digital ISFET Pixel that integrates both ADC and memory with sensing elements on each pixel, enhancing its parallelism. Furthermore, this architecture removes the need for external instrumentation or memories and facilitates its integration with computational capabilities on-chip, such as the proposed ARM Cortex M3 system. These computational capabilities need to be complemented with software methods that enable sensing enhancement and new applications using ISFET arrays. The second part of this thesis is devoted to these methods. Leveraging the programmability capabilities available on oscillator-based architectures, various digital signal processing algorithms are implemented to overcome the most urgent ISFET non-idealities, such as trapped charge, drift and chemical noise. These methods enable fast trapped charge cancellation and enhanced dynamic range through real-time drift compensation, achieving over 36 hours of continuous monitoring without pixel saturation. Furthermore, the recent development of data-driven models and software methods open a wide range of opportunities for ISFET sensing and beyond. In the last section of this thesis, two examples of these opportunities are explored: the optimisation of image compression algorithms on chemical images generated by an ultra-high frame-rate ISFET array; and a proposed paradigm shift on surface Electromyography (sEMG) signals, moving from data-harvesting to information-focused sensing. These examples represent an initial step forward on a journey towards a new generation of miniaturised, precise and efficient sensors for PoC diagnostics.Open Acces

    Implementation and Characterisation of Monolithic CMOS Pixel Sensors for the CLIC Vertex and Tracking Detectors

    Get PDF
    Different CMOS technologies are being considered for the vertex and tracking layers of the detector at the proposed high-energy e+^{+}e^{−} Compact Linear Collider (CLIC). CMOS processes have been proven to be suitable for building high granularity, large area detector systems with low material budget and low power consumption. An effort is put on implementing detectors capable of performing precise timing measurements. Two Application-Specific Integrated Circuits (ASICs) for particle detection have been developed in the framework of this thesis, following the specifications of the CLIC vertex and tracking detectors. The process choice was based on a study of the features of each of the different available technologies and an evaluation of their suitability for each application. The CLICpix Capacitively Coupled Pixel Detector (C3PD) is a pixelated detector chip designed to be used in capacitively coupled assemblies with the CLICpix2 readout chip, in the framework of the vertex detector at CLIC. The chip comprises a matrix of 128×128 square pixels with 25 µm pitch. A commercial 180 nm High-Voltage (HV) CMOS process was used for the C3PD design. The charge is collected with a large deep N-well, while each pixel includes a preamplifier placed on top of the collecting electrode. The C3PD chip was produced on wafers with different values for the substrate resistivity (∼ 20, 80, 200 and 1000 Ωcm) and has been extensively tested through laboratory measurements and beam tests. The design details and characterisation results of the C3PD chip will be presented. The CLIC Tracker Detector (CLICTD) is a novel monolithic detector chip developed in the context of the silicon tracker at CLIC. The CLICTD chip combines high density, mixed mode circuits on the same substrate, while it performs a fast time-tagging measurement with 10 ns time bins. The chip is produced in a 180 nm CMOS imaging process with a High-Resistivity (HR) epitaxial layer. A matrix of 16×128 detecting cells, each measuring 300 × 30 µm2^{2} , is included. A small N-well is used to collect the charge generated in the sensor volume, while an additional deep N-type implant is used to fully deplete the epitaxial layer. Using a process split, additional wafers are produced with a segmented deep N-type implant, a modification that has been simulated to result in a faster charge collection time. Each detecting cell is segmented into eight front-ends to ensure prompt charge collection in the sensor diodes. A simultaneous 8-bit timing and 5-bit energy measurement is performed in each detecting cell. A detailed description of the CLICTD design will be given, followed by the first measurement results

    Design of a reliability methodology: Modelling the influence of temperature on gate Oxide reliability

    Get PDF
    An Integrated Reliability Methodology (IRM) is presented that encompasses the changes that technology growth has brought with it and includes several new device degradation models. Each model is based on a physics of failure approach and includes on the effects of temperature. At all stages the models are verified experimentally on modern deep sub-micron devices. The research provides the foundations of a tool which gives the user the opportunity to make appropriate trade-offs between performance and reliability, and that can be implemented in the early stages of product development

    Bio-inspired electronics for micropower vision processing

    No full text
    Vision processing is a topic traditionally associated with neurobiology; known to encode, process and interpret visual data most effectively. For example, the human retina; an exquisite sheet of neurobiological wetware, is amongst the most powerful and efficient vision processors known to mankind. With improving integrated technologies, this has generated considerable research interest in the microelectronics community in a quest to develop effective, efficient and robust vision processing hardware with real-time capability. This thesis describes the design of a novel biologically-inspired hybrid analogue/digital vision chip ORASIS1 for centroiding, sizing and counting of enclosed objects. This chip is the first two-dimensional silicon retina capable of centroiding and sizing multiple objects2 in true parallel fashion. Based on a novel distributed architecture, this system achieves ultra-fast and ultra-low power operation in comparison to conventional techniques. Although specifically applied to centroid detection, the generalised architecture in fact presents a new biologically-inspired processing paradigm entitled: distributed asynchronous mixed-signal logic processing. This is applicable to vision and sensory processing applications in general that require processing of large numbers of parallel inputs, normally presenting a computational bottleneck. Apart from the distributed architecture, the specific centroiding algorithm and vision chip other original contributions include: an ultra-low power tunable edge-detection circuit, an adjustable threshold local/global smoothing network and an ON/OFF-adaptive spiking photoreceptor circuit. Finally, a concise yet comprehensive overview of photodiode design methodology is provided for standard CMOS technologies. This aims to form a basic reference from an engineering perspective, bridging together theory with measured results. Furthermore, an approximate photodiode expression is presented, aiming to provide vision chip designers with a basic tool for pre-fabrication calculations
    corecore