Intrinsic parameter fluctuations in decananometer MOSFETs introduced by gate line edge roughness

In this paper, we use statistical three-dimensional (3-D) simulations to study the impact of the gate line edge roughness (LER) on the intrinsic parameters fluctuations in deep decananometer (sub 50 nm) gate MOSFETs. The line edge roughness is introduced using a Fourier synthesis technique based on the power spectrum of a Gaussian autocorrelation function. In carefully designed simulation experiments, we investigate the impact of the rms amplitude /spl Delta/ and the correlation length /spl Lambda/ on the intrinsic parameter fluctuations in well scaled, but simple devices with fixed geometry as well as the channel length and width dependence of the fluctuations at fixed LER parameters. For the first time, we superimpose in the simulations LER and random discrete dopants and investigate their relative contribution to the intrinsic parameter fluctuations in the investigated devices. For particular MOSFET geometries, we were able to identify the regions where each of these two sources of intrinsic parameter fluctuations dominates

Simulation of intrinsic parameter fluctuations in decananometer and nanometer-scale MOSFETs

Intrinsic parameter fluctuations introduced by discreteness of charge and matter will play an increasingly important role when semiconductor devices are scaled to decananometer and nanometer dimensions in next-generation integrated circuits and systems. In this paper, we review the analytical and the numerical simulation techniques used to study and predict such intrinsic parameters fluctuations. We consider random discrete dopants, trapped charges, atomic-scale interface roughness, and line edge roughness as sources of intrinsic parameter fluctuations. The presented theoretical approach based on Green's functions is restricted to the case of random discrete charges. The numerical simulation approaches based on the drift diffusion approximation with density gradient quantum corrections covers all of the listed sources of fluctuations. The results show that the intrinsic fluctuations in conventional MOSFETs, and later in double gate architectures, will reach levels that will affect the yield and the functionality of the next generation analog and digital circuits unless appropriate changes to the design are made. The future challenges that have to be addressed in order to improve the accuracy and the predictive power of the intrinsic fluctuation simulations are also discussed

RTS amplitudes in decananometer MOSFETs: 3-D simulation study

In this paper we study the amplitudes of random telegraph signals (RTS) associated with the trapping of a single electron in defect states at the Si/SiO/sub 2/ interface of sub-100-nm (decananometer) MOSFETs employing three-dimensional (3-D) "atomistic" simulations. Both continuous doping charge and random discrete dopants in the active region of the MOSFETs are considered in the simulations. The dependence of the RTS amplitudes on the position of the trapped charge in the channel and on device design parameters such as dimensions, oxide thickness and channel doping concentration is studied in detail. The 3-D simulations offer a natural explanation for the large variation in the RTS amplitudes measured experimentally in otherwise identical MOSFETs. The random discrete dopant simulations result in RTS amplitudes several times higher compared to continuous charge simulations. They also produce closer to the experimentally observed distributions of the RTS amplitudes. The results highlight the significant impact of single charge trapping in the next generation decananometer MOSFETs

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

Optimization and evaluation of variability in the programming window of a flash cell with molecular metal-oxide storage

We report a modeling study of a conceptual nonvolatile memory cell based on inorganic molecular metal-oxide clusters as a storage media embedded in the gate dielectric of a MOSFET. For the purpose of this paper, we developed a multiscale simulation framework that enables the evaluation of variability in the programming window of a flash cell with sub-20-nm gate length. Furthermore, we studied the threshold voltage variability due to random dopant fluctuations and fluctuations in the distribution of the molecular clusters in the cell. The simulation framework and the general conclusions of our work are transferrable to flash cells based on alternative molecules used for a storage media

Comprehensive Investigation of Statistical Effects in Nitride Memories-Part I: Physics-Based Modeling

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Probabilistic computing with future deep sub-micrometer devices: a modelling approach

An approach is described that investigates the potential of probabilistic "neural" architectures for computation with deep sub-micrometer (DSM) MOSFETs. Initially, noisy MOSFET models are based upon those for a 0.35 /spl mu/m MOS technology with an exaggerated 1/f characteristic. We explore the manifestation of the 1/f characteristic at the output of a 2-quadrant multiplier when the key n-channel MOSFETs are replaced by "noisy" MOSFETs. The stochastic behavior of this noisy multiplier has been mapped on to a software (Matlab) model of a continuous restricted Boltzmann machine (CRBM) - an analogue-input stochastic computing structure. Simulation of this DSM CRBM implementation shows little degradation from that of a "perfect" CRBM. This paper thus introduces a methodology for a form of "technology-downstreaming" and highlights the potential of probabilistic architectures for DSM computation

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