Validity of the parabolic effective mass approximation in silicon and germanium n-MOSFETs with different crystal orientations

This paper investigates the validity of the parabolic effective mass approximation (EMA), which is almost universally used to describe the size and bias-induced quantization in n-MOSFETs. In particular, we compare the EMA results with a full-band quantization approach based on the linear combination of bulk bands (LCBB) and study the most relevant quantities for the modeling of the mobility and of the on-current of the devices, namely, the minima of the 2-D subbands, the transport masses, and the electron density of states. Our study deals with both silicon and germanium n-MOSFETs with different crystal orientations and shows that, in most cases, the validity of the EMA is quite satisfactory. The LCBB approach is then used to calculate the values of the effective masses that help improve the EMA accuracy. There are crystal orientations, however, where the 2-D energy dispersion obtained by the LCBB method exhibits features that are difficult to reproduce with the EMA model

Monte Carlo study of current variability in UTB SOI DG MOSFETs

The scaling of conventional silicon based MOSFETs is increasingly difficult into the nanometer regime due to short channel effects, tunneling and subthreshold leakage current. Ultra-thin body silicon-on-insulator based architectures offer a promising alternative, alleviating these problems through their geometry. However, the transport behaviour in these devices is more complex, especially for silicon thicknesses below 10 nm, with enhancement from band splitting and volume inversion competing with scattering from phonons, Coulomb interactions, interface roughness and body thickness fluctuation. Here, the effect of the last scattering mechanism on the drive current is examined as it is considered a significant limitation to device performance for body thicknesses below 5 nm. A simulation technique that properly captures non-equilibrium transport, includes quantum effects and maintains computational efficiency is essential for the study of this scattering mechanism. Therefore, a 3D Monte Carlo simulator has been developed which includes this scattering effect in an ab initio fashion, and quantum corrections using the Density Gradient formalism. Monte Carlo simulations using `frozen field' approximation have been carried out to examine the dependence of mobility on silicon thickness in large, self averaging devices. This approximation is then used to carry out statistical studies of uniquely different devices to examine the variability of on-current. Finally, Monte Carlo simulations self consistent with Poisson's equation have been carried out to further investigate this mechanism

Exploiting smallest error to calibrate non-linearity in SAR ADCs

This paper presents a statistics-optimised organisation technique to achieve better element matching in Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) in smart sensor systems. We demonstrate the proposed technique ability to achieve a significant improvement of around 23 dB on Spurious Free Dynamic Range (SFDR) of the ADC than the conventional, testing with a capacitor mismatch σu = 0.2% in a 14 bit SAR ADC system. For the static performance, the max root mean square (rms) value of differential nonlinearity (DNL) reduces from 1.63 to 0.20 LSB and the max rms value of integral nonlinearity (INL) reduces from 2.10 to 0.21 LSB. In addition, it is demonstrated that by applying grouping optimisation and strategy optimisation, the performance boosting on SFDR can be effectively achieved. Such great improvement on the resolution of the ADC only requires an off-line pre-processing digital part

Fusion of radioactive 132^{132}Sn with 64^{64}Ni

Evaporation residue and fission cross sections of radioactive $^{132}$Sn on $^{64}$Ni were measured near the Coulomb barrier. A large sub-barrier fusion enhancement was observed. Coupled-channel calculations including inelastic excitation of the projectile and target, and neutron transfer are in good agreement with the measured fusion excitation function. When the change in nuclear size and shift in barrier height are accounted for, there is no extra fusion enhancement in $^{132}$Sn+$^{64}$Ni with respect to stable Sn+$^{64}$Ni. A systematic comparison of evaporation residue cross sections for the fusion of even $^{112-124}$Sn and $^{132}$Sn with $^{64}$Ni is presented.Comment: 9 pages, 11 figure

Large-scale simulations of intrinsic parameter fluctuations in nano-scale MOSFETs

Intrinsic parameter fluctuations have become a serious obstacle to the continued scaling of MOSFET devices, particularly in the sub-100 nm regime. The increase in intrinsic parameter fluctuations means that simulations on a statistical scale are necessary to capture device parameter distributions. In this work, large-scale simulations of samples of 100,000s of devices are carried out in order to accurately characterise statistical variability of the threshold voltage in a real 35 nm MOSFET. Simulations were performed for the two dominant sources of statistical variability – random discrete dopants (RDD) and line edge roughness (LER). In total ∼400,000 devices have been simulated, taking approximately 500,000 CPU hours (60 CPU years). The results reveal the true shape of the distribution of threshold voltage, which is shown to be positively skewed for random dopants and negatively skewed for line edge roughness. Through further statistical analysis and data mining, techniques for reconstructing the distributions of the threshold voltage are developed. By using these techniques, methods are demonstrated that allow statistical enhancement of random dopant and line edge roughness simulations, thereby reducing the computational expense necessary to accurately characterise their effects. The accuracy of these techniques is analysed and they are further verified against scaled and alternative device architectures. The combined effects of RDD and LER are also investigated and it is demonstrated that the statistical combination of the individual RDD and LER-induced distributions of threshold voltage closely matches that obtained from simulations. By applying the statistical enhancement techniques developed for RDD and LER, it is shown that the computational cost of characterising their effects can be reduced by 1–2 orders of magnitude

Impact of randomly distributed dopants on Ω-gate junctionless silicon nanowire transistors

This paper presents experimental and simulation analysis of an Ω-shaped silicon junctionless nanowire field-effect transistor (JL-NWT) with gate lengths of 150 nm and diameter of the Si channel of 8 nm. Our experimental measurements reveal that the ON-currents up to 1.15 mA/μm for 1.0 V and 2.52 mA/μm for the 1.8-V gate overdrive with an OFF-current set at 100 nA/μm. Also, the experiment data reveal more than eight orders of magnitude ON-current to OFF-current ratios and an excellent subthreshold slope of 66 mV/dec recorded at room temperature. The obtained experimental current-voltage characteristics are used as a reference point to calibrate the simulations models used in this paper. Our simulation data show good agreement with the experimental results. All simulations are based on drift-diffusion formalism with activated density gradient quantum corrections. Once the simulations methodology is established, the simulations are calibrated to the experimental data. After this, we have performed statistical numerical experiments of a set of 500 different JL-NWTs. Each device has a unique random distribution of the discrete dopants within the silicon body. From those statistical simulations, we extracted important figures of merit, such as OFF-current and ON-current, subthreshold slope, and voltage threshold. The performed statistical analysis, on samples of those 500 JL-NWTs, shows that the mean ID-VGs characteristic is in excellent agreement with the experimental measurements. Moreover, the mean ID-VGs characteristic reproduces better the subthreshold slope data obtained from the experiment in comparison to the continuous model simulation. Finally, performance predictions for the JL transistor with shorter gate lengths and thinner oxide regions are carried out. Among the simulated JL transistors, the configuration with 25-nm gate length and 2-nm oxide thickness shows the most promising characteristics offering scalable designs