Variation tolerant design methods for wideband low noise amplifiers

In this paper, we develop design techniques for reducing the impact of manufacturing variations on wideband low noise amplifiers (LNA). Utilizing an efficient modeling and circuit optimization method, we investigate the sensitivity of LNA performance metrics to process variations and determine that the input impedance matching is particularly sensitive to perturbations in component values. To mitigate the impact of process variations on the input impedance matching, we add additional circuit elements and tunable capacitors to dynamically compensate for manufacturing variations after fabrication. The results indicate that the proposed design techniques can increase manufacturing yield by up to one order of magnitude for input impedance matching with only a 14% increase in noise figure.     

Model order reduction using spline-based dynamic multi-point rational interpolation for passive circuits

The efficient modeling of integrated passive components and interconnects is vital for the realization of high performance mixed-signal systems. In this paper, we develop a dynamic multi-point rational interpolation method based on Krylov subspace techniques to generate reduced order models for passive components and interconnects that are accurate across a wide-range of frequencies. We dynamically select interpolation points by applying a cubic spline-based algorithm to detect complex regions in the system's frequency response. The results indicate that our method provides greater accuracy than techniques that apply uniform interpolation points.     

On the Impact of Process Variations for Carbon Nanotube Bundles for VLSI Interconnect

Bundles of single-walled carbon nanotubes (SWCNTs) have been proposed as a possible replacement for on-chip copper interconnect due to their large conductivity and current-carrying capabilities. Given the manufacturing challenges associated with future nanotube-based interconnect solutions, determining the impact of process variations on this new technology relative to standard copper interconnect is vital for predicting the reliability of nanotube-based interconnect. In this paper, we investigate the impact of process variations on future interconnect solutions based on carbon nanotube bundles. Leveraging an equivalent RLC model for SWCNT bundle interconnect, we calculate the relative impact of ten potential sources of variation in SWCNT bundle interconnect on resistance, capacitance, inductance, and delay. We compare the relative impact of variation for SWCNT bundles and standard copper wires as process technology scales and find that SWCNT bundle interconnect will typically have larger overall three-sigma variations in delay. In order to achieve the same percentage variation in both SWCNT bundles and copper interconnect, the percentage variation in bundle dimensions must be reduced by up to 63% in 22-nm process technology     

The growth of the passive film on iron in 0.05 M NaOH studied in situ by Raman micro‐spectroscopy and electrochemical polarisation. Part I: near‐resonance enhancement of the Raman spectra of iron oxide and oxyhydroxide compounds

Raman spectroscopy, in principle, is an excellent technique for the study of molecular species developed on metal surfaces during electrochemical investigations. However, the use of the more common laser wavelengths such as the 514.5‐nm line results in spectra of less than optimal intensity, particularly for iron oxide compounds. In the present work, near‐resonance enhancement of the Raman spectra was investigated for the iron oxide and iron oxyhydroxide compounds previously reported to be present in the passive film on iron, using a tuneable dye laser producing excitation wavelengths between 560 and 637 nm. These compounds were hematite (α‐Fe₂O₃), maghemite (γ‐Fe₂O₃), magnetite (Fe₃O₄), goethite (α‐FeOOH), akaganeite (β‐FeOOH), lepidocrocite (γ‐FeOOH) and feroxyhyte (δ‐FeOOH). Optimum enhancement, when compared to that with the 514.5‐nm line, was obtained for all the iron oxide and oxyhydroxide standard samples in the low wavenumber region (<1000 cm⁻¹) using an excitation wavelength of 636.4 nm. Particularly significant enhancement was obtained for lepidocrocite, hematite and goethite. Copyright © 2010 John Wiley & Sons, Ltd.     

Instrumental measurement of bitter taste in red wine using an electronic tongue

An electronic tongue (ET) based on potentiometric chemical sensors was assessed as a rapid tool for the quantification of bitterness in red wines. A set of 39 single cultivar Pinotage wines comprising 13 samples with medium to high bitterness was obtained from the producers in West Cape, South Africa. Samples were analysed with respect to a set of routine wine parameters and major phenolic compounds using Fourier transform infrared-multiple internal reflection spectroscopy (WineScan) and high-performance liquid chromatography, respectively. A trained sensory panel assessed the bitterness intensity of 15 wines, 13 of which had a bitter taste of medium to high intensity. Thirty-one wine samples including seven bitter-tasting ones were measured by the ET. Influence of the chemical composition of wine on the occurrence of the bitter taste was evaluated using one-way analysis of variance. It was found that bitter-tasting wines had higher concentrations of phenolic compounds (catechin, epicatechin, gallic and caffeic acids and quercetin) than non-bitter wines. Sensitivity of the sensors of the array to the phenolic compounds related to the bitterness was studied at different pH levels. Sensors displayed sensitivity to all studied compounds at pH 7, but only to quercetin at pH 3.5. Based on these findings, the pH of wine was adjusted to 7 prior to measurements. Calibration models for classification of wine samples according to the presence of the bitter taste and quantification of the bitterness intensity were calculated by partial least squares-discriminant analysis (PLS-DA) regression. Statistical significance of the classification results was confirmed by the permutation test. Both ET and chemical analysis data could discriminate between bitter and control wines with the correct classification rates of 94% and 91%, respectively. Prediction of the bitterness intensity with good accuracy (root mean square error of 2 and mean relative error of 6% in validation) was possible only using ET data.     

Analytical techniques for wine analysis: An African perspective; a review

Analytical chemistry is playing an ever-increasingly important role in the global wine industry. Chemical analysis of wine is essential in ensuring product safety and conformity to regulatory laws governing the international market, as well as understanding the fundamental aspects of grape and wine production to improve manufacturing processes. Within this field, advanced instrumental analysis methods have been exploited more extensively in recent years. Important advances in instrumental analytical techniques have also found application in the wine industry. This review aims to highlight the most important developments in the field of instrumental wine and grape analysis in the African context. The focus of this overview is specifically on the application of advanced instrumental techniques, including spectroscopic and chromatographic methods. Recent developments in wine and grape analysis and their application in the African context are highlighted, and future trends are discussed in terms of their potential contribution to the industry.     

Performance Implications of Inductive Effects for Carbon-Nanotube Bundle Interconnect

In this letter, we investigate the impact of inductance on bundles of single-walled carbon nanotubes (SWCNT) for future very large scale integration interconnect applications. Leveraging a scalable equivalent circuit model, we assess the relative impact of magnetic inductance and the worst case theoretical value of kinetic inductance on both delay and voltage overshoot. Based on our results, even if the worst case theoretical value for kinetic inductance is assumed, it will only increase the delay and the voltage overshoot by a maximum of 6% and 3%, respectively. Therefore, kinetic inductance will not be a significant factor in the future SWCNT bundle-based interconnect solutions     

Accurate Analytical Spiral Inductor Modeling Techniques for Efficient Design Space Exploration

Efficient modeling techniques are required to accelerate design space exploration for integrated spiral inductors. In this letter, closed-form modeling techniques for the inductor's physical inductance and substrate eddy currents are introduced. The model provides several orders of magnitude performance improvement over field-solver-based approaches with typical errors of less than 4% while demonstrating excellent agreement with measured data from fabricated inductors