Minimizing power dissipation in optical interconnects at low voltage using optimal modulator design

A strong motivation for insertion of optical interconnects in short-distance applications such as chip-to-chip or back-plane communication, apart from high bit rates, is their potential to achieve these bit rates at low power compared to the currently prevalent copper based interconnects. Thus, it is imperative to construct design methodologies which minimize the total optical link power dissipation. We present one such methodology, where we optimize the quantum-well modulators to minimize the power dissipation in modulator-based optical interconnects. In the first part of the paper, the focus is on obtaining the optimal modulator metrics [contrast ration (CR) and insertion loss], which yield the lowest total power (receiver and the modulator). The trends are studied as a function of the input laser power and bit rate. Having obtained the desirable modulator metrics and the corresponding power dissipation, in the second part, the focus is on the feasibility of these metrics in the light of voltage swing constraints. The biggest concern with the modulator based optical link is the low CR, especially at low voltage swing. While studying these concerns, we also provide insight into the physical design of the modulator including, its intrinsic region thickness, pre-bias voltage, and the size and the number of quantum-wells. Specifically, we outline the method to obtain the design parameters, which allows minimum power dissipation with the least laser power. This ultimately yields higher aggregate I/O bandwidth for chip to chip communication in power limited chips.     

A fast algorithm and practical considerations for passive macromodeling of measured/simulated data

Passive macromodeling of high-speed package and interconnect modules characterized by measured/simulated data has generated immense interest during the recent years. This paper presents an efficient algorithm for transient simulation of interconnect networks characterized by measured/simulated data in the presence of other linear and nonlinear devices. A new set of linear constraints are proposed, which help in preserving the passivity of resulting macromodels. Examples are presented to demonstrate the validity and efficiency of the proposed algorithm.     

SiO2 degradation with charge injection polarity

We have investigated gate oxide degradation in metal-oxide-semiconductor (MOS) devices as a function of high-field constant-current stress for charge injection from both gate and substrate. The two polarities are asymmetric: gate injection, where the substrate Si-SiO₂ interface is the collecting electrode for the energetic electrons, shows a higher rate of interface-state generation (ΔD_it) and lower charge-to-breakdown Q_bd. Thus the collecting electrode interface, which suffers primary damage, emerges as a critical degradation site in addition to the injecting electrode interface, which has been the traditional focus. Consistent with a physical-damage model of breakdown, we demonstrate that interfacial degradation is an important precursor of breakdown, and that the nature of breakdown-related damage is physical, such as trap-generation by broken bonds     

Thermal studies of Cr2O3 doped CaCO3-SiO2 (2∶1) system

Mixtures of CaCO₃SiO₂ in 21 molar ratio were subjected separated to thermal analysis with varying concentration of Cr₂O₃ (0.1 to 5%) as dopant. The activation energy (E _a) and enthalpy (H) shows a decreasing trend with 0.1 to 1% Cr₂O₃ and attains a minimum value with 1% dopant. 0.1 to 0.5% Cr₂O₃ helps in the formation of and C₂S, (Cement Chemistry notations, C = CaO, S = SiO₂) phases at 1400° C and above but 1% Cr₂O₃ stabilizes -C₂S phase along with a little free lime and CaCrO₄. A small quantity of CaCrO₄, Cr₂SiO₂ and -C₂S are also formed along with the major phases with 5% Cr₂O₃ indicating that Cr³⁺ can substitute both Ca²⁺ and Si⁴⁺ ions in the C₂S lattice.     

Chemical composition and bond structure of carbon-nitride films deposited by CH4/N2 dielectric barrier discharge

Carbon nitride films have been deposited by dielectric barrier discharge with a CH₄/N₂ gas mixture at different conditions. Fourier Transform Infrared (FTIR) spectroscopy, X-ray photo electron spectroscopy (XPS), Raman spectroscopy, Atomic force microscopy (AFM) and ellipsometry were used to systematically study chemical composition, bond structure and surface morphology of deposited films. Various bonds between carbon, nitrogen, hydrogen, and also oxygen were observed.     

Microstructure and properties of flame sprayed tungsten carbide coatings

This article reports on feasibility experiments carried out with oxy-acetylene spray system with various oxygen to fuel ratios using two different tungsten carbide powders and powder feeding methods, to evaluate the newly developed fused WC, synthesised by transferred arc thermal plasma method. Transferred arc thermal plasma method is more economical and less energy intensive than the conventional arc method and results in a fused carbide powder with higher hardness. The microstructure and phase composition of powders and coatings were analysed by optical and scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction. Carbon content of the powders and coatings were determined to study the decarburisation of the material during spraying process. Coatings were also characterised by their hardness and abrasive wear. The effects of metallurgical transformation and phase content are related to wear performance. The results demonstrate that the powders exhibit various degree of phase transformation during the spray process depending on the type of powder, powder feeding and spray parameters. The carbon loss during the spray process in excess of 45% resulted in reduced hardness and wear resistance of the coatings. Coatings with high amount of WC and W₂C along with FeW₃C showed higher wear resistance. Thus, coatings of high wear resistance can be produced using fused tungsten carbide powder with WC and W₂C phases, which can be economically synthesised by thermal plasma transferred arc method.     

Multi-objective reactive power market clearing in competitive electricity market using HFMOEA

This paper presents an application of a hybrid fuzzy multi-objective evolutionary algorithm (HFMOEA) for solving a highly constraint, mixed integer type, complex multi-objective reactive power market clearing (RPMC) problem for the competitive electricity market environment. In HFMOEA based multi-objective optimization approach, based on the output of a fuzzy logic controller crossover and mutation probabilities are varied dynamically. It enhances stochastic search capabilities of HFMOEA. In multi-objective RPMC optimization framework, two objective functions namely the total payment function (TPF) for reactive power support from generators and synchronous condensers and the total real transmission loss (TRTL) are minimized simultaneously for clearing the reactive power market. The proposed HFMOEA based multi-objective RPMC scheme is tested on a standard IEEE 24 bus reliability test system and its performance is compared with five other multi-objective evolutionary techniques such as MOPBIL, NSGA-II, UPS-EMOA and SPEA-2 and a new extended form of NSGA (ENSGA-II). Applying all these six evolutionary techniques, a detailed statistical analysis using T-test and boxplots is carried out on three performance metrics (spacing, spread and hypervolume) data for RPMC problem. The obtained simulation results confirm the overall superiority of HFMOEA to generate better Pareto-optimal solutions with higher convergence rate as compared to above mentioned algorithms. Further, TPF and TRTL values corresponding to the best compromise solutions are obtained using said multi-objective evolutionary techniques. These values are compared with one another to take better market clearing decisions in competitive electricity environment.     

NodeWiz: Fault-tolerant grid information service

Large scale grid computing systems may provide multitudinous services, from different providers, whose quality of service will vary. Moreover, services are deployed and undeployed in the grid with no central coordination. Thus, to find out the most suitable service to fulfill their needs, or to find the most suitable set of resources on which to deploy their services, grid users must resort to a Grid Information Service (GIS). This service allows users to submit rich queries that are normally composed of multiple attributes and range operations. The ability to efficiently execute complex searches in a scalable and reliable way is a key challenge for current GIS designs. Scalability issues are normally dealt with by using peer-to-peer technologies. However, the more reliable peer-to-peer approaches do not cater for rich queries in a natural way. On the other hand, approaches that can easily support these rich queries are less robust in the presence of failures. In this paper we present the design of NodeWiz, a GIS that allows multi-attribute range queries to be performed efficiently in a distributed manner, while maintaining load balance and resilience to failures.     

Uncertainty propagation in puff-based dispersion models using polynomial chaos

Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these uncertainties through the dispersion models is crucial for a reliable prediction of the probability distribution of the states and assessment of risk. A simple three-dimensional Gaussian puff-based dispersion model is used as a test case to study the effect of uncertainties in the model parameters and initial conditions on the output concentration. A polynomial chaos based approach is used to numerically investigate the evolution of the model output uncertainties due to initial condition and parametric uncertainties. The polynomial chaos solution is found to be an accurate approximation to ground truth, established by Monte Carlo simulation, while offering an efficient computational approach for large nonlinear systems with a relatively small number of uncertainties.     

Classification of patterns representing Apples and Oranges in three-qubit system

The study of the classification of Apples and Oranges in a warehouse has been undertaken in a three-qubit system using the method of repeated iterations in Grover’s algorithm and Ventura’s algorithm separately. Operator describing an inversion about average has been constructed as a square matrix of order eight, the phase inversion operators and corresponding iteration operators for patterns separately representing Apples and Oranges have been derived, and various possible superpositions as the choice for search states for the classification of these patterns have been obtained for starting states consisting of two patterns and a single pattern, respectively. It has been demonstrated that on the second iteration of the exclusion superposition by the corresponding iteration operators, the patterns Apples and Oranges, respectively, are most suitably classified using the Grover’s algorithm. The probabilities of classifications of Apples have also been calculated by using Ventura’s algorithm (Ventura and Martinez in Inf Sci 124:273–296, 2000; Found Phys Lett 12:547–559, 1999) for all the possible superpositions as the search states, and the results have been compared with those of Grover’s algorithm and it has been demonstrated that in general for classification of a given pattern (Apples) in three-qubit system, the Grover’s and Ventura’s algorithms are effective in the cases where the number of patterns in the stored database is larger or smaller, respectively.