An innovative design of spin transfer torque based ternary content addressable memory with match line sense amplifier

Ternary Content Addressable Memory (TCAM) device is integrated with Static-Random Access Memory unit to attain high production at a lesser cost. Moreover, the TCAM searching device performs faster parallel searching of whole memory in the entire time. Also, TCAM is constrained by its large area of the cell, extensive active state leakage current, and high power consumption for searching. In this present work, an innovative Spin Transfer Torque-TCAM (STT-TCAM) with Match Line Sensing Amplifier sensing scheme is developed to acquire trustworthy sensing functions with high speed. The projected scheme has pertained minimum consumption of power and high operating speed. The proposed method consumes a lesser amount of power and functions at a higher speed. It also exploits the least number of resources compared to the prevailing techniques. The proposed designing is done with the use of Xilinx vertex 6 simulation tools and it calculated the power, current, voltage, frequency and delay values used in this simulation. Hence, the attained parameters are compared with recent existing methods to prove the efficacy of the proposed TCAM model.

     

Knowledge spaces and places: From the perspective of a “born-global” start-up in the field of urban technology

The success of cities increasingly relies on its capacity to capitalize on its knowledge base, but also on its potential to anchor external knowledge and the strategies of knowledge-based firms. In this paper we analyze how a “born global” start-up firm is linked to different types of places, and how it explores and exploits different territorial innovation potentials. Our case company—i.e., Living PlanIT—develops, tests and sells smart city software to processes real-time information collected through sensors embedded in a city’s buildings and infrastructure towards energy savings and manifold efficiency gains. The paper illustrates how the interaction with different places and knowledge-based cities provides unique resources for the technology development, search, experimentation, market formation and societal legitimation. Beyond focusing on a place’s fixed knowledge assets, the paper empirically assesses the innovation functions of different types of knowledge-cities and temporary “non-places” such as international high-level events.     

Neural Network Based Thermal Analysis of Ultradeep Submicron Digital Circuit Design

With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network (ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model (PTM) nominal parameters has been done to compare with ANN (trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.     

High rate deposition of hard a-C:H films using microwave excited plasma enhanced CVD

High rate deposition processes for hydrogenated diamond-like carbon films (a-C:H) were developed using microwave plasma enhanced CVD (PECVD) techniques. Basic investigations were carried out in a laboratory scale deposition apparatus (0.04 m³ chamber) and after that the processes were transferred to an industrial scale PECVD machine (1 m³) and optimized therein. The application of an asymmetric bipolar pulsed mid-frequency substrate bias allowed controlling the ion fluxes to the growing films independently of the generation of film forming species (radicals and ions) by the microwave plasma source. After preliminary experiments using five different hydrocarbon precursors, more thorough investigations were done with the selected precursors acetylene (C₂H₂) and isobutene (C₄H₈; isobutylene, 2-Methyl-1-propene). The a-C:H films were characterised with respect to deposition rates, hardness, abrasive wear rates, internal stresses and topography.Wear resistant, atomically smooth a-C:H films with a hardness above 25 GPa were deposited at a very high rate of 15 μm/h. The combination of high rate and high hardness values should be promising for industrial applications, even for in-line technologies. For the both mentioned precursors C₂H₂ and C₄H₈ some differences in hardness–rate relations were observed.     

Energy- and exergy-based comparison of coal-fired and nuclear steam power plants

The results are reported of energy- and exergy-based comparisons of coal-fired and nuclear electrical generating stations. A version of a process-simulation computer code, previously enhanced by the author for exergy analysis, is used. Overall energy and exergy efficiencies, respectively, are 37% and 36% for the coal-fired process, and 30% and 30% for the nuclear process. The losses in both plants exhibit many common characteristics. Energy losses associated with emissions (mainly with spent cooling water) account for all of the energy losses, while emission-related exergy losses account for approximately 10% of the exergy losses. The remaining exergy losses are associated with internal consumptions, mainly in components which generate heat by combustion or nuclear reactions, and in components which transfer heat across large temperature differences. It is anticipated that the results will prove useful to those involved in the improvement of existing and design of future electrical generating stations.     

Thermal vaporization and deposition of gallium oxide in hydrogen

The thermodynamics of gallium oxide vaporization and deposition in Ar–6% H₂ at elevated temperatures are described. It is shown that Ga₂O₃ vaporizes in H₂ as Ga₂O(g) at elevated temperatures. During thermal processing the Ga₂O(g) moves to cooler zones of the furnace, back reacts with H₂(g) and H₂O(g) and condenses out as Ga(l) and Ga₂O₃(s). Upon removal from the furnace, the exposed Ga forms a ubiquitous surface oxide of Ga₂O₃. X-ray photoelectron spectroscopy (XPS) was used to examine heat treated Ga₂O₃ powders and vaporization products deposited onto SiO₂ and Cu substrates. In agreement with the thermodynamic predictions, these data demonstrate that the deposition product contained Ga₂O₃ and metallic Ga. Analysis of the XPS spectra also revealed an intermediate oxidation state for Ga. The precise bonding of this state could not be demonstrated conclusively, but it is suggested that it may be solid Ga₂O. For coherent product deposition on Cu the metallic Ga concentration increases and the Ga₂O₃ concentration decreases with sputtering depth, suggesting the metallic Ga in the outermost layers of the deposit is readily oxidized during air exposure.     

A neuro-fuzzy controller for a stoker-fired boiler,based on behavior modeling

A key issue in an industrial stoker-fired boiler is the design of an efficient and robust controller for its combustion system, so that the boiler can provide a continuous supply of steam at the desired pressure conditions. However, it is difficult to achieve this objective by using a model-based approach because of the high nonlinearity and uncertainty of boiler systems. In addition, the control performance may also suffer as a result of strong load changes, large disturbances, large time lags, and so forth. This paper presents a behavior-modeling-based approach to the design of a neuro-fuzzy controller for the combustion control of a stoker-fired boiler. In this approach, boiler combustion processes with unknown structure are modeled by defining three dynamic behaviors. According to these behavior ‘templates’, their corresponding fuzzy-logic controllers can be optimized off-line. During boiler system operation, the appropriate fuzzy-logic controller is fired, based on an on-line assessment of its dynamic behavior. The application results obtained demonstrate the effectiveness and the robustness of the proposed controller.     

Electrostatic Investigation of Intended Source Drain Ultra Thin Body FD-SOI MOSFET

Silicon - In this paper, the proposed modified source and modified drain fully depleted silicon-on-insulator metal oxide semiconductor field effect transistor (FD-SOI MOSFET) presents better...     

Modelling of surface finish,electrode wear and material removal rate in electrical discharge machining of hard-to-machine alloys

Hard-to-machine alloys are commonly used for industrial applications in the aeronautical, nuclear and automotive sectors, where the materials must have excellent resistance to corrosion and oxidation, high temperature resistance and high mechanical strength. In this present study the influence of different parameters of the electrical discharge machining process on surface roughness, electrode wear and material removal rate have been studied. Regression techniques are employed to model arithmetic mean deviation Ra (μm), peak count Pc (1/cm), material removal rate MRR (mm³/min) and electrode wear EW (%). All these parameters have been studied in terms of current intensity supplied by the generator of the electrical discharge machine I (A), pulse time t_i (μs), duty cycle η and open-circuit voltage U (V). This modelling allows us to obtain mathematical data and models to predict that the most influential factor in MRR and Ra is the current intensity and in the case of EW and Pc is the pulse time.     

Tuning the mechanical performance and adhesion of polyurethane UV cured coatings by composition of acrylic reactive diluents

An approach to modify the properties of UV curable polyurethane coatings by altering the amount and functionality of acrylic reactive diluents, in order to optimize the coating performance, is demonstrated. Based on the rheology analysis, a model of the rheological behavior of the UV curable materials depending on the amount and type of a reactive diluent in the composition is demonstrated in this study. The relationships between the rheological behavior, the mechanical properties and adhesion of the coatings prepared from polyurethane UV curable compositions containing different amounts and functionalities of acrylic reactive diluents, have been investigated and discussed in this study. Based on the results of the study, the desired properties of UV cured coatings can be modeled and controlled without changing the nature of a particularly selected oligomer, thus maintaining the advantages of its chemical structure in a coating composition.