Thermionic emission model of electron gate current in submicronNMOSFETs

A thermionic emission model based on a non-Maxwellian electron energy distribution function for the electron gate current in NMOSFET's is described. The model uses hydrodynamic equations to describe more correctly the electron transport and gate injection phenomena in submicron devices. A generalized analytical function is used to describe the high-energy tail of the electron energy distribution function. Coefficients of this generalized function are determined by comparing simulated gate currents with the experimental data. This model also includes the self-consistent calculation of the tunneling component of the gate current by using the WKB approximation, and by using a more accurate representation of the oxide barrier by including the image potential. Good agreement with gate currents over a wide range of bias conditions for three different technological sets of devices are demonstrated by using a single set of coefficients     

Tribological Performance of Bamboo Fabric Reinforced Epoxy Composites

Bamboo fiber is one of the strongest natural fibers with high strength-to-weight and stiffness-to-weight ratios and can be used economically for manufacturing fiber-reinforced composites. In this paper, bamboo fabric-reinforced epoxy composite is manufactured and its tribological properties for load-bearing applications are investigated. Sliding wear tests are conducted using a linear reciprocating tribometer and the effect of dry and lubricated contact conditions, applied load, sliding speed, temperature, and woven fabric direction on the coefficient of friction and wear rate are investigated. A scanning electron microscope is used to define the wear mechanisms at room and elevated temperatures. It is observed that the fabric orientation influences the mechanical and tribological performances of the composite material. Wear rate increases at higher loads and working temperatures; however, the effect of sliding speed is not remarkable, especially under lubricated contact conditions. The results present in this paper can be used for designing bamboo-reinforced epoxy composites for load-bearing applications, under different working conditions.     

Hydrogen and CO2 Management in the Refinery with Fuzzy Multiobjective Nonlinear Programming

An innovative approach for optimization of the hydrogen network in a refinery is presented. The optimization problem was formulated as a fuzzy‐based multiobjective nonlinear programming (FMONLP), aiming at simultaneous minimization of the total annual cost and CO₂ emission. This is achieved by defining an objective function with a weighted sum of the annual cost and CO₂ emission. The weighting factors are considered as fuzzy parameters which are described based on the experts' experiences. The applicability of the proposed approach is illustrated by optimization of an Iranian refinery hydrogen network.     

Experimental study of the flow structure in a counter flow Ranque–Hilsch vortex tube

The mechanism of the temperature separation in a Ranque–Hilsch vortex tube has been investigated since the discovery of this phenomenon. In spite of being investigated by many researchers, no consensus has yet been reached regarding the mechanism’s hypothesis.This paper reports on a study in progress exploring the temperature separation in a counter-flow vortex tube. The effects of the geometrical parameters, including inlet nozzles, cold exit, hot exit and length of the tube, were investigated, which indicated the settings for the best performance of the vortex tube. Flow properties in the vortex tube were measured and used to understand the flow structure inside the tube. Accurate measurements of the three-dimensional velocity distribution in the tube were conducted. The results provided enough evidence that the flow in the tube consists of a forced vortex formed near the inlet gradually transforming to a free vortex at the hot end. Experimental results found in this research show the vortex transformation along the tube and support the hypothesis proposed in previous study.     

An effective stress-based parametric study on the seismic stability of unsaturated slopes with implications for preliminary microzonation

Bulletin of Engineering Geology and the Environment - The stability of unsaturated slopes under seismic loading has become an important issue over the past few years which is the indication of its...     

Chemical vapor deposition and electrical characterization of sub-10 nm diameter InSb nanowires and field-effect transistors

Synthesis of InSb nanowires using a chemical vapor deposition technique, as a function of growth temperature and time, was investigated. High aspect ratio InSb nanowires, having a diameter of about 5–10 nm, were grown at 400 °C for 1 h on InSb (1 1 1) substrate onto which 60 nm Au particle was used as a metal catalyst. The synthesized InSb nanowires had zinc blend single crystal structure without any stacking faults, and they were covered with a thin (∼1 nm thick) amorphous layer. Electrical characterization of InSb nanowires was conducted utilizing a back-gated SNWFET. Device characterization demonstrated that NWs were n-type and exhibited a high I_on/I_off ratio of 10⁶ and device resistance of 250 kΩ.     

A static friction model for tube bulge forming using a solid bulging medium

In a metal working process, the friction between the material and the tools influences the process by modifying the strain distribution of the workpiece. From a numerical point of view, a constant coefficient of friction (Coulomb’s friction) is commonly used in finite element simulations to model the frictional behaviour of contacting solids. However, friction coefficient varies in time and space with many parameters. We presented here a theoretical model of static friction in rubber/metal contact which allows the determination of the static coefficient of friction as a function of local contact conditions. Simulations using finite element software ABAQUS/Explicit were carried out for an axisymmetric tube bulging operation using the defined friction model. We compared the computed tube thickness related to the constant coefficient of static friction with the defined friction model. The results clearly showed that the new friction model provides better agreement between experiments (Girard, Grenier, Mac Donald, J Mater Process Technol 172:346–355, 2006) and results of numerical simulations.     

A new approach to verify and derive a transverse-field-dependentmobility model for electrons in MOS inversion layers

A modeling approach is described that extracts the functional dependence of carrier mobility on local transverse and longitudinal fields, channel doping, fixed interface charge, and temperature in MOS inversion and accumulation layers directly from the experimentally measured effective (or average) mobility. This approach does not require a priori detailed knowledge of the experimental variation of mobility within the inversion or accumulation layer, and it can be used to evaluate the validity of other models described in the literature. Also, an improved transverse-field dependent mobility model is presented for electrons in MOS inversion layers that was developed using this new modeling approach. This model has been implemented in the PISCES 2-D device simulation program. Comparisons of the calculated versus measured data show excellent agreement for I_D-V_G and I_D-V_D curves for devices with L_eff=0.5 to 1.2 μm     

Microgrid dynamic responses enhancement using artificial neural network‐genetic algorithm for photovoltaic system and fuzzy controller for high wind speeds

The microgrid (MG) is described as an electrical network of small modular distributed generation, energy storage devices and controllable loads. In order to maximize the output of solar arrays, maximum power point tracking (MPPT) technique is used by artificial neural network (ANN), and also, control of turbine output power in high wind speeds is proposed using pitch angle control technic by fuzzy logic. To track the maximum power point (MPP) in the photovoltaic (PV), the proposed ANN is trained by the genetic algorithm (GA). In other word, the data are optimized by GA, and then these optimum values are used in ANN. The simulation results show that the ANN‐GA in comparison with the conventional algorithms with high accuracy can track the peak power point under different insolation conditions and meet the load demand with less fluctuation around the MPP; also it can increase convergence speed to achieve MPP. Moreover, pitch angle controller based on fuzzy logic with wind speed and active power as inputs that have faster responses which leads to have flatter power curves enhances the dynamic responses of wind turbine. The models are developed and applied in Matlab/Simulink. Copyright © 2015 John Wiley & Sons, Ltd.