Au/Pt/Ti/Ni ohmic contacts to p-ZnTe

Ohmic contacts of Au/Pd/Ti/Ni to p-ZnTe show a minimum specific contact resistance of 10^-6 Ωcm² for a p-type doping level of 3×10¹⁹ cm^-3 and at an annealing temperature of 300°C. The Ni and Ti layers are very effective in improving the electrical properties of these contact     

Raman spectroscopy of carbon fibres

Investigations of coated carbon fibres are reported using Raman spectroscopy. Relationships between different process parameters (for example precursor concentration, reactor temperature and various precursors) and the resulting types of carbon fibres are discussed.     

Pulse-width tunable, self-frequency conversion of short opticalpulses over 200 nm based on supercontinuum generation

Self-frequency conversion of ultrashort optical pulses into arbitrary multiwavelength components without the use of a pump is achieved by using supercontinuum generation. Frequency conversion of a randomly-modulated 1.535-1.560 μm, 2.5 ps pulse stream at 6.3 Gbit/s into 1.41-1.64 μm, 0.29-1.0 ps pulse streams is demonstrated for the first time. The method features ultrawide tunability of over 200 nm, and multiwavelength, pulsewidth-tunable output for flexible WDM distribution networks     

Surface heating and energy transfer in pulsed microwave catalytic systems: A microwave-induced acoustic study

Since the early demonstrations of our concept of pulsed microwave catalysis in chemistry, we have witnessed the coming of age of the technique as an enabling technology in the industrial world, despite the inadequate understanding of the basic mechanisms of how microwaves interact with metallic surface sites and the subsequent energy transfer. We shall present here some very recent developments of the microwave-induced acoustic technique and its applications to a better understanding of the basic surface heating and energy transfer phenomena in pulsed microwave catalytic systems.     

Resonance ionization spectroscopy for trace analysis and fundamental research

Resonance ionization spectroscopy (RIS) and its combination with mass spectrometry (RIMS) have grown to become powerful techniques, which offer high sensitivity as well as elemental and isotopic selectivity. The principles of RIS and RIMS are introduced; they primarily concern the analysis of the optical spectra for the choice of efficient excitation schemes and the suitable design of the experimental apparatus. Recent applications span from studies of short-lived isotopes at on-line mass separators to a wide variety of trace analysis applications for radioactive isotopes, which can range from measurements of solar neutrino flux to environmental assessment.On leave from Pacific Northwest Laboratory, Richland, USA     

Simultaneous solution of emission transfer and thermal conductivityequations in the problems of atmosphere and subsurface radiothermometry

Expressions are derived that relate the half-space temperature profile and the heat flux with the brightness temperature evolution. Remote sensing methods are proposed to measure the temperature and heat flux in the atmosphere and subsoil layer by radiometric measurements     

Protocol design and performance analysis for manufacturing messagespecification: A Petri net approach

The manufacturing message specification (MMS) is the ISO standard communication protocol specific to manufacturing. To analyze MMS design and performance, service unit automats are introduced to represent individual MMS services, while service connection Petri Nets (PNs) are constructed from these automats to describe MMS service connections and processes. This approach makes MMS protocol specification and analysis possible in terms of well-developed concepts and methods in PN theory. It leads to a distributed and hierarchical model of MMS software system by integrating service connection PNs. A generalized stochastic PN for MMS performance evaluation is obtained by incorporating service parameters and time factors into the model. A technique based on T-invariants is used to simplify the performance analysis     

Path tracking control of a manipulator considering torquesaturation

When the minimum-time trajectory of a manipulator along a geometrically prescribed path is planned taking into consideration the manipulator's dynamics and actuator's torque limits, at least one of the joints should be at the torque limit. The execution of such a trajectory by a conventional feedback control scheme results in torque saturation. Consequently, the tracking error cannot be suppressed and the manipulator may deviate from the desired path. In this paper, the author's propose a feedback control method for path tracking which takes the torque saturation into account. Based on the desired path, a coordinate system called path coordinates is defined. The path coordinates are composed of the component along the path and the components normal to the path. The equation of motion is described in terms of the path coordinates. Control of the components normal to the path is given priority in order to keep the motion of the manipulator on the path. Simulations of a two-degree-of-freedom manipulator show the effectiveness of this method     

Analysis and implementation of a real-time predictive currentcontroller for permanent-magnet synchronous servo drives

A real-time current controller for PWM inverter-fed permanent-magnet synchronous motor drives is presented and analyzed. The proposed current control scheme is based on predictive control with a parallel integral loop added to compensate for the inaccuracy of the motor model and for the variations of motor parameters and DC voltage source. The proposed current control scheme is analyzed and its performance is evaluated by computer simulation. An EPROM-based implementation is presented in which calculations and pulsewidth modulation are executed by lookup tables resulting in high-speed operation. The controller performance is evaluated using a prototype l kW PM synchronous servo drive. Experimental results are given and discussed     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load