A selective conductive polymer-based sensor for volatile halogenated organic compounds (VHOC)

A novel poly(p-xylylene), PPX, derivative bearing alkoxyphenyl side groups was electrochemically synthesized in 87% yield. The polymer, poly(4′-hexyloxy-2,5-biphenyleneethylene) (PHBPE), presented a fraction (92%) soluble in common organic solvents. It showed to be thermally resistant up to 185 °C. UV–vis analysis revealed an E_gap of 3.5 eV. Gas sensors made from thin films of 10-camphorsulfonic acid-doped PHBPE deposited on interdigitated electrodes exhibited significant changes in electrical conductance upon exposure to five VHOCs: 1,2-dichloroethane, bromochloromethane, trichloromethane, dichloromethane and tetrachloromethane. The conductance decreased after exposure to tetrachloromethane and increased after exposure to all the other VHOCs. Three-dimensional plots of relative response versus time of half response versus time of half recovery showed good discrimination between the five VHOCs tested.     

Magnetic order and evolution of the electronic state aroundx=0.12 in La2?xBaxCuO4 and La2?xSrxCuO4

Muon spin rotation ( ⁺SR) measurement provides clear evidence of the antiferromagnetic order of Cu moments below 35 K for La_2–x Ba _x CuO₄ and below 15 K for La_2–x Sr _x CuO₄ in the narrow range ofx where the high-T _c superconductivity (SC) is suppressed remarkably. The results suggest that the change of the electronic state coupled with the lattice instability is relevant to the local suppression of SC and freezing of spin fluctuations of the Cu moment.     

Sensory evaluation of beef patties and sausages containing lipids with various component fatty acids

Sensory scores of beef patties and emulsion-type sausages containing varying levels of lipids with various component fatty acids were investigated. Sensory scores of beef patties containing solid fat were relatively constant at every fat level examined. However, scores of beef patties containing liquid oil decreased with increasing level of added oil. In the case of sausages, on the other hand, sensory evaluation scores markedly decreased with increasing the level of solid fat, while no significant change was observed in panel scores when liquid oil was mixed into sausages. Even 10% level of added lipids satisfactorily gave preferable acceptability to beef patties and sausages.     

A combined approach for modeling particle behavior in granular impact damper using discrete element method and cellular automata

A particle impact damper is a vibration absorber type that consists of a container attached to a primary vibrating structure. It also contains many particles that are constrained to move inside the container, whereby the damping effect can be obtained by collision between particles and the container. The discrete element method (DEM) has been developed for modeling granular systems, where the kinematics of each particle are calculated numerically using the equations of motion. However, the computational time is significant since the algorithm checks for particle contacts for all possible particle combinations. The use of a cellular automata (CA) modeling technique may provide increased computational efficiency due to the local updating of variables, and the discrete treatment of time and space. In this study, we propose a new approach combining DEM with CA for modeling a granular damper under a forced excitation. We use DEM to describe the particle motion according to the equations of motion, while CA is introduced for the particle contact checks in discrete space. We also investigate the effect of simplification in the contact force model, which allows the unit time step of numerical integration to become larger than that used in the strict model. It is shown that the suggested particle contact scanning method and the force approximation model contribute to the reduction of the computational time, and neither degenerates the calculation accuracy nor causes the numerical instability.     

Thermodynamic properties and phase equilibria for Pt-Rh alloys

The activity of rhodium in solid Pt-Rh alloys is measured in the temperature range from 900 to 1300 K using the solid-state cell

Phonon anomalies in YNi2 11B2C

Recently we have discovered a new peak with phonon character which appears only below T_c in an intermetallic superconductor, YNi₂ ¹¹B₂C (Tc14-2K) by neutron inelastic scattering measurements. The peak intensity of the new peak shows the order-parameter-like temperature dependence of the superconductivity. The new peak grows by absorbing the spectral weight from the above-lying soft phonon mode. In the present study we investigate the magnetic field dependence of the new peak. With increasing magnetic field, the new peak is gradually suppressed and disappears by H=H_c2 (4.7T at T=5.5K). Beyond H_c2, the profile of the scattering function recovers that of the non-superconducting state above T_c These results strongly indicate that this new peak is undoubtedly associated with the superconducting state in YNi₂ ¹¹B₂C.     

Characteristics of sol-gel derived PZT thin films with lead oxide cover layers and lead titanate interlayers

The sol-gel derived PbZr_0.53Ti_0.47O₃ (PZT) films were fabricated on the bare Pt/Ti/SiO₂/Si substrates or the same substrates coated by the PbTiO₃ (PT) interlayers. The post-deposition annealing temperature and time were optimized when the PbO cover layers and PbO vapour-containing atmosphere were compared with each other and adopted as the method to diminish the lead-loss problem during the high-temperature post-deposition annealing. The X-ray diffraction patterns, microstructures, and electrical properties such as relative permittivity, _r, remanent polarization, P _r, and coercive electrical field, E _c, were investigated in relation to the annealing conditions. The PZT films deposited on the bare Pt/Ti/SiO₂/Si substrates under the PbO vapour-containing atmosphere showed better electrical properties. This indicates that the PbO vapour-containing atmosphere may be the better method of lead-loss-prevention to process the lead-containing films rather than the PbO cover layer method. The electrical characteristics of the PZT films, _r=1150, a dissipation factor of 0.039, P _r=26 C cm^–2, and E _c=40.5 kV cm^–1 were measured at 1 kHz. When PZT films were deposited on substrates coated by the PT layers, PZT-PT films with single perovskite phase were derived by post-deposition annealing at 500 °C for 1 h. However, the relative electrical properties are very poor, i.e. E _r=160, P _r=2.0 C cm^–2 and E _c=75 kVcm^–1. The optimum combination for preparing PZT-PT films is a 40 nm PbTiO₃ interlayer and annealing conditions of 6 h at 550 °C in a PbO vapour-containing atmosphere; the derived films exhibit electrical properties of E _r=885, P _r=21.5 C cm^–2 and E _c=64 kV cm^–1. The combination of inserting a PT interlayer and annealing in a PbO vapour-containing atmosphere can prevent the formation of electrical short paths. In this case, nearly pin-hole-free PZT films can be grown on the PT (interlayer) /Pt/Ti/SiO₂/Si substrates. It is believed that it is possible to prepare the PZT films with nano-scale uniformity, reproducible quality, which may be worth considering for commercial applications.     

Identification of a golf swing robot using soft computing approach

Golf swing robots have been recently developed in an attempt to simulate the ultra high-speed swing motions of golfers. Accurate identification of a golf swing robot is an important and challenging research topic, which has been regarded as a fundamental basis in the motion analysis and control of the robots. But there have been few studies conducted on the golf swing robot identification, and comparative analyses using different kinds of soft computing methodologies have not been found in the literature. This paper investigates the identification of a golf swing robot based on four kinds of soft computing methods, including feedforward neural networks (FFNN), dynamic recurrent neural networks (DRNN), fuzzy neural networks (FNN) and dynamic recurrent fuzzy neural networks (DRFNN). The performance comparison is evaluated based on three sets of swing trajectory data with different boundary conditions. The sensitivity of the results to the changes in system structure and learning rate is also investigated. The results suggest that both FNN and DRFNN can be used as a soft computing method to identify a golf robot more accurately than FFNN and DRNN, which can be used in the motion control of the robot.     

Trajectory planning for a manipulator with nonlinear Coulomb friction using a dynamically incremental genetic algorithm

Global warming and environmental destruction are caused in part by the mass consumption of energy by industries that use robotic manipulators. Hence, there is a need to minimize the energy used for manipulator control systems. It is relatively easy to analytically obtain an optimal solution for a linear system. However, a multi-link manipulator is governed by a nonlinear dynamical equation that is difficult to solve as a two-point boundary value problem. Here, the manipulator angles are approximated by Taylor and Fourier series, whose coefficients are sought by a genetic algorithm (GA) to optimize the objective function subject to the boundary conditions. A search method is proposed for planning the trajectory of a manipulator with nonlinear friction and geometrical constraints.