Studies on influence of hydrogen and carbon monoxide concentration on reduction progression behavior of molybdenum oxide catalyst

Temperature programmed reduction (TPR) analysis was applied to investigate the chemical reduction progression behavior of molybdenum oxide (MoO₃) catalyst. The composition and morphology of the reduced phases were characterized by X-ray diffraction spectroscopy (XRD), X-ray photoelectron spectroscopy (XPS), and field emission scanning electron microscopy (FE-SEM). The reduction progression of MoO₃ catalyst was attained with different reductant types and concentration (10% H₂/N₂, 10% and 20% CO/N₂ (%, v/v)). Two different modes of reduction process were applied. The first approach of reduction involved non-isothermal mode reduction up to 700 °C, while the second approach of reduction involved the isothermal mode reduction for 60 min at 700 °C. Hydrogen temperature programmed reduction (H₂-TPR) results showed the reduction progression of three-stage reduction of MoO₃ (Mo⁶⁺ → Mo⁵⁺ → Mo⁴⁺ → Mo⁰) with Mo⁵⁺ and Mo⁴⁺. XRD analysis confirmed the formation of Mo₄O₁₁ phase as an intermediate phase followed by MoO₂ phase. After 60 min of isothermal reduction, peaks of metallic molybdenum (Mo) appeared. Whereas, FESEM analysis showed porous crater-like structure on the surface cracks of MoO₂ layer which led to the growth of Mo phase. Meanwhile, the reduction of MoO₃ catalyst in 10% carbon monoxide (CO) showed the formation of unstable intermediate phase of Mo₉O₂₆ at the early stage of reduction. Furthermore, by increasing 20% CO led to the carburization of MoO₂ phase, resulted in the formation of Mo₂C rather than the formation of metallic Mo, as confirmed by XPS analysis. Therefore, the presented study shows that hydrogen gave better reducibility due to smaller molecular size, which contributed to high diffusion rate and achieved deeper penetration into the MoO₃ catalyst compared to carbon monoxide reductant. Hence, the reduction of MoO₃ in carbon monoxide atmosphere promoted the formation of Mo₂C which was in agreement with the thermodynamic assessment.     

Kernel Spectral Matched Filter for Hyperspectral Imagery

In this paper a kernel-based nonlinear spectral matched filter is introduced for target detection in hyperspectral imagery, which is implemented by using the ideas in kernel-based learning theory. A spectral matched filter is defined in a feature space of high dimensionality, which is implicitly generated by a nonlinear mapping associated with a kernel function. A kernel version of the matched filter is derived by expressing the spectral matched filter in terms of the vector dot products form and replacing each dot product with a kernel function using the so called kernel trick property of the Mercer kernels. The proposed kernel spectral matched filter is equivalent to a nonlinear matched filter in the original input space, which is capable of generating nonlinear decision boundaries. The kernel version of the linear spectral matched filter is implemented and simulation results on hyperspectral imagery show that the kernel spectral matched filter outperforms the conventional linear matched filter.     

Evaporation and Evolution of Suspended Solution Droplets at Atmospheric and Reduced Pressures

Thermal history and solute precipitation behavior of suspended solution droplets of sodium chloride (NaCl), magnesium sulphate (MgSO₄), and zirconium hydroxychloride (ZrO(OH)Cl) evaporating at atmospheric and reduced pressures are studied. Experimental measurements on the variation of droplet diameter, solution concentration, and temperature during the evaporation period are presented and discussed. The results of solute precipitation behavior in solution droplets observed under an optical microscope are displayed and discussed. Results indicate that reducing the pressure (∼ 33 kPa) results in a change in the solution droplet evaporation rate, but the thermal histories of a particular solution droplet are similar at the atmospheric and reduced pressures. At atmospheric and reduced pressures used in this study, the d² law for solution droplets is valid at early stages of the evaporation and before the solute precipitation initiates. Drying of MgSO₄ and ZrO(OH)Cl solution droplets results in the formation of spherical particles, whereas drying of spherical NaCl solution droplets results in the formation of cubic particles.     

Dynamic Analysis of Truss‐Beam System

As the manned exploration of space continues, many complex structural components are being developed to construct the orbital platforms that will be used to house communication hardware, personnel, and manufacturing complexes. These components are extremely flexible and complex in their behavior. There is a need for a simple method for determining the dynamic characteristics of these space structures with a minimum of effort. A mathematical model of one of these structural elements, an articulating truss beam, has been developed to predict its dynamic response. Assumptions of the force interaction between the beam elements and the joints have been made for using this model. Algorithms are provided to determine the flexibility matrix of the truss beam for use in the equation of motion. The natural frequencies obtained from using this method are compared with those obtained by the finite element method. An experimental procedure is planned to validate the results from the theoretical method.     

A knowledge-based system for sensor selection

This paper presents a Knowledge-based system (KBS) developed to allow users, who may not be knowledgeable about sensors, to select sensors suitable for their specific needs. The KBS runs on a micro-computer. The selection criteria are user specified and are based on the desired measurement parameters. The system output includes all of the operational and dimensional parameters of the recommended sensor, price, and vendor information.     

Evaluation of simple dynamic models and controllers for hydraulic and nozzle pressure in injection molding

Simple pseudo-steady state relations between the hydraulic and nozzle pressures of an injection molding machine were presented and verified experimentally. A simulation study was performed to evaluate the performance of simple controllers using dynamic models developed for the hydraulic and nozzle pressures. The controllers chosen were the discrete proportional, proportional-integral (PI), and proportional-integral-derivative (PID) types, tuned according to the ITAE criterion. The control of hydraulic pressure simulation showed that the PI controller had the best overall performance, whereas the result of nozzle pressure control loop simulation showed that the PID controller performance was better than that of the PI controller. All the controllers, in both loops, gave responses that were about an order of magnitude more rapid than the open loop response.