Modification of SiO2 nanowires with metallic nanocrystals from supercritical CO2

Through hydrogen reduction of metal precursors in supercritical CO2, Cu, and Pd, nanocrystals were deposited onto SiO2 nanowires to form different types of nanostructured materials, including nanocrystal-nanowire, spherical aggregation-nanowire, shell-nanowire composites, and "mesoporous" metals supported by the framework of nanowires. This supercritical fluid deposition technique is an attractive approach for modifying nanowires because of its generality and simplicity; the modified nanowires could be useful as catalysts and for further fabrication of multifunctional composites.     

Performance optimization of spectroscopic process analyzers

To increase the power and the robustness of spectroscopic process analyzers, methods are needed that suppress the spectral variation that is not related to the property of interest in the process stream. An approach for the selection of a suitable method is presented. The approach uses the net analyte signal (NAS) to analyze the situation and to select methods to suppress the nonrelevant spectral variation. The empirically determined signal-to-noise of the NAS is used as a figure of merit. The advantages of the approach are (i). that the error of the reference method does not affect method selection and (ii). that only a few spectral measurements are needed. A diagnostic plot is proposed that guides the user in the evaluation of the particular suppression method. As an example, NIR spectroscopic monitoring of a mol-sieve separation process is used.     

Effects of pore flow on the separation efficiency in capillary electrochromatography with porous particles

The effect of pore flow on the separation efficiency of capillary electrochromatography (CEC) has been studied using columns packed with particles with different pore sizes. A previously developed model was used to predict the (relative) pore flow velocity in these columns under various experimental conditions. Equations are derived describing the effect of pore flow on peak broadening in CEC. The theory has been compared with practice in the reversed-phase CEC separation of various polyaromatic hydrocarbons. It is shown, by theory and experimentally, that the mass-transfer resistance contribution to peak dispersion can be effectively eliminated when using porous particles with a high (> or =50 nm) average pore diameter. Moreover, at high pore-to-interstitial flow ratios the flow inhomogeneity contribution (the A term in the plate height equation) is also shown to decrease. Under optimal conditions, a reduced plate height of 0.3 for the nonretained compound could be obtained. It is argued that fully perfusive porous particles can be a more efficient separation medium in CEC than nonporous particles.     

Agent-based simulation of electricity markets: a survey of tools

Agent-based simulation has been a popular technique in modeling and analyzing electricity markets in recent years. The main objective of this paper is to study existing agent-based simulation packages for electricity markets. We first provide an overview of electricity markets and briefly introduce the agent-based simulation technique. We then investigate several general-purpose agent-based simulation tools. Next, we review four popular agent-based simulation packages developed for electricity markets and several agent-based simulation models reported in the literature. We compare all the reviewed packages and models and identify their common features and design issues. Based on the study, we describe an agent-based simulation framework for electricity markets to facilitate the development of future models for electricity markets.     

Reconfigurable Microwave Photonic Filter Using Multiwavelength Erbium-Doped Fiber Laser

A microwave photonic filter using a simple and novel multiwavelength erbium-doped fiber laser (EDFL) is proposed. The filter was experimentally demonstrated featuring tunability and reconfigurability by adjustment of the output from the EDFL. The experimental results show excellent agreement with the numerical simulations.     

New results in robust actuator fault reconstruction for linear uncertain systems using sliding mode observers

This paper presents a robust actuator fault reconstruction scheme for linear uncertain systems using sliding mode observers. In existing work, fault reconstruction via sliding mode observers is limited to either linear certain systems subject to unknown inputs, relative degree one systems or a specific class of relative degree two systems. This paper presents a new method that is applicable to a wider class of systems with relative degree higher than one, and can also be used for systems with more unknown inputs than outputs. The method uses two sliding mode observers in cascade. Signals from the first observer are processed and used to drive the second observer. Overall, this results in actuator fault reconstruction being feasible for a wider class of systems than using existing methods. A simulation example verifies the claims made in this paper. Copyright © 2007 John Wiley & Sons, Ltd.     

Geometry dependence of microstructure and microhardness for selective electron beam-melted Ti–6Al–4V parts

In an additive-manufactured metallic part, distinct and different microstructure and mechanical properties may exist in different areas due to differences in shape and location. Two parts, one with straight-finned structure and the other with curve-finned structure, were fabricated by the selective electron beam melting method using pre-alloyed Ti–6Al–4V ELI powder. Microstructural characterisation of these two parts that have varying fin thickness and shape was carried out to investigate the synthetical influence of 2D planar build geometry and in-fill hatching strategy on selective electron beam melting. It was found that the β interspacing is larger in the curve-finned structure, leading to a lower microhardness as compared to the straight-finned structure. It suggests a slower cooling rate in the curve-finned structure due to the differences in build geometry and in-fill hatching strategy.     

High Sensitivity,Wearable, Piezoresistive Pressure Sensors Based on Irregular Microhump Structures and Its Applications in Body Motion Sensing

A pressure sensor based on irregular microhump patterns has been proposed and developed. The devices show high sensitivity and broad operating pressure regime while comparing with regular micropattern devices. Finite element analysis (FEA) is utilized to confirm the sensing mechanism and predict the performance of the pressure sensor based on the microhump structures. Silicon carbide sandpaper is employed as the mold to develop polydimethylsiloxane (PDMS) microhump patterns with various sizes. The active layer of the piezoresistive pressure sensor is developed by spin coating PEDOT:PSS on top of the patterned PDMS. The devices show an averaged sensitivity as high as 851 kPa^?1, broad operating pressure range (20 kPa), low operating power (100 nW), and fast response speed (6.7 kHz). Owing to their flexible properties, the devices are applied to human body motion sensing and radial artery pulse. These flexible high sensitivity devices show great potential in the next generation of smart sensors for robotics, real‐time health monitoring, and biomedical applications.     

Sustainable multi-period electricity planning for Iskandar Malaysia

This paper presents the current situation and projected planning of the electricity generation sector for Iskandar Malaysia by implementing a model to optimise the cost, utilise the usage of available renewable energy sources, and achieve carbon dioxide reduction targets. This Mixed Integer Linear Programming model was developed with the main objective of minimising the total cost of electricity generation, taking into consideration energy demand, reserve margin, electricity generation, peak and base generation, resource availability, and CO₂ emission. Data for the year 2013 were forecasted until 2025 to illustrate the analysis for this study, and are represented via four scenarios. This optimal model is capable of balancing types of fuel and switching coal plants to natural gas power plants. It also enhances the use of renewable energy (RE) to meet CO₂ emission targets. The model is further integrated with several other considerations related to energy systems, such as suitability of power plants as peak or base plants, RE resource availability, intermittency of solar power, losses during transmission, fuel selection for biomass, decision to retrofit existing coal power plant to NG power plant, and construction lead time of power plants. The results for this study determined that the optimal scenario is Scenario 3 (CS3). This research proves that Iskandar Malaysia can reduce CO₂ emission by 2025 via utilisation of RE. This model is generic and can be applied to any case study, which would be useful for assisting government policy-making.     

Recurrent neural network approach for cyclic job shop scheduling problem

While cyclic scheduling is involved in numerous real-world applications, solving the derived problem is still of exponential complexity. This paper focuses specifically on modelling the manufacturing application as a cyclic job shop problem and we have developed an efficient neural network approach to minimise the cycle time of a schedule. Our approach introduces an interesting model for a manufacturing production, and it is also very efficient, adaptive and flexible enough to work with other techniques. Experimental results validated the approach and confirmed our hypotheses about the system model and the efficiency of neural networks for such a class of problems.