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Numerical characterization and experimental verification of an in-plane MEMS-actuator with thin-film aluminum heater

In this paper, a novel concept of a thermo-mechanical MEMS actuator using aluminum thin-film heaters on a thermal oxide for electrical insulation is presented. The actuator is part of an universal tensile testing platform for thermo-mechanical material characterization of one dimensional materials on a micro- and nano-scopic scale under different environmental conditions, as varying temperatures, pressure, moisture or even vacuum and is realised in BDRIE technology. It is shown, that the actuator concept fulfills the requirements for the use in a tensile loading stage along with heterogeneously integrated nanofunctional elements, following a specimen centered approach in line with bottom-up self-assembly processes. Simulation and experiment agree very well in the thermal and mechanical domain and allow subsequent optimisation of the actuator performance.     

Wafer bonding using Cu–Sn intermetallic bonding layers

Wafer-level Cu–Sn intermetallic bonding is an interesting process for advanced applications in the area of MEMS and 3D interconnects. The existence of two intermetallic phases for Cu–Sn system makes the wafer bonding process challenging. The impact of process parameters on final bonding layer quality have been investigated for transient liquid phase wafer-level bonding based on the Cu–Sn system. Subjects of this investigation were bonding temperature profile, bonding time and contact pressure as well as the choice of metal deposition method and the ratio of deposited metal layer thicknesses. Typical failure modes in intermetallic compound growth for the mentioned process and design parameters have been identified and were subjected to qualitative and quantitative analysis. The possibilities to avoid abovementioned failures are indicated based on experimental results.     

A new variety of low-linolenic rapeseed oil; Characteristics and room-odor tests

Two Canadian rapeseed oils, “Westar” and “low-linolenic”, supplied by the Canola Council were studied and compared with a French rapeseed. The linolenic acid content of the low-linolenic variety is about 3%. This drop in the C18∶3 is completely compensated for by an increase in the C18∶2. Seventy-two percent of the triglycerides with at least one linolenic chain disappeared. A strong increase in the OOL and OLL was observed. The room-odor tests showed that the “low-linolenic” had a significantly higher odor score than the French rapeseed and the “Westar”, both of these being very similar. A fruity odor dominated in the “low-linolenic”, and the fishy painty odors were particularly reduced.     

Nature-Inspired Meta-Heuristics on Modern GPUs: State of the Art and Brief Survey of Selected Algorithms

Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly parallel implementation and execution of Nature and Bio-inspired Algorithms with excellent price-to-power ratio. In contrast to common multicore CPUs that contain up to tens of independent cores, the GPUs represent a massively parallel single-instruction multiple-data devices that can nowadays reach peak performance of hundreds and thousands of giga floating-point operations per second. Nature and Bio-inspired Algorithms implement parallel optimization strategies in which a single candidate solution, a group of candidate solutions (population), or multiple populations seek for optimal solution or set of solutions of given problem. Genetic algorithms (GA) constitute a family of traditional and very well-known nature-inspired populational meta-heuristic algorithms that have proved its usefulness on a plethora of tasks through the years. Differential evolution (DE) is another efficient populational meta-heuristic algorithm for real-parameter optimization. Particle swarm optimization (PSO) can be seen as nature-inspired multiagent method in which the interaction of simple independent agents yields intelligent collective behavior. Simulated annealing (SA) is global optimization algorithm which combines statistical mechanics and combinatorial optimization with inspiration in metallurgy. This survey provides a brief overview of the latest state-of-the-art research on the design, implementation, and applications of parallel GA, DE, PSO, and SA-based methods on the GPUs.     

Surface and subsurface products of the interaction of O2 with Ag under catalytic conditions

Polycrystalline Ag treated with O₂ at pressures up to 1 bar and at temperatures up to 920 K was examined by TDS. It was found that the peak commonly observed at 595±25 K and assigned to adsorbed atomic oxygen (O_a) is shifted to higher desorption temperatures with rising dosing temperatures. Since saturation of the uptake was not possible either, this peak was identified as dissolved atomic oxygen (O_d). The existence of a maximum for the O₂ uptake after exposure at 820 K was found. Hence, under conditions of formaldehyde synthesis ( 920 K) the ability of the catalyst to dissolve oxygen is near its maximum.     

Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.     

Structural characteristics of oxide nanosphere supported metal nanoparticles

Structural characterization by transmission electron microscopy of metal nanoparticle coatings on oxide nanospheres has been employed to point out the potential of such materials for use as porous support model catalysts. On silica and titania nanospheres of various origins surface-mediated metal deposition at mild temperature conditions has been utilized to fabricate Pt, Pd, Ag, and Au nanoparticle coatings on the oxide supports. Promising coating characteristics have been achieved for Ag and Au nanoparticles by direct reduction on terminating hydroxyl-rich St?ber silica. A high-resolution electron microscopy analysis directed to surface stress, lattice contraction and planar lattice defects of the latter particles revealed no strong metal-support interaction.     

Upgrading of gas oils: the HDS kinetics of dibenzothiophene and its derivatives in real gas oil

The hydrodesulphurization (HDS) of dibenzothiophene (DBT), 4-methyl dibenzothiophene (4 M-DBT), 4,6-dimethyl dibenzothiophene (4,6 DM-DBT) and 4,6-diethyl dibenzothiophene (4,6 DE-DBT) as real gas oil components on NiMo/Al₂O₃ catalyst was investigated. On the basis of the first order rate constants of HDS of the individual sulphur compounds reactivities of the investigated compounds decreased in the order DBT ≫ 4 M-DBT > 4,6 DE-DBT ≈ 4,6 DM-DBT. Apparent activation energies of HDS of above sulphur compounds increased from 80.0 to 120.5 kJ/mol.