Key features of flexure hinges used as rotational joints

This article is supposed to serve as a guide for the design of flexure hinges that act as rotational joints. Firstly, flexure hinges with concentrated and distributed compliance are reviewed. They can be modeled by linear beam theories or by the theory of Elastica, respectively. Secondly, the transition between these limit cases is investigated by finite element methods (FEM). A planar symmetric flexure hinge with a circular notch serves as an exemplary geometry. By extending the notch the compliance is distributed. The deflection curves and the kinetics of desired and parasitic motions are chosen as key features to be studied. The corresponding results are compressed into a pseudo-rigid-body model (PRBM) approximation for a range of geometries. It turned out that the concentrated compliance matches best with an ideal rotational joint, but even for small displacements large stresses occur so that its range of operation is small. Distributing the compliance increases the range of operation, however stiffness within the task space decreases dramatically so that the design of a flexure hinge becomes a tradeoff between the two concurring goals large stiffness and large range of operation.     

Microwave-hydrothermal synthesis and characterization of nanostructured copper substituted ZnM2O4 (M = Al, Ga) spinels as precursors for thermally stable Cu catalysts

Nanostructured Cu(x)Zn(1-x)Al(2)O(4) with a Cu:Zn ratio of ?:? has been prepared by a microwave-assisted hydrothermal synthesis at 150 °C and used as a precursor for Cu/ZnO/Al(2)O(3)-based catalysts. The spinel nanoparticles exhibit an average size of approximately 5 nm and a high specific surface area (above 250 m(2) g(-1)). Cu nanoparticles of an average size of 3.3 nm can be formed by reduction of the spinel precursor in hydrogen and the accessible metallic Cu(0) surface area of the reduced catalyst was 8 m(2) g(-1). The catalytic performance of the material in CO(2) hydrogenation and methanol steam reforming was compared with conventionally prepared Cu/ZnO/Al(2)O(3) reference catalysts. The observed lower performance of the spinel-based samples is attributed to a lack of synergetic interaction of the Cu nanoparticles with ZnO due to the incorporation of Zn(2+) in the stable spinel lattice. Despite its lower performance, however, the nanostructured nature of the spinel catalyst was stable after thermal treatment up to 500 °C in contrast to other Cu-based catalysts. Furthermore, a large fraction of the re-oxidized copper migrates back into the spinel upon calcination of the reduced catalyst, thereby enabling a regeneration of sintered catalysts after prolonged usage at high temperatures. Similarly prepared samples with Ga instead of Al exhibit a more crystalline catalyst with a spinel particle size around 20 nm. The slightly decreased Cu(0) surface area of 3.2 m(2) g(-1) due to less copper incorporation is not a significant drawback for the methanol steam reforming.     

Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling

Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessment of the parameters of water models. This paper compares a number of these techniques: the Generalized Likelihood Uncertainty Estimation (GLUE), the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), an approach based on a multi-objective auto-calibration (a multialgorithm, genetically adaptive multi-objective method, AMALGAM) and a Bayesian approach based on a simplified Markov Chain Monte Carlo method (implemented in the software MICA). To allow a meaningful comparison among the different uncertainty techniques, common criteria have been set for the likelihood formulation, defining the number of simulations, and the measure of uncertainty bounds. Moreover, all the uncertainty techniques were implemented for the same case study, in which the same stormwater quantity and quality model was used alongside the same dataset. The comparison results for a well-posed rainfall/runoff model showed that the four methods provide similar probability distributions of model parameters, and model prediction intervals. For ill-posed water quality model the differences between the results were much wider; and the paper provides the specific advantages and disadvantages of each method. In relation to computational efficiency (i.e. number of iterations required to generate the probability distribution of parameters), it was found that SCEM-UA and AMALGAM produce results quicker than GLUE in terms of required number of simulations. However, GLUE requires the lowest modelling skills and is easy to implement. All non-Bayesian methods have problems with the way they accept behavioural parameter sets, e.g. GLUE, SCEM-UA and AMALGAM have subjective acceptance thresholds, while MICA has usually problem with its hypothesis on normality of residuals. It is concluded that modellers should select the method which is most suitable for the system they are modelling (e.g. complexity of the model’s structure including the number of parameters), their skill/knowledge level, the available information, and the purpose of their study.     

SiGe epitaxy on a 300 mm batch furnace

This work reports the feasibility of silicon and silicon germanium epitaxy using an ASM A412(TMa) LPCVD all quartz, hot wall, vertical batch furnace reactor using 100 wafer product loads. The very same furnace can be used for 25 wafer and 200 wafer load size, without any hardware changes, dependant on production needs. Following this approach a significant cost reduction for epitaxy in 300 mm high volume manufacturing is possible and enables new applications. The native oxide of the substrate was removed by wet chemical cleaning with time coupling of less than 1 h and subsequent in-situ low pressure hydrogen anneal prior to Si or SiGe deposition. The epitaxial layers were grown using silane and germane. The Si and SiGe layers have been characterized with ToFSIMS, XRD, Raman, AFM and TEM confirming excellent crystalline quality, layer thickness and within wafer SiGe stoichiometry uniformity.