Intrinsic CFRP-metal-hybrids with rubber interface for the improvement of the damping behaviour

This paper presents an integrated passive damping approach in hybrid metal-CFRP parts for structural applications. In this concept a viscoelastic material is embedded in the joint zone of the hybrid component. To examine the connection strength single-lap-joint specimens were produced and tested and the influence of the used material combinations, different surface structures, and different process parameters i.e. the moment of cross-linking were evaluated. Afterwards, the metal-CFRP hybrids were tested in quasi-static tests to assess their connection strength and failure behaviour. Dynamic cyclic tensile tests with step-wise increased loading conditions were performed to determine the specimens damping behaviour and to estimate their fatigue performance. Finally, these results are compared to a state of the art metal-CFRP hybrid with rivets connecting both materials.     

Effect of complexation of oxidised corn starch with mineral elements on physicochemical properties

The objective of this study was to determine the effect of complexation of oxidised starch with mineral elements on its physicochemical properties. Corn starch was oxidised with sodium hypochlorite and, afterwards, modified with ions of potassium, magnesium and iron. Thus, native and modified starches were analysed for: contents of mineral elements, colour parameters (L*a*b*), water binding capacity and solubility in water at temperature of 60 and 80 °C. Thermodynamic characteristics of gelatinisation by DSC, molecular weight distribution by GPC, intrinsic viscosity and pasting properties by RVA were studied. The efficiency of incorporation of metal ions into oxidised corn starch was about 30%, 20% and 20% for potassium, magnesium and iron ions, respectively. The complexation with potassium ions caused the greatest changes in the molecular weight distribution and the intrinsic viscosity of starches and viscosity of starch pastes. Only modification of starch with iron ions affected the colour parameters of the starch. Incorporation of metal ions into starch resulted also in changes in its water binding capacity and solubility in water.     

Matrix Transformation in Boron Containing High-Temperature Co–Re–Cr Alloys

An addition of boron largely increases the ductility in polycrystalline high-temperature Co–Re alloys. Therefore, the effect of boron on the alloy structural characteristics is of high importance for the stability of the matrix at operational temperatures. Volume fractions of ε (hexagonal close-packed—hcp), γ (face-centered cubic—fcc) and σ (Cr₂Re₃ type) phases were measured at ambient and high temperatures (up to 1500 °C) for a boron-containing Co–17Re–23Cr alloy using neutron diffraction. The matrix phase undergoes an allotropic transformation from ε to γ structure at high temperatures, similar to pure cobalt and to the previously investigated, more complex Co–17Re–23Cr–1.2Ta–2.6C alloy. It was determined in this study that the transformation temperature depends on the boron content (0–1000 wt. ppm). Nevertheless, the transformation temperature did not change monotonically with the increase in the boron content but reached a minimum at approximately 200 ppm of boron. A probable reason is the interplay between the amount of boron in the matrix and the amount of σ phase, which binds hcp-stabilizing elements (Cr and Re). Moreover, borides were identified in alloys with high boron content.     

Purification of the cardiac sarcoplasmic reticulum membrane protein phospholamban from recombinant Escherichia coli

Phospholamban (PLN) was expressed in Escherichia coli as a protein fusion with glutathione S-transferase (GST). GST-PLN was mostly present in the insoluble protein fraction and accounted for approximately 50% of total insoluble protein. Attempts to suppress inclusion body formation or to use GST as an affinity-purification tag failed. A successful purification method is based on preparative SDS/PAGE and electrodialysis. From 1 g cells we typically purified 13.5 mg fusion protein with a PLN content of 2.8 mg. We genetically inserted an enterokinase (EK) protease site just in front of the PLN sequence and demonstrated the proteolytical liberation of PLN from the carrier protein. The approach described represents a substantial advancement in PLN expression and purification.     

An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.     

Stream Classification System Based on Susceptibility to Algal Growth in Response to Nutrients

We developed a stream classification system that is based on stream’s susceptibility to algal growth using a two-step approach. The model portrays algal biomass as a result of stream’s response to nutrient concentrations and the response is governed by various stream factors. In the first step, a nutrient-chlorophyll a relationship was developed to characterize nutrient’s effects on algal biomass. Residuals of the relationship were attributed to stream’s susceptibility to algal growth in response to nutrients and referred to as “observed” susceptibility. In the second step, conditions of other contributing factors were used to explain the variation in the residuals and the developed relationship was used to generate “predicted” susceptibility. Existing data compiled from various monitoring projects of Illinois streams and rivers were used to illustrate the approach. Streams were classified into three (high, medium, and low) categories based on their observed and predicted susceptibility values, respectively. With the available data, the model showed a 40-50% success rate for classifying the streams based on three observed and predicted susceptibility categories. Model entropy also was calculated for selecting the best model. The results show the important role of both nutrients and other contributing factors in explaining the variation of algal biomass. The study also suggests ways to fine tune the model and improve its accuracy, which would make the presented model a more viable tool for stream classification for establishing nutrient criteria to prevent surface streams from eutrophication.