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Although Selective Laser Melting (SLM) process is an innovative manufacturing method, there are challenges such as inferior mechanical properties of fabricated objects. Regarding this, buckling deformation which is caused by thermal stress is one of the undesired mechanical properties which must be alleviated. As buckling deformation is more observable in hard to process materials, silver is selected to be studied theoretically and experimentally for this paper. Different scanning strategies are utilized and a Finite Element Method (FEM) is applied to calculate the temperature gradient in order to determine its effect on the buckling deformation of the objects from experiments.
Often, detailed simulations of heat conduction in complicated, porous media have large runtimes. Then homogenization is a powerful tool to speed up the calculations by preserving accurate solutions at the same time. Unfortunately real structures are generally non-periodic, which requires unpractical, complicated homogenization techniques. We demonstrate in this paper, that the application of simple, periodic techniques to realistic media, that are just close to periodic, gives accurate, approximative solutions. In order to obtain effective parameters for the homogenized heat equation, we have to solve a so called “cell problem”. In contrast to periodic structures it is not trivial to determine a suitable unit cell, which represents a non-periodic media. To overcome this problem, we give a rule of thumb on how to choose a good cell. Finally we demonstrate the efficiency of our method for virtually generated foams as well as real foams and compare these results to periodic structures.
Field-effect capacitive electrolyte-insulator-semiconductor (EIS) sensors functionalised with citrate-capped gold nanoparticles (AuNP) have been used for the electrostatic detection of macromolecules by their intrinsic molecular charge. The EIS sensor detects the charge changes in the AuNP/macromolecule hybrids induced by the adsorption or binding events. A feasibility of the proposed detection scheme has been exemplary demonstrated by realising EIS sensors for the detection of poly-D-lysine molecules.
The chemical imaging sensor is a chemical sensor which is capable of visualizing the spatial distribution of chemical species in sample solution. In this study, a novel measurement system based on the chemical imaging sensor was developed to observe the inside of a Y-shaped microfluidic channel while injecting two sample solutions from two branches. From the collected chemical images, it was clearly observed that the injected solutions formed laminar flows in the microfluidic channel. In addition, ion diffusion across the laminar flows was observed. This label-free method can acquire quantitative data of ion distribution and diffusion in microfluidic devices, which can be used to determine the diffusion coefficients, and therefore, the molecular weights of chemical species in the sample solution.
This work describes the novel combination of the light-addressable electrode (LAE) and the light-addressable potentiometric sensor (LAPS) into a microsystem set-up. Both the LAE as well as the LAPS shares the principle of addressing the active spot by means of a light beam. This enables both systems to manipulate resp. to detect an analyte with a high spatial resolution. Hence, combining both principles into a single set-up enables the active stimulation e.g., by means of electrolysis and a simultaneous observation e.g., the response of an entrapped biological cell by detection of extracellular pH changes. The work will describe the principles of both technologies and the necessary steps to integrate them into a single set-up. Furthermore, examples of application and operation of such systems will be presented.
A variety of transition metals, e.g., copper, zinc, cadmium, lead, etc. are widely used in industry as components for wires, coatings, alloys, batteries, paints and so on. The inevitable presence of transition metals in industrial processes implies the ambition of developing a proper analytical technique for their adequate monitoring. Most of these elements, especially lead and cadmium, are acutely toxic for biological organisms. Quantitative determination of these metals at low activity levels in different environmental and industrial samples is therefore a vital task. A promising approach to achieve an at-side or on-line monitoring on a miniaturized and cost efficient way is the combination of a common potentiometric sensor array with heavy metal-sensitive thin-film materials, like chalcogenide glasses and polymeric materials, respectively.
The construction of a statistical test is investigated which is based only on “reliability” and “precision” as quality criteria. The reliability of a statistical test is quantifiedin a straightforward way by the probability that the decision of the test is correct. However, the quantification of the precision of a statistical test is not at all evident. Thereforethe paper presents and discusses several approaches. Moreover the distinction of “nullhypothesis” and “alternative hypothesis” is not necessary any longer.
Real-time and reliable monitoring of the biogas process is crucial for a stable and efficient operation of biogas production in order to avoid digester breakdowns. The concentration of dissolved hydrogen (H₂) represents one of the key parameters for biogas process control. In this work, a one-chip integrated combined amperometric/field-effect sensor for monitoring the dissolved H₂ concentration has been developed for biogas applications. The combination of two different transducer principles might allow a more accurate and reliable measurement of dissolved H₂ as an early warning indicator of digester failures. The feasibility of the approach has been demonstrated by simultaneous amperometric/field-effect measurements of dissolved H₂ concentrations in electrolyte solutions. Both, the amperometric and the field-effect transducer show a linear response behaviour in the H₂ concentration range from 0.1 to 3% (v/v) with a slope of 198.4 ± 13.7 nA/% (v/v) and 14.9 ± 0.5 mV/% (v/v), respectively.
The Volatility Framework is a collection of tools for the analysis of computer RAM. The framework offers a multitude of analysis options and is used by many investigators worldwide. Volatility currently comes with a command line interface only, which might be a hinderer for some investigators to use the tool. In this paper we present a GUI and extensions for the Volatility Framework, which on the one hand simplify the usage of the tool and on the other hand offer additional functionality like storage of results in a database, shortcuts for long Volatility Framework command sequences, and entirely new commands based on correlation of data stored in the database.