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Numerical solution of the heat equation with non-linear, time derivative-dependent source term
(2010)
The mathematical modeling of heat conduction with adsorption effects in coated metal structures yields the heat equation with piecewise smooth coefficients and a new kind of source term. This term is special, because it is non-linear and furthermore depends on a time derivative. In our approach we reformulated this as a new problem for the usual heat equation, without source term but with a new non-linear coefficient. We gave an existence and uniqueness proof for the weak solution of the reformulated problem. To obtain a numerical solution, we developed a semi-implicit and a fully implicit finite volume method. We compared these two methods theoretically as well as numerically. Finally, as practical application, we simulated the heat conduction in coated aluminum fibers with adsorption in the zeolite coating. Copyright © 2010 John Wiley & Sons, Ltd.
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.