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The semiconductor field-effect platform represents a powerful tool for detecting the adsorption and binding of charged macromolecules with direct electrical readout. In this work, a capacitive electrolyte–insulator–semiconductor (EIS) field-effect sensor consisting of an Al-p-Si-SiO2 structure has been applied for real-time in situ electrical monitoring of the layer-by-layer formation of polyelectrolyte (PE) multilayers (PEM). The PEMs were deposited directly onto the SiO2 surface without any precursor layer or drying procedures. Anionic poly(sodium 4-styrene sulfonate) and cationic weak polyelectrolyte poly(allylamine hydrochloride) have been chosen as a model system. The effect of the ionic strength of the solution, polyelectrolyte concentration, number and polarity of the PE layers on the characteristics of the PEM-modified EIS sensors have been studied by means of capacitance–voltage and constant-capacitance methods. In addition, the thickness, surface morphology, roughness and wettabilityof the PE mono- and multilayers have been characterised by ellipsometry, atomic force microscopy and water contact-angle methods, respectively. To explain potential oscillations on the gate surface and signal behaviour of the capacitive field-effect EIS sensor modified with a PEM, a simplified electrostatic model that takes into account the reduced electrostatic screening of PE charges by mobile ions within the PEM has been proposed and discussed.
In the Collaborative Research Center SFB 401 at RWTH Aachen University, the numerical aeroelastic method SOFIA for direct numerical aeroelastic simulation is being progressively developed. Numerical results obtained by applying SOFIA were compared with measured data of static and dynamic aeroelastic wind tunnel tests for an elastic swept wing in subsonic flow.
In this part of the MEGADESIGN project, aeroelastic effects are introduced into the aerodynamic analysis of aircrafts by coupling DLR’s flow solvers TAU and FLOWer to a Timoshenko-beam solver. The emerging aeroelastic solvers and a method for the automatic identification of Timoshenko-beam models for wing-box structures were integrated into a simulation environment enabling the combined optimisation of aerodynamic wing shape and structure.
Temperature-dependent ranges of coexistence in a model of a two-prey-one-predator microbial food web
(2012)
The objective of our study was to analyze the effects of temperature on the population dynamics of a three-species food web consisting of two prey bacteria (Pedobacter sp. and Acinetobacter johnsonii) and a protozoan predator (Tetrahymena pyriformis) as model organisms. We assessed the effects of temperature on the growth rates of all three species with the objective of developing a model with four differential equations based on the experimental data. The following hypotheses were tested at a theoretical level: Firstly, temperature changes can affect the dynamic behavior of a system by temperature-dependent parameters and interactions and secondly, food web response to temperature cannot be derived from the single species temperature response. The main outcome of the study is that temperature changes affect the parameter range where coexistence is possible within all three species. This has significant consequences on our ideas regarding the evaluation of effects of global warming.
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.