Zeitschriftenaufsätze

This paper elucidates the feasibility of magnetic drug targeting to the eye by using magnetic nanoparticles (MNPs) to which pharmaceutical drugs can be linked. Numerical simulations revealed that a magnetic field gradient of 20 T m^-1 seems to be promising for dragging magnetic multicore nanoparticles of about 50 nm into the eye. Thus, a targeting magnet system made of superconducting magnets with a magnetic field gradient at the eye of about 20 T m^-1 was simulated. For the proof-of-concept tissue experiments presented here the required magnetic field gradient of 20 T m^-1 was realized by a permanent magnet array. MNPs with an optimized multicore structure were selected for this application by evaluating their stability against agglomeration of MNPs with different coatings in water for injections, physiological sodium chloride solution and biological media such as artificial tear fluid. From these investigations, starch turned out to be the most promising coating material because of its stability in saline fluids due to its steric stabilization mechanism. To evaluate the passage of MNPs through the sclera and cornea of the eye tissues of domestic pigs (Sus scrofa domesticus), a three-dimensionally printed setup consisting of two chambers (reservoir and target chamber) separated by the eye tissue was developed. With the permanent magnet array emulating the magnetic field gradient of the superconducting setup, experiments on magnetically driven transport of the MNPs from the reservoir chamber into the target chamber via the tissue were performed. The resulting concentration of MNPs in the target chamber was determined by means of quantitative magnetic particle spectroscopy. It was found that none of the tested particles passed the cornea, but starch-coated particles could pass the sclera at a rate of about 5 ng mm^-2 within 24 h. These results open the door for future magnetic drug targeting to the eye.

In this work we present SiOx films deposited in cost-effective laboratory scale three-dimensional printed atmospheric pressure chemical vapor deposition setup. As SiOx films are deposited at room temperature without complex vacuum systems, they can be a good candidate for the use in commercial c-Si solar cell production lines. The quality of the deposited films was investigated as to their integrity, conformity with various surfaces, and post-treatment resilience such as stability against etchants and annealing. Several applications of the SiOx film prepared with the atmospheric pressure chemical vapor deposition (APCVD) were discussed. In one application, the APCVD SiOx was utilized to effectively promote single-side texturing of Float Zone and Czochralski Si wafers by coating only one side with SiOx and subsequently annealing prior to texturing in an alkaline aqueous solution. Another application was to exploit the APCVD SiOx as a plating mask for silicon heterojunction solar cells. Two processing options prior to the oxide-film deposition were investigated: i) application of an Ag seed-layer, which promotes subsequent electroplating, and ii) printing of an organic grid, which, after stripping, creates openings in the SiOx that facilitate electroplating of the solar cell's electrode on the underlying transparent conducting oxide. In a different application, the APCVD SiOx films acted as protection against parasitic plating on the front side of passivated emitter and rear solar cells. The deposited films were characterized by ellipsometry, hemispherical reflectance measurements, scanning electron microscopy, energy dispersive X-ray spectroscopy and optical microscopy.

Magnetohydrodynamic convection in a downward flow of liquid metal in a vertical duct is investigated experimentally and numerically. It is known from earlier studies that in a certain range of parameters, the flow exhibits high-amplitude pulsations of temperature in the form of isolated bursts or quasi-regular fluctuations. This study extends the analysis while focusing on the effects of symmetry introduced by two-sided rather than one-sided wall heating. It is found that the temperature pulsations are robust physical phenomena appearing for both types of heating and various inlet conditions. At the same time, the properties, typical amplitude, and range of existence in the parametric space are very different at the symmetric and asymmetric heating. The obtained data show good agreement between computations and experiments and allow us to explain the physical mechanisms causing the pulsation behavior.

In this study, a new class of magnetorheological (MR) damper, which can realize desired damping force at both low and high speeds of vehicle suspension systems, is proposed and its salient characteristics are shown through computer simulations. Unlike conventional MR dampers, the proposed MR damper has a specific pole shape function and therefore the damping coefficient is changed by varying the effective area of the main orifice. In addition, by controlling the opening or closing the bypass orifice, the drastic change of the damping coefficient is realizable. After briefly describing the operating principle, a mathematical modeling is performed considering the pole shape function which is a key feature of the proposed MR damper. Then, the field-dependent damping force and piston velocity-dependent characteristics are presented followed by an example on how to achieve desired damping force characteristics by changing the damping coefficient and slope breaking point which represents the bilinear damping property.

Biological neural networks outperform current computer technology in terms of power consumption and computing speed while performing associative tasks, such as pattern recognition. The analogue and massive parallel in-memory computing in biology differs strongly from conventional transistor electronics that rely on the von Neumann architecture. Therefore, novel bio-inspired computing architectures have been attracting a lot of attention in the field of neuromorphic computing. Here, memristive devices, which serve as non-volatile resistive memory, are employed to emulate the plastic behaviour of biological synapses. In particular, CMOS integrated resistive random access memory (RRAM) devices are promising candidates to extend conventional CMOS technology to neuromorphic systems. However, dealing with the inherent stochasticity of resistive switching can be challenging for network performance. In this work, the probabilistic switching is exploited to emulate stochastic plasticity with fully CMOS integrated binary RRAM devices. Two different RRAM technologies with different device variabilities are investigated in detail, and their potential applications in stochastic artificial neural networks (StochANNs) capable of solving MNIST pattern recognition tasks is examined. A mixed-signal implementation with hardware synapses and software neurons combined with numerical simulations shows that the proposed concept of stochastic computing is able to process analogue data with binary memory cells.