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Projection
(2009)
Production of Y-86 and other radiometals for research purposes using a solution target system
(2015)
We present the production of 58mCo on a small, 13 MeV medical cyclotron utilizing a siphon style liquid target system. Different concentrated iron(III)-nitrate solutions of natural isotopic distribution were irradiated at varying initial pressures and subsequently separated by solid phase extraction chromatography. The radio cobalt (58m/gCo and 56Co) was successfully produced with saturation activities of (0.35 ± 0.03) MBq μA−1 for 58mCo with a separation recovery of (75 ± 2) % of cobalt after one separation step utilizing LN-resin.
Production and Characterization of Porous Fibroin Scaffolds for Regenerative Medical Application
(2019)
In co-operation with the German Aerospace Center, the Solar-Institut Jülich has been analyzing the different technologies that are available for methanol production from CO2 using solar energy. The aim of the project is to extract CO2 from industrial exhaust gases or directly from the atmosphere to recycle it by use of solar energy. Part of the study was the modeling and simulating of a methane reformer for the production of synthesis gas, which can be operated by solar or hybrid heat sources. The reformer has been simplified in such a way that the model is accurate and enables fast calculations. The developed pseudo-homogeneous one- dimensional model can be regarded as a kind of counter-current heat exchanger and is able to incorporate a steam reforming reaction as well as a dry reforming reaction.
Procedures for the Determination of the Scattering Parameters for Network Analyzer Calibration
(1993)
Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.
Planning the air-terminations for a structure to be protected the use of the rolling-sphere method (electro-geometrical model) is the best way from the physics of lightning point-of-view. Therefore, international standards prefer this method. However, using the rolling-sphere method only results in possible point-of-strikes on a structure without giving information about the probability of strikes at the individual points compared to others.
Pro-Forma-Angaben
(2002)
Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability.