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SOLAR DECATHLON EUROPE - TEAM MIMO DER HSD STELLT SICH DER AUFSTOCKUNG SAMT SANIERUNG DES CAFÉS ADA
(2021)
Development of open educational resources for renewable energy and the energy transition process
(2021)
Forschungsdatenmanagement (FDM) umfasst alle Aktivitäten, die mit der Planung, Erhebung, Aufbereitung, Speicherung, Archivierung und Veröffentlichung von Forschungsdaten verbunden sind. Hierbei sind sowohl generische als auch fachspezifische Aspekte zu berücksichtigen; außerdem müssen rechtliche und technische Gesichtspunkte beachtet werden. Dies erfordert ein umfangreiches Serviceportfolio – von Information und Sensibilisierung über Beratung und Koordination bis hin zu IT-Infrastrukturen.
Mit der Förderlinie FDMScouts.nrw unterstützen das Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen und die Digitale Hochschule NRW (DH.NRW) im Rahmen der landesweiten Digitalisierungsoffensive fünf Hochschulverbünde bei der nachhaltigen Verankerung des Themas FDM auf strategischer und operativer Ebene. Dabei werden sie inhaltlich und organisatorisch von der Landesinitiative fdm.nrw begleitet. Die hieraus resultierenden Impulse für den bedarfsgerechten Auf- und Ausbau von Kontaktstellen, Kompetenzen und Kapazitäten zum FDM sollen über die Verbünde hinaus auch anderen interessierten Hochschulen für angewandte Wissenschaften (HAW) und Fachhochschulen (FH) zugutekommen.
Das vorliegende Poster zeigt die Handlungsfelder und die einzelnen Aktivitäten, die im Rahmen der Förderlinie FDMScouts.nrw im ersten Förderjahr bereits begonnen bzw. umgesetzt wurden. Dieses Poster wurde in vergleichbarer Form auf der Jahrestagung der Digitalen Hochschule NRW am 14. und 15. September 2021 präsentiert.
Individual addressing of trapped ions and coupling of motional and spin states using RF radiation
(2009)
Individual electrodynamically trapped and laser cooled ions are addressed in frequency space using radio-frequency radiation in the presence of a static magnetic field gradient. In addition, an interaction between motional and spin states induced by an rf field is demonstrated employing rf optical double resonance spectroscopy. These are two essential experimental steps towards realizing a novel concept for implementing quantum simulations and quantum computing with trapped ions.
Performance Testing and Optimization of Solar Assisted Heating Systems for Multi Family Houses
(2016)
Market and simulation analysis of PVT applications for the determination of new PVT test procedures
(2014)
Many different cell types are able to migrate by formation of a thin actin-based cytoskeletal extension. Recently, it became evident that this extension consists of two distinct substructures, designated lamellipodium and lamellum, which differ significantly in their kinetic and kinematic properties as well as their biochemical composition. We developed a stochastic two-dimensional computer simulation that includes chemical reaction kinetics, G-actin diffusion, and filament transport to investigate the formation of growing actin networks in migrating cells. Model parameters were chosen based on experimental data or theoretical considerations. In this work, we demonstrate the system's ability to form two distinct networks by self-organization. We found a characteristic transition in mean filament length as well as a distinct maximum in depolymerization flux, both within the first 1-2 microm. The separation into two distinct substructures was found to be extremely robust with respect to initial conditions and variation of model parameters. We quantitatively investigated the complex interplay between ADF/cofilin and tropomyosin and propose a plausible mechanism that leads to spatial separation of, respectively, ADF/cofilin- or tropomyosin-dominated compartments. Tropomyosin was found to play an important role in stabilizing the lamellar actin network. Furthermore, the influence of filament severing and annealing on the network properties is explored, and simulation data are compared to existing experimental data.
Despite its impressive complexity the cytoskeleton succeeds to persistently organize itself and thus the cells' interior. In contrast to classical man-made machines, much of the cellular organization originates from inherent self-assembly and self-organization allowing a high degree of autonomy for various functional units. Recent experimental and theoretical studies revealed numerous examples of cytoskeleton components that arrange and organize in a self-regulative way. In the present review we want to shortly summarize some of the principle mechanisms that are able to inherently trigger and regulate the cytoskeleton organization. Although taken individually most of these regulative principles are rather simple with intuitively predictable consequences, combinations of two or more of these mechanisms can quickly give rise to very complex, unexpected behavior and might even be able to explain the formation of different functional units out of a common pool of available building blocks.
Kohlendioxid, Biomasse und Regenerativer Strom - Ressourcen einer neuen Kohlenstoffwirtschaft?
(2017)
The rock material pentlandite with the composition Fe4.5Ni4.5S8 was synthesized via high temperature synthesis from the elements. The structure and composition of the material was characterized via powder X-ray diffraction (PXRD), Mössbauer spectroscopy (MB), scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and energy dispersive X-ray spectroscopy (EDX). Two preparation methods of pentlandite bulk electrodes are presented. In the first approach a piece of synthetic pentlandite rock is directly contacted via a wire ferrule. The second approach utilizes pentlandite pellets, pressed from finely ground powder, which is immobilized in a Teflon casing. Both electrodes, whilst being prepared by an additive-free method, reveal high durability during electrocatalytic conversions in comparison to common drop-coating methods. We herein showcase the striking performance of such electrodes to accomplish the hydrogen evolution reaction (HER) and present a standardized method to evaluate the electrocatalytic performance by electrochemical and gas chromatographic methods. Furthermore, we report stability tests via potentiostatic methods at an overpotential of 0.6 V to explore the material limitations of the electrodes during electrolysis under industrial relevant conditions.
In the present contribution, the utilization of steel-mill gases for an industrial methanol synthesis process is described. The focus of this work is on the influence of syngas compositions derived from steel-mill gases on an industrial Cu/ZnO/Al2O3 catalyst. Elevated CO2 and H2O concentrations seem to have an irreversible impact on the activity of the catalyst. In order to obtain realistic gas composition for the catalyst tests, a process simulation of the methanol synthesis was conducted. The calculated gas compositions at the reactor inlet were applied in a practical test in order to evaluate the catalyst stability under steel mill gas conditions. No noticeable deactivation was observed.
Videokunst, Sammlung, Archiv
(2020)
The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.