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    EXC 3120 BlueMat - Cross Area Imaging
    To unravel the unique physics and chemistry of water-driven materials, the CA Imaging aims to achieve groundbreaking innovations in three primary focus areas: (1) extreme temporal resolution imaging, (2) multiscale imaging spanning 10 orders of magnitude in length and 16 in time, and (3) correlative image analysis that integrates these diverse data sources to uncover the role and structural dynamics of water in multiscale structured matter with an unprecedented accuracy and comprehensiveness. To this end, BlueMat will leverage the unparalleled infrastructure at the EuXFEL and PETRA III at DESY in Hamburg, offering exceptional opportunities for correlative in-operando characterization. Extreme temporal resolution imaging will be realized by advancing MHz X-ray multi-projection imaging (MHz XMPI), stroboscopic pump-probe X-ray diffraction (XRD), and X-ray photon correlation spectroscopy (XPCS) at X-ray free electron lasers. This will enable the visualization of atomic interactions, molecular mobility, and flow dynamics down to femtosecond and picosecond timescales. Leveraging a uniquely comprehensive combination of methods, we will image water across a wide range of scales. For instance, we will observe macroscale mean flow using magnetic resonance (MR), ?m- to sub-?m-scale flow patterns via synchrotron radiation nano computed tomography (SRnCT), and detailed processes at the nm-scale using scanning and transmission electron microscopy (SEM/TEM). Finally, CA Imaging will pioneer computational and deep learning techniques to achieve a step change in throughput and resolution of characterization methods, enabling truly correlative image analysis. The qualitative and quantitative data collected in CA Imaging are crucial for model validation in CA Modeling and calibration in CA Exploitation & Experiencing. By making these unique methods available to all young researchers in the cluster, CA Imaging further contributes to the highly advanced education they will receive.
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    Design of structured packings using CFD-based optimization, absorption experiments and magnetic resonance imaging
    In order to achieve the ambitious target of carbon neutrality by 2050, the chemical industry has to pursue major transformations. In addition to a gradual shift to renewable resources and energy systems, especially energy-intensive operations have to be optimized. In this context, thermal separation processes such as absorption and distillation are of crucial importance, as they not only contribute significantly to the energy demand of the chemical industry but are also of particular importance for CO2 utilization in the context of CO2 capture. Besides process intensification and energy integration measures on the process systems level, performance improvements of the individual unit operations are of utmost importance. Structured packings have become the most important internals for mass transfer and hydraulic performance improvements in absorption and distillation columns. While the design of structured packings has been actively researched for nearly six decades, additive manufacturing allows for novel, unconventional, and topologically complex packing structures and provides an efficient method for rapid prototyping. However, so far it has not had a considerable impact on the design of structured packings, since the resulting increased freedom in the design also poses a considerable challenge. This challenge may effectively be addressed by mathematical optimization methods, given that adequate problem formulations and performance models are available to efficiently compute the performance of the printed packing in a real application. In order to achieve this goal, the current project pursues the development of a systematic design approach based on mathematical optimization, that exploits the bi-functional use of computer-aided design (CAD) models for computational fluid dynamics (CFD) simulations and additive manufacturing. The latter allows for rapid prototyping of polymeric packings which will not only be investigated in hydraulic and absorption experiments, providing integral performance data but also enabling more fundamental insight into the fluid flow by means of an innovative and worldwide unique large-bore vertical Magnetic Resonance Imaging (MRI) system. The experiments will reveal the local distribution of the fluid and gas in the 3D-printed structured packings together with the local fluid velocities in all three spatial directions. The data obtained from the MRI experiments will enable a targeted improvement of the simulation models, which are providing the basis for a CFD-based optimization of individual packing designs, exploring different model formulations. Shape, topology, and parametric optimization approaches will be investigated to effectively develop innovative packing structures with significant performance improvements based on the optimization of the CAD models and validate the performance of the resulting packings experimentally using 3D printing.
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    CRC 1615 - Project B03: Magnetic resonance imaging of large-scale multiphase and reactive flow systems
    In this project, we will develop and use magnetic resonance imaging (MRI) methods which allow to non-intrusively quantify a variety of process variables at high spatial and temporal resolution. The measured variables include the spatial distribution, the velocity, the temperature, and the chemical composition of the phases in the reactor, as well as the pore size distribution and diffusion properties of gels. In numerous collaborations within the CRC, these MRI methods are applied to characterise the material and system components of SMART reactors. The experiments of this project are mainly carried out on a globally unique large-scale vertical MRI system located at the TUHH.
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