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Abstract: Emissions of green-house gasses have been in the forefront of scientific research in recent decades. One of the approaches towards reducing the amount of green gas CO2 in the atmosphere is its capture and storage with subsequent conversion where pure enough CO2 can be regenerated. While CO2 capture widely utilizes two mature technologies, amine absorption and cryogenic distillation, they both have significant downsides, in either cost or potential new danger to the environment. To that end an adsorption-based CO2 capture has seen quite a lot of interest in recently. Nanoporous materials have been extensively studied for this application, starting with zeolites, followed by aluminophosphates and also the new members of the porous materials group, the so called reticular porous materials. Metal-Organic Frameworks (MOFs), the first discovered reticular porous materials have shown very promising results for post combustion CO2 capture and recently also for in-door and direct air capture. MOFs are in general enough thermally stable for CO2 capture, their main weakness for wide applicability is sometimes lower selectivity for CO2 in real gas mixtures and lower stability in humid conditions. Zeolitic imidazolate frameworks (ZIFs), a subgroup of MOFs, have in recent years been extensively studied for sorption applications, also CO2, due to their superior stability and kinetics for vapour/gas adsorption if compared to carboxylate-based MOFs. While extensively studied, an overview of articles shows that most research is limited to a limited set group of frameworks, with ZIF-8 being used in more than half of ZIF papers. While ZIF-8 has successfully been prepared in water and even in solvent-free conditions, the rest of the ZIFs synthesis still heavily rely on solvothermal synthesis with formamide based solvent systems and synthesis times upwards of 5 days. Even in the case of ZIF-8, while greener synthesis approaches are available, dimethylformamide (DMF) synthesis still prevails in the cases tested for CO2 capture, mainly due to the increased CO2 uptake resulting from the synergistic contribution of the remaining DMF solvent in the pores. The goal of this thesis was to develop green synthesis approaches, both solvothermal and mechanochemical, for known ZIFs and then to extend the scope towards preparation of new ZIF materials. The goal for latter was to experimentally determine the optimal topology and functionality of ZIFs for CO2 adsorption in humid conditions. Model humid gas isotherms were developed and measured for a series of ZIFs with mostly SOD (sodalite) and RHO framework topologies and Zn and Ni as metal nodes. Finally, some novel bio-based binder materials were tested for the use with ZIFs. The sorption tests revealed than the SOD topology ZIFs have high potential for CO2 sorption applications, as the adsorption is rapid and further combination of terminally functionalised imidazoles in those frameworks drastically increases the frameworks affinity for CO2 at lower pressures. With most common 4,5- functionalised imidazole having hydrophilic functional groups, the challenge of competitive water sorption still remains. On the other hand some hydrophobic 4,5-substituted sodalite ZIFs, both with 4,5-dichloroimidazole, show excellent CO2 sorption and even complete hydrophobicity. The results led us to hypothesize that further research on ZIFs- for CO2 capture has to shift form 2 substituted sodalite frameworks to 4,5 substituted frameworks with strongly dipolar hydrophobic groups. The hydrophilic polar groups currently in use lead to issues with competitive water adsorption, due to their potential to form hydrogen bonds with water. Furthermore, some new agar and alginate based shaping methods were tested, as both potential binders are not environmentally toxic and are already used on the industrial scale world-wide for other applications.
Keywords: carbon capture, synthesis, metal-organic frameworks, zeolitic imidazolate frameworks, nanoporous materials, dissertations
Published in RUNG: 10.09.2024; Views: 430; Downloads: 15
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Keywords: EarthCARE, Saharan dust, validation, aerosol, airborne measurements
Published in RUNG: 09.09.2024; Views: 272; Downloads: 2
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Abstract: The NASA Convective Processes Experiment - Cabo Verde (CPEX-CV) field campaign took place in September 2022 out of Sal Island, Cabo Verde. A unique payload aboard the NASA DC-8 aircraft equipped with advanced remote sensing and in situ instrumentation, in conjunction with radiosonde launches and satellite observations, allowed CPEX-CV to target the coupling between atmospheric dynamics, marine boundary layer properties, convection, and the dust-laden Saharan Air Layer in the data-sparse tropical East Atlantic region. CPEX-CV provided measurements of African Easterly Wave environments, diurnal cycle impacts on convective lifecycle, and several Saharan dust outbreaks, including the highest dust optical depth observed by the DC-8 interacting with what would become Tropical Storm Hermine. Preliminary results from CPEX-CV underscore the positive impact of dedicated tropical East Atlantic observations on downstream forecast skill, including sampling environmental forcings impacting the development of several non-developing and developing convective systems such as Hurricanes Fiona and Ian. Combined airborne radar, lidar, and radiometer measurements uniquely provide near-storm environments associated with convection on various spatiotemporal scales and, with in situ observations, insights into controls on Saharan dust properties with transport. The DC-8 also collaborated with the European Space Agency to perform coordinated validation flights under the Aeolus spaceborne wind lidar and over the Mindelo ground site, highlighting the enhanced sampling potential through partnership opportunities. CPEX-CV engaged in professional development through dedicated team building exercises that equipped the team with a cohesive approach for targeting CPEX-CV science objectives and promoted active participation of scientists across all career stages.
Keywords: convective processesž, Saharan dust, aerosol, airborne measurements
Published in RUNG: 09.09.2024; Views: 244; Downloads: 4
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Abstract: The emergence of antimicrobial resistance due to antibiotics in the environment presents significant public health, economic, and societal risks. This study addresses the need for effective strategies to reduce antibiotic residues, focusing on ciprofloxacin degradation. Magnetic iron oxide nanoparticles (IO NPs), approximately 13 nm in size, were synthesized and functionalized with branched polyethyleneimine (bPEI) to obtain a positive charge. These IO-bPEI NPs were combined with negatively charged titanium dioxide NPs (TiO2@CA) to form magnetically photocatalytic IO-TiO2 nanocomposites. Characterization techniques, including X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), infrared spectroscopy (IR), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), electrokinetic measurements, and a vibrating sample magnetometer (VSM), confirmed the successful formation and properties of the nanocomposites. The nanocomposites exhibited a high specific surface area, reduced mobility of photogenerated charge carriers, and enhanced photocatalytic properties. Testing the photocatalytic potential of IO-TiO2 with ciprofloxacin in water under UV-B light achieved up to 70% degradation in 150 min, with a degradation rate of 0.0063 min−1. The nanocomposite was magnetically removed after photocatalysis and successfully regenerated for reuse. These findings highlight the potential of IO-TiO2 nanocomposites for reducing ciprofloxacin levels in wastewater, helping curb antibiotic resistance.
Keywords: photocatalytic degradation, magnetic iron oxide-TiO2 nanocomposites, hetero-agglomeration, multifunctionality, antibiotic ciprofloxacin, antimicrobial resistance
Published in RUNG: 09.09.2024; Views: 286; Downloads: 3
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Abstract: Dark matter (DM), known to be a dominant matter component in the Universe, has been searched for extensively, yet remains undetected. One of the promising avenues of detecting a DM signal is to observe the so called ’DM sub-halos’ within our galaxy. These sub-halos, which are numerous within the Milky Way, are formed by the clustering of DM, as predicted by cosmological simulations, and most of them lack baryonic matter counterparts, making them challenging to detect. How- ever, the annihilation or decay of Weakly Interacting Massive Particles (WIMPs), a leading candidate for DM, within these sub-halos is expected to produce very high-energy (VHE) photons (called gamma-rays) at TeV energies, offering possible indirect DM detection. In this thesis, we focus on the Galactic Plane Survey (GPS) of the Cherenkov Tele- scope Array Observatory (CTAO), an upcoming ground-based gamma-ray obser- vatory, which promises unprecedented sensitivity and resolution in the detection of cosmic gamma-ray sources in the ∼ 30 GeV to ∼ 100 TeV energy range. As dark sub-halos are expected to appear as unidentified (point) sources in the CTAO GPS data, we employ a machine learning (ML)-based approach, the AutoSour- ceID framework, leveraging U-shaped networks (U-Nets) and Laplacian of Gaus- sian (LoG) filter, for automatic source detection and localization, and apply it to simulated GPS data. We establish detection thresholds for U-Nets trained on dif- ferently scaled counts (counts, square root or log of counts) and identify which approach offers best results (in terms of flux sensitivity and location accuracy). Our findings suggest that using log-scaled counts yields a factor of 1.7 lower flux threshold compared to counts alone. In addition, we compare our ML outcomes with traditional methods; however, this comparison is not straightforward, as ML and traditional approaches fundamentally differ in their methodologies and un- derlying assumptions. Nevertheless, The flux threshold obtained using log-scaled counts is comparable to that of the traditional likelihood-based detection method implemented in the Gammapy library, although further study is needed to estab- lish a more definitive comparison. These preliminary results also suggest that the flux threshold for detecting 90% of true sources with the ML approach is approx- imately two times lower than the sensitivity reported for the GPS in the CTAO publication. Although these results are not directly comparable due to differences in methodology, they hint that ML methods may offer superior performance in certain scenarios. Furthermore, we discuss the implications of our results on the sensitivity to DM sub-halos, improving it by a factor of 4, highlighting the possi- bility of detecting at least one sub-halo with a cross section approximately ⟨σv⟩ = 2.4 × 10−23 cm3 /s.
Keywords: Cherenkov Telescope Array Observatory, dark matter, sub-halos, machine learning, gamma-rays, master's thesis
Published in RUNG: 06.09.2024; Views: 338; Downloads: 1
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