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6. Proučevanje eno in večkovinskih katalizatorjev na silikatnem nosilcu v naprednem oksidacijskem procesu za čiščenje odpadnih voda : magistrsko deloSara Kozjan, 2024, magistrsko delo Opis: Ena izmed glavnih onesnaževal v odpadnih vodah so strupene organske spojine, katerih količina se z industrijskim razvojem nenehno povečuje. Najbolj nevarna so tako imenovana zaskrbljujoča onesnaževala (CEC – Contaminants of Emerging Concern), med katerimi so najpogostejših farmacevtski izdelki in izdelki za osebno nego. Za učinkovito odstranjevanje le-teh se raziskave osredotočajo na napredne oksidacijske procese (Advanced Oxidation Processes – AOP), ki s pomočjo katalizatorjev in oksidantov organska onesnaževala oksidirajo v ogljikov dioksid, vodo in mineralne kisline. Magistrska naloga se nanaša na proučevanje eno, dvo in trikovinskih katalizatorjev na silikatnem nosilcu. Kovine, ki smo jih proučevali, so bile baker, mangan in železo.
Katalizatorji so bili sintetizirani na Odseku za anorgansko kemijo in tehnologijo na Kemijskem inštitutu. Katalizatorje smo najprej ovrednotili z osnovnimi karakterizacijskimi metodami, kot so rentgenska difrakcija (XRD – X-Ray Diffraction), dušikova fizisorpcija in vrstična elektronska mikroskopija (SEM – Scanning Electron Microscopy). Ugotovili smo, da imajo višjo vsebnost kovin skoraj vsi kalcinirani katalizatorji v primerjavi z ekstrahiranimi in kalciniranimi katalizatorji, kar lahko pripišemo ekstrakcijskemu postopku, med katerim se najverjetneje odstrani določeno množino kovin iz katalizatorjev. Postopek priprave bistveno ne vpliva na specifično površino, velikost por in volumen por katalizatorjev. Pri kalciniranih katalizatorjih, ki vsebujejo Cu, je le-ta prisoten v obliki CuO.
Katalitske teste sem izvedla na dveh modelnih onesnaževalih iz skupine CEC in sicer na kumarinu (Fenton in foto-Fenton AOP) in glifosatu (Fenton AOP). Ugotovila sem, da so v primeru obeh uporabljenih modelnih onesnaževal najbolj učinkoviti dvokovinski katalizatorji in sicer pri kumarinu katalizator s Cu in Mn ter pri glifosatu katalizator s Cu in Fe. Pri kumarinu katalizator s Cu in Mn kaže tudi na fotokatalitsko aktivnost pri obsevanju z vidno svetlobo. Prav tako sem ugotovila, da so tako kot pri kumarinu tudi pri glifosatu bolj učinkoviti kalcinirani katalizatorji v primerjavi z ekstrahiranimi in kalciniranimi katalizatorji. To lahko pripišemo višji vsebnosti kovin ali/in prisotnosti Cu specij v obliki CuO v kalciniranih katalizatorjih. To ugotovitev bi bilo potrebno v nadaljevanju podrobneje raziskati.
Ključne besede: čiščenje odpadnih voda, napredni oksidacijski procesi, heterogena kataliza, katalizatorji na silikatnem nosilcu, glifosat, kumarin
Objavljeno v RUNG: 11.09.2024; Ogledov: 1728; Prenosov: 18
 Celotno besedilo (2,43 MB) |
7. Search for a signal from dark matter sub-halos with the galactic plane survey of CTA Observatory : master's thesisZoja Rokavec, 2024, magistrsko delo Opis: 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.
Ključne besede: Cherenkov Telescope Array Observatory, dark matter, sub-halos, machine learning, gamma-rays, master's thesis
Objavljeno v RUNG: 06.09.2024; Ogledov: 1642; Prenosov: 28
Celotno besedilo (5,39 MB) |
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