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Fluorine, though abundant on Earth, is not readily available in a form suitable for organic synthesis. While fluoride salts like fluorite exist, they have limited reactivity due to solubility properties. Converting fluorite to hydrofluoric acid (HF) or fluorine gas (F2) increases reactivity but introduces significant safety concerns due to the …

Magnetic resonance imaging (MRI) is a diagnostic method that is used for broad range of hospitalized patient, emergency patients, chemotherapy treated and as well the patients that may have infectious diseases. Because the examinations of different patients are usually performed with the same equipment in the same environment, the surfaces …

The rapid advancements in Machine Learning (ML) and Black-Box Optimization (BBO) have led to an increased reliance on benchmarking data for evaluating and comparing algorithms across diverse domain tasks. However, the effective exploitation of this data is hindered by challenges such as syntactic variability, semantic ambiguity, and lack of standardization. …

This doctoral dissertation present research aimed into enhancing polymer-bonded Nd–Fe–B magnets through innovative surface treatments and additive manufacturing techniques, focusing on improving their mechanical strength, magnetic characteristics, and environmental stability. This research is critical for broadening the applicability of these magnets in sectors like green technologies and motion control systems. …

Hydrogen is a promising energy carrier in the emerging green energy landscape. It is environmentally friendly, transportable, and storable. The Solid Oxide Cell (SOC) system is a complex technology that enables the bidirectional conversion of hydrogen to energy. The label SOC entails solid oxide fuel cell (SOFC) systems, which produce …

Rapid population growth and increasing water demand places a serious strain on both quantity and quality of available local water resources. Climate change puts additional pressure by altering the water balance, affecting recharge conditions, and contributing to pollution and water degradation. Addressing these issues requires water management strategies that enhance …

As ecological, agricultural, and biological disciplines face mounting challenges like biodiversity loss, food chain disruption, and climate change, leveraging machine learning (ML) to process complex and heterogeneous data becomes increasingly vital. This dissertation explores the potential of ML in combination with explainability approaches for enhancing research in life sciences, specifically …

In the scope of this thesis, I focused on SrTiO3 (ST)-based dielectric ceramic composites as a lead-free perovskite material, which holds great potential for use in various electronic components. Such materials are large-scale and fabricated under high energy requirements, indicating an increasing need for a more environmentally friendly processing method. …

Automatic terminology extraction, also known as automatic term extraction (ATE), is a natural language processing (NLP) task that identifies specialized terminology from domain-specific corpora. ATE is often used for terminographic tasks (e.g., the creation of specialized dictionaries) and contributes to several complex downstream tasks (e.g., machine translation and information retrieval). …

This dissertation combines academic research and the application of its results to a real benchmark process. With the emerging electro-energetic systems that have a large share of renewable sources, hydrogen is becoming an important energy carrier that contributes to the storage and usage of surplus green energy and thus reduces …