n the rapidly evolving semiconductor industry, precise material characterization is crucial. This thesis focuses on enhancing Ion Beam Analysis (IBA), a pivotal tool in semiconductor characterization, through the integration of differential evolution optimization. This research proposes a single and multi spectra optimization algorithm approach controlled by a web application. Central to this work is a com- parative analysis of the proposed algorithms to simulated annealing and the DE algorithm proposed by Heller et al. [5]. This analysis shows a good performance of the proposed algorithms and a potential for industry application. The web application offers users a robust, user-friendly, and scalable interface for IBA optimization. By proposing and testing new IBA optimization methods, this thesis contributes significantly to semiconductor technology, offering new methods for material characterization at microscopic level.
This project is a joint project between Imec (Leuven, Belgium) and HZDR (Dresden, Germany).

The increasing amount of untrusted content on the internet is a worrisome trend. The headline of an article can be adjusted to influence a potential readers attention and click-through rate. This clickbait or sensationalism can mislead the reader as the headline does not accurately represent the information in the corresponding article body. This headline incongruity problem has received some recent attention from the research community with proposed datasets and approaches. However, there still lacks an overarching paper that tries to answer the current state of tackling the problem. This paper aims to fill this gap, look at recent proposed datasets and approaches, and compare them. These results will be discussed, reflected on, and formulated to answer the research question in conclusion. The main conclusions from this research are that the most suited dataset for comparison purposes is the Real-News based dataset and the Graph Neural Network by Yoon et al. performed the best.