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Computational workflow optimization for magnetic fluctuation measurements of 3D nano-tetrapods
(2021)
The detailed understanding of micro–and nanoscale structures, in particular their magnetization dynamics, dominates contemporary solid–state physics studies. Most investigations already identified an abundance of phenomena in one–and two–dimensional nanostructures. The following thesis focuses on the magnetic fingerprint of three–dimensional CoFe nano–magnets, specifically the temporal development of their hysteresis loop. These nano–magnets were grown in a tetrahedral pattern on top of a highly susceptible home–build GaAs/AlGaAs micro–Hall sensor using focused electron beam induced deposition (FEBID).
During the measurements, utmost efforts were employed to exemplify current best research practices. The data life cycle of the present thesis is based upon open–source data science tools and packages. Data acquisition and analysis required self–written automated algorithms to handle the extensive quantity of data. Existing instrumental-controlling software was improved, and new Python packages were devised to analyze and visualize the gathered data. The open–source Python data analysis framework (ana) was developed to facilitate computational reproducibility. This framework transparently analyses and visualizes the gathered data automatically using Continuous Analysis tools based on GitLab and Continuous Integration. This automatization uses bespoke scripts combined with virtualization tools like Docker to facilitate reproducible and device–independent results.
The hysteresis loops reveal distinct differences in subsequently measured loops with identical initial experimental parameters, originating from the nano–magnet’s magnetic noise. This noise amplifies in regions where switching processes occur. In such noise–prone regions, the time–dependent scrutinization reveals presumably thermally induced metastable magnetization states. The frequency–dependent power spectral density uncovers a characteristic 1/f² behavior at noise–prone regions with metastable magnetization states.
Die vorliegende Dissertation behandelt das Thema der Wechselstromleitfähigkeit nano-granularer Metalle, welche mit Hilfe der fokussierten elektronenstrahlinduzierten Direktabscheidung (FEBID) hergestellt wurden, sowie der dielektrischen Relaxation in metall-organischen Gerüstverbindungen (MOFs). Sie war eingebettet in das interdisziplinäre Projekt „Dielectric and Ferroelectric Surface-Mounted Metal-Organic Frameworks (SURMOFs) as Sensor Devices“ im Rahmen des DPG-Schwerpunktsprogramms „Coordination Networks: Building Blocks for Functional Systems“ (SPP 1928, COORNETs). Dabei verfolgt sie ein Sensorkonzept zur selektiven Detektion von Analytgasen. Der zentrale Erfolg der Arbeit besteht dabei in neuen Erkenntnissen über die Wechselstromleitfähigkeit nano-granularer Pt(C)-FEBID-Deponate. Die hierbei gewonnen Erkenntnisse können in Zukunft einen weiteren Baustein in der theoretischen Beschreibung dieses grundlegend interessanten und für sensorische Anwendungen wichtigen Teilgebiets der Festkörperphysik darstellen.