Item type:Thesis, Open Access

Time-resolved photoemission momentum microscopy: valley depolarization in monolayer MoSe2 and enhanced data acquisition

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Abstract

This dissertation focuses on the application and further development of time-resolved photoemission momentum microscopy. It combines experimental studies of two-dimensional transition metal dichalcogenides (TMDCs) with the development of a new concept for data storage and processing that is specifically tailored to multidimensional photoemission experiments. The first part of the work addresses the use of time-resolved momentum microscopy in the sub-10-fs range on a MoSe2 and a WS2 monolayer. Using a valley-selective excitation scheme, relaxation and scattering processes in the first 4 ps after excitation were investigated at varying excitation densities. At low excitation densities, a persistent and small valley polarization can be detected in MoSe2. Furthermore, defect states were identified that act as electron reservoirs and contribute to the occupation of long-lived bound states. High excitation densities, on the other hand, led to saturation effects in the optically pumped K-valleys. Within the first 500 fs after excitation, significant material-dependent differences from WS2 were also observed, where an inversion of population was observed with a temporarily stronger occupation of the K′-valleys. The second part of the dissertation presents a specialized concept for data storage and processing developed for time-resolved momentum microscopy. The LVD data format and the accompanying conversion software, “LVD Sorter,” improve adaptability to different experimental conditions while also increasing flexibility in the processing of multi-electron hits. Systematic investigations on two experimental setups showed that both the measurement efficiency and the linearity between incoming and detected electrons can be significantly improved.

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Zajusch, Sarah: Time-resolved photoemission momentum microscopy: valley depolarization in monolayer MoSe2 and enhanced data acquisition. : 2026-05-11. DOI: https://doi.org/10.17192/openumr/709.

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This item has been published with the following license: In Copyright

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