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Spin properties of Graphene
Antragsteller
Professor Dr. Markus Morgenstern
Fachliche Zuordnung
Experimentelle Physik der kondensierten Materie
Förderung
Förderung von 2008 bis 2015
Projektkennung
Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 39338622
In the first part of the project, spectroscopic features of probably magnetic defect structures have been identified including the edge state at a zig-zag edge of graphene and localized states in several types of vacancy arrangements. These states should now be proven to be of magnetic origin, i.e. we will probe the magnetic properties of edge states and localized states at vacancies by static spin-polarized scanning tunnelling microscopy measurements as well as by probing the dynamic precession of defect states in a magnetic field on the local scale. For the latter, we will take advantage on the noise spectrum of the tunnelling current presumably showing peaks at the precession frequency of a local spin. For the second part of the project, we have performed systematic spin transport studies in single and bilayer graphene using MgO as a barrier material for spin injection and detection. The dominant spin scattering mechanism in bilayer graphene is shown to be of D’yakanov-Perel type such that the longest spin relaxation time is observed in samples with the lowest carrier mobility. We have observed spin relaxation times of up to 2 ns, which are an order of magnitude longer than any values previously reported for single layer graphene. Within the next period, we will, proceed towards time-resolved spin transport measurements in order to obtain information about spin decoherence. Therefore, we will improve the trans-impedance and we will control the graphene mobility by varying substrate, gate oxide and preparation processes. Finally, we will combine the expertise of both parts of the project in order to probe the time-resolved spin injection on the local scale.
DFG-Verfahren
Forschungsgruppen
Beteiligte Personen
Dr. Bernd Beschoten; Professor Dr. Gernot Güntherodt