ﻻ يوجد ملخص باللغة العربية
The weak intrinsic spin-orbit coupling in graphene can be greatly enhanced by proximity coupling. Here we report on the proximity-induced spin-orbit coupling in graphene transferred by hexagonal boron nitride (hBN) onto the topological insulator Bi$_{1.5}$Sb$_{0.5}$Te$_{1.7}$Se$_{1.3}$ (BSTS) which was grown on a hBN substrate by vapor solid synthesis. Phase coherent transport measurements, revealing weak localization, allow us to extract the carrier density-dependent phase coherence length $l_phi$. While $l_phi$ increases with increasing carrier density in the hBN/graphene/hBN reference sample, it decreases in BSTS/graphene due to the proximity-coupling of BSTS to graphene. The latter behavior results from Dyakonov-Perel-type spin scattering in graphene with a large proximity-induced spin-orbit coupling strength of at least 2.5 meV.
We used low-energy, momentum-resolved inelastic electron scattering to study surface collective modes of the three-dimensional topological insulators Bi$_2$Se$_3$ and Bi$_{0.5}$Sb$_{1.5}$Te$_{3-x}$Se$_{x}$. Our goal was to identify the spin plasmon p
Van der Waals heterostructures composed of multiple few layer crystals allow the engineering of novel materials with predefined properties. As an example, coupling graphene weakly to materials with large spin orbit coupling (SOC) allows to engineer a
We performed x-ray magnetic circular dichroism (XMCD) measurements on heterostructures comprising topological insulators (TIs) of the (Bi,Sb)$_2$(Se,Te)$_3$ family and the magnetic insulator EuS. XMCD measurements allow us to investigate element-sele
Spin-orbit coupling (SOC) in graphene can be greatly enhanced by proximity coupling it to transition metal dichalcogenides (TMDs) such as WSe2. We find that the strength of the acquired SOC in graphene depends on the stacking order of the heterostruc
Spin-orbit coupling in graphene can be increased far beyond its intrinsic value by proximity coupling to a transition metal dichalcogenide. In bilayer graphene, this effect was predicted to depend on the occupancy of both graphene layers, rendering i