"Manipulating valley and spin behaviour in graphene nanostructures"

The discovery of graphene allows exotic new electron behaviours to be investigated. These properties motivate a range of new devices and technologies, and can be linked to interplays between the various symmetries that emerge in 2D systems. Here I present a few recent examples of how we can take advantage of these properties to control spin and valley currents. 

The valley degree of freedom can be linked to mechanical strain, and I show how a number of valleytronic functionalities could be realised using nanobubble structures [1]. Signatures of valley-dependent phenomena have also been reported in recent experiments based on stacked heterostructures due to the appearance of a mass term. I discuss how the selective patterning of mass regions in monolayer [2] and bilayer [3] graphene allows valley currents to be created and manipulated. This approach also overcomes difficulties that emerge when trying to reconcile experimental and theoretical transport phenomena in uniformly-gapped systems. 

Next, I discuss the formation of local magnetic moments near the edges of graphene flakes and ribbons. A large number of proposed spintronic devices are predicated on this behaviour, and recent experimental progress allows high-precision edges to be engineered.

Simulations play a key role in both interpreting experimental measurements and confirming the presence of desired magnetic behaviour. However, computational costs prevent the simulation of large-scale disorders that can occur in experiment and could quench the desired behaviour. We have developed a machine-learning approach which removes this computational bottleneck [4]. I will discuss its performance on a range of geometries, and show how spin currents in graphene nanoribbons unexpectedly survive in the presence of long-ranged edge roughness.

Finally, I consider the proximity-induced spin-orbit coupling in graphene / transition metal dichalcogenide (TMD) heterostructures. Previous studies [5] have shown that the choice of TMD layer can lead to either trivial or topological behaviour in the graphene layer. Here, we demonstrate that alloying of the metal species in the TMD layer allows this effect to be fine-tuned [6]. We argue that this provides a route toward tuning spin-valley coupling and spin-transport anisotropy in 2D heterostructures.

[1] Settnes et al (2016), Phys. Rev. Lett. 117, 276801.

[2] Aktor et al (2021), Phys. Rev. B 103, 115406.

[3] Solomon and Power (2021), Phys. Rev. B 103, 235435.

[4] Kucukbas et al (2022), under review.

[5] Gmitra et al (2016), Phys. Rev. B 93, 155104.

[6] Khatibi and Power (2022), in preparation

Participante: Dr. Stephen Power

Institución: Dublin City University, Ireland

Fecha y hora: Este evento terminó el Miércoles, 27 de Abril de 2022