A graphene strain superlattice made of repeated Gaussian bumps produces valley-polarized conductance plateaus, and a deep neural network can approximate the valley polarization computed by Green's functions.
Manipulation of Valley Isospins in Strained Graphene for Valleytronics
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abstract
Graphene's outstanding mechanical properties lend to strain engineering, allowing for future valleytronics and nanoelectromechanic applications. In this work, we have found that a Gaussian-shaped strain on a graphene p-n junction results in quantum Hall conductance oscillations due to the rotated angle between valley isospins at the graphene armchair edges. Furthermore, additional Fano resonances were observed as the value of the strain-induced pseudo-magnetic field approaches that of the external magnetic field. The lifted valley degeneracy, stemming from the interplay between the real and pseudo-magnetic fields, results in clearly valley-resolved Fano resonances. Exploring strain engineering as a means to control conductance through valley isospin manipulation is believed to open the door to potential graphene valleytronic devices.
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cond-mat.mes-hall 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
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Valley notch filter in a graphene strain superlattice: Green's function and machine learning approach
A graphene strain superlattice made of repeated Gaussian bumps produces valley-polarized conductance plateaus, and a deep neural network can approximate the valley polarization computed by Green's functions.