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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Valley notch filter in a graphene strain superlattice: Green's function and machine learning approach

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Author(s):
Torres, V [1, 2] ; Silva, P. [1] ; de Souza, E. A. T. [1] ; Silva, L. A. [3, 4] ; Bahamon, D. A. [1]
Total Authors: 5
Affiliation:
[1] Univ Prebiteriana Mackenzie, MackGraphe Graphene & Nanomat Res Ctr, Rua Consolacao 896, BR-01302907 Sao Paulo, SP - Brazil
[2] Univ Fed Fluminense, Inst Fis, Av Litoranea S-N, BR-24210340 Niteroi, RJ - Brazil
[3] Univ Prebiteriana Mackenzie, Sch Comp & Informat, Rua Consolacao 896, BR-01302907 Sao Paulo, SP - Brazil
[4] Univ Prebiteriana Mackenzie, Grad Program Elect Engn & Comp, Rua Consolacao 896, BR-01302907 Sao Paulo, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: Physical Review B; v. 100, n. 20 NOV 11 2019.
Web of Science Citations: 0
Abstract

The valley transport properties of a superlattice of out-of-plane Gaussian deformations are calculated using a Green's function and a machine learning approach. Our results show that periodicity significantly improves the valley filter capabilities of a single Gaussian deformation; these manifest themselves in the conductance as a sequence by valley filter plateaus. We establish that the physical effect behind the observed valley notch filter is the coupling between counterpropagating transverse modes; the complex relationship between the design parameters of the superlattice and the valley filter effect make it difficult to estimate in advance the valley filter potentialities of a given superlattice. With this in mind, we show that a deep neural network can be trained to predict valley polarization with a precision similar to the Green's function but with much less computational effort. (AU)

FAPESP's process: 15/11779-4 - Plasmonic and nonlinear effects in graphene coupled to optical waveguides
Grantee:Christiano José Santiago de Matos
Support type: Research Projects - Thematic Grants
FAPESP's process: 12/50259-8 - Graphene: photonics and opto-electronics: UPM-NUS collaboration
Grantee:Antonio Helio de Castro Neto
Support type: Research Projects - SPEC Program
FAPESP's process: 18/07276-5 - Mid- and far-infrared plasmonic biosensing with graphene
Grantee:Christiano José Santiago de Matos
Support type: Regular Research Grants