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Graphene is a nonlinear material which can be used as a saturable absorber, frequency mixer and frequency multiplier. We investigate the third harmonic generation from graphene lying on different substrates, consisting of a dielectric…

Mesoscale and Nanoscale Physics · Physics 2017-02-09 N. A. Savostianova , S. A. Mikhailov

The use of Raman scattering techniques to study the mechanical properties of graphene films is reviewed here. The determination of Gruneisen parameters of suspended graphene sheets under uni- and bi-axial strain is discussed and the values…

Materials Science · Physics 2015-05-19 Nicola Ferralis

The isolation of graphene has triggered an avalanche of studies into the spin-dependent physical properties of this material, as well as graphene-based spintronic devices. Here we review the experimental and theoretical state-of-art…

Mesoscale and Nanoscale Physics · Physics 2015-03-11 Wei Han , Roland K. Kawakami , Martin Gmitra , Jaroslav Fabian

Scattering transforms are non-trainable deep convolutional architectures that exploit the multi-scale resolution of a wavelet filter bank to obtain an appropriate representation of data. More importantly, they are proven invariant to…

Machine Learning · Computer Science 2019-06-13 Fernando Gama , Joan Bruna , Alejandro Ribeiro

The recent discovery of methods to isolate graphene, a one-atom-thick layer of crystalline carbon, has raised the possibility of a new class of nano-electronics devices based on the extraordinary electrical transport and unusual physical…

Mesoscale and Nanoscale Physics · Physics 2008-10-02 Xu Du , Ivan Skachko , Anthony Barker , Eva Y. Andrei

Because of its fascinating electronic properties, graphene is expected to produce breakthroughs in many areas of nanoelectronics. For spintronics, its key advantage is the expected long spin lifetime, combined with its large electron…

The distribution of net electric charge in graphene is investigated, using both a constitutive atomic charge-dipole interaction model and an approximate analytical solution to Laplace's equation. We demonstrate a strong size dependence of…

Mesoscale and Nanoscale Physics · Physics 2009-09-21 Zhao Wang , Robert W. Scharstein

In contrast to conventional structures, efficient non-radiative carrier recombination counteracts the appearance of optical gain in graphene. Based on a microscopic and fully quantum-mechanical study of the coupled carrier, phonon, and…

Mesoscale and Nanoscale Physics · Physics 2015-08-12 Roland Jago , Torben Winzer , Andreas Knorr , Ermin Malic

Electronic and transport properties of Graphene, a one-atom thick crystalline material, are sensitive to the presence of atoms adsorbed on its surface. An ensemble of randomly positioned adatoms, each serving as a scattering center, leads…

Materials Science · Physics 2015-05-13 V. V. Cheianov , V. I. Fal'ko , O. Syljuasen , B. L. Altshuler

Graphene, dubbed as a two-dimensional material represents the topological concept of "surface" embedded in a three-dimensional space. This regard enables to employ existing theories/tools in topology to understand different…

Mesoscale and Nanoscale Physics · Physics 2018-09-27 Hadi Arjmandi-Tash , Alexander Kloosterman , Gregory F. Schneider

Conventional three-dimensional crystal lattices are terminated by surfaces, which can demonstrate complex rebonding and rehybridisation, localised strain and dislocation formation. Two dimensional crystal lattices, of which graphene is the…

Mesoscale and Nanoscale Physics · Physics 2012-07-23 Viktoria V. Ivanovskaya , Philipp Wagner , Alberto Zobelli , Irene Suarez-Martinez , Abu Yaya , Christopher P. Ewels

Only one atom thick and not inclined to lattice defects, graphene represents the ultimate crystalline membrane. However, its structure reveals unique features not found in other crystalline membranes, in particular the existence of ripples…

Materials Science · Physics 2016-09-08 Doron Gazit

Reflectance and transmittance of graphene in the optical region are analyzed as a function of frequency, temperature, and carrier density. We show that the optical graphene properties are determined by the direct interband electron…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 L. A. Falkovsky

The stability number of a graph G is the cardinality of a stability system of G (that is of a stable set of maximum size of G). A graph is alpha-stable if its stability number remains the same upon both the deletion and the addition of any…

Combinatorics · Mathematics 2007-05-23 Vadim E. Levit , Eugen Mandrescu

Ever since the discovery of graphene and subsequent explosion of interest in single atom thick materials, studying their mechanical properties has been an active area of research. New length scales often necessitate a rethinking of physical…

In this work we explore mechanical properties of graphene samples of variable thickness. For this purpose, we coupled a high pressure sapphire anvil cell to a micro-Raman spectrometer. From the evolution of the G band frequency with stress…

Graphynes and graphdiynes are carbon 2D allotrope structures presenting both sp2 and sp hybridized atoms. These materials have been theoretically predicted but due to intrinsic difficulties in their synthesis, only recently some of these…

Mesoscale and Nanoscale Physics · Physics 2017-02-21 Daniel Solis , Cristiano F. Woellner , Daiane D. Borges , Douglas S. Galvao

We address the two-dimensional band-structure of graphene above the vacuum level in the context of discrete states immersed in the three-dimensional continuum. Scattering resonances are discovered that originate from the coupling of the…

Mesoscale and Nanoscale Physics · Physics 2013-01-31 V. U. Nazarov , V. M. Silkin , E. E. Krasovskii

Graphene, a single sheet of graphite, has attracted tremendous attention due to recent experiments which demonstrate that carriers in it are described by massless fermions with linear dispersion. In this note, we consider the possibility of…

Strongly Correlated Electrons · Physics 2015-06-25 Hari P Dahal , Yogesh N. Joglekar , Kevin S. Bedell , Alexander V. Balatsky

Graph neural networks (GNNs) are learning architectures that rely on knowledge of the graph structure to generate meaningful representations of large-scale network data. GNN stability is thus important as in real-world scenarios there are…

Machine Learning · Computer Science 2021-04-27 Luana Ruiz , Zhiyang Wang , Alejandro Ribeiro
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