Anisotropic Approach for Simulating Electron Transport in Layered Materials: Computational and Experimental Study of Highly Oriented Pyrolitic Graphite

Azzolini, Martina; Morresi, Tommaso; Abrams, Kerry J.; Masters, Robert; Stehling, Nicola; Rodenburg, Cornelia; Pugno, Nicola; Taioli, Simone; Dapor, Maurizio

doi:10.1021/acs.jpcc.8b02256

Cited by 18 publications

(15 citation statements)

References 27 publications

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“…Using this MC approach it is possible to simulate the anisotropic features of electron transport in layered materials. An example is the calculation of the plasmonic spectrum in highly oriented pyrolytic graphite (HOPG) [96] (see Fig. 3(f)).…”

Section: E Semiclassical Approaches: Monte-carlomentioning

confidence: 99%

Computational methods for 2D materials modelling

Carvalho,

Trevisanutto,

Taioli

et al. 2021

Preprint

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Materials with thickness ranging from a few nanometers to a single atomic layer present unprecedented opportunities to investigate new phases of matter constrained to the two-dimensional plane. Particle-particle Coulomb interaction is dramatically affected and shaped by the dimensionality reduction, driving well-established solid state theoretical approaches to their limit of applicability. Methodological developments in theoretical modelling and computational algorithms, in close interaction with experiments, led to the discovery of the extraordinary properties of two-dimensional materials, such as high carrier mobility, Dirac cone dispersion and bright exciton luminescence, and inspired new device design paradigms. This review aims to describe the computational techniques used to simulate and predict the optical, electronic and mechanical properties of two-dimensional materials, and to interpret experimental observations. In particular, we discuss in detail the particular challenges arising in the simulation of two-dimensional constrained fermions, and we offer our perspective on the future directions in this field.

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Section: E Semiclassical Approaches: Monte-carlomentioning

confidence: 99%

Computational methods for 2D materials modelling

Carvalho,

Trevisanutto,

Taioli

et al. 2021

Preprint

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“…Elastic scattering: As a first step, the differential elastic scattering cross section dσ el /dΩ is calculated for different values of the scattering angle using the following Eq. (17). These values represent the input information necessary to perform NS simulations of elastic scattering events.…”

Section: Logical Flow Of the Calculationsmentioning

confidence: 99%

A comparison between Monte Carlo method and the numerical solution of the Ambartsumian-Chandrasekhar equations to unravel the dielectric response of metals

Azzolini

Ridzel

Kaplya

et al. 2020

Computational Materials Science

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In this work we describe two different models for interpreting and predicting Reflection Electron Energy Loss (REEL) spectra and we present results of a study on metallic systems comparing the computational cost and the accuracy of these techniques. These approaches are the Monte Carlo (MC) method and the Numerical Solution (NS) of the Ambartsumian-Chandrasekhr equations. The former is based on a statistical algorithm to sample the electron trajectories within the target material for describing the electron transport. The latter relies on the numerical solution of the Ambartsumian-Chandrasekhar equations using the invariant embedding method. Both methods receive the same input parameters to deal with the elastic and inelastic electron scattering. To test their respective capability to describe REEL experimental spectra, we use copper, silver, and gold as case studies. Our simulations include both bulk and surface plasmon contributions to the energy loss spectrum by using the effective electron energy loss functions and the relevant extensions to finite momenta. The agreement between MC and NS theoretical spectra with experimental data is remarkably good. Nevertheless, while we find that these approaches are comparable in accuracy, the computational cost of NS is several orders of magnitude lower than the widely used MC. Inputs, routines and data are enclosed with this manuscript via the Mendeley database.

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“…The ELF, conveniently weighted and integrated, provides the electron inelastic scattering cross-section, 39,40 which is used, along with the elastic scattering cross-section derived from the relativistic Mott theory, 41 as an input to a Monte Carlo (MC) routine to model the transport of charged particles within these solids and predict the reflection electron energy loss (REEL) spectra in particular. [42][43][44][45][46][47][48][49] REEL spectroscopy is an analysis technique that uses an electron beam impinging with kinetic energy lower than 2 keV into thin films. Primary electrons penetrate a few nanometers into the material surface, lose their energy via inelastic collisions and some of them are eventually backscattered to the spectrometer, 50 resulting in spectra that are typically characterised by a number of structures attributed to both collective (plasmons) and single-electron excitations and can be directly benchmarked against the available experimental data.…”

Section: Introductionmentioning

confidence: 99%