B. Da

Validity of the semi-classical approach for calculation of the surface excitation parameter

The problem of surface plasmon excitation by moving charges has been elaborated by several different approaches, mainly based on dielectric response theory within either semi-classical or quantum mechanical frameworks. In this work, a comparison of the surface excitation effect between two different frameworks is made by calculation of the differential inverse inelastic mean free path (DIIMFP) and a Monte Carlo simulation of reflection electron energy loss spectroscopy (REELS) spectra. A semi-classical modeling of the interaction between electrons and a solid surface is based on analyzing the work done by moving electrons; the stopping power and inelastic cross section are derived with the induced potential. On the other hand, a quantum mechanical approach is based on derivation of the complex inhomogeneous self-energy of the electrons. The numerical calculation shows that the semi-classical model presents almost the same values of DIIMFP as by the quantum model except at the glancing condition. The simulation of REELS spectra for Ag and SiO(2) as well as a comparison with experimental spectra also confirms that a good agreement with the spectral shape is found among the two simulation results and the experimental data.

A Monte Carlo study of reflection electron energy loss spectroscopy spectrum of a carbon contaminated surface

It has been experimentally found that the carbon surface contamination influences strongly the spectrum signals in reflection electron energy loss spectroscopy (REELS) especially at low primary electron energy. However, there is still little theoretical work dealing with the carbon contamination effect in REELS. Such a work is required to predict REELS spectrum for layered structural sample, providing an understanding of the experimental phenomena observed. In this study, we present a numerical calculation result on the spatially varying differential inelastic mean free path for a sample made of a carbon contamination layer of varied thickness on a SrTiO3 substrate. A Monte Carlo simulation model for electron interaction with a layered structural sample is built by combining this inelastic scattering cross-section with the Motts cross-section for electron elastic scattering. The simulation results have clearly shown that the contribution of the electron energy loss from carbon surface contamination incre...

Extended reverse Monte Carlo method for extracting optical constants of thin Ni film from reflection electron energy-loss spectroscopy

An extended reverse Monte Carlo (RMC) method for obtaining optical constants of ultrathin films and solids is presented. Our results show that this method works very well in extracting some exquisite information from experimentally measured reflection electron energy loss spectroscopy (REELS) spectra. The energy loss function (ELF) of 100 nm nickel film in a relatively larger energy loss range of 0-200 eV has been obtained, which agrees well with other computational data. Employing this ELF, individual contributions to REELS intensity due to surface and bulk plasmon excitations are quantitatively separated for further study.

Quantum monte carlo simulation for atomic resolution SEM/STEM image

School of Nuclear Science and Technology, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, P.R. China Direct imaging of individual atoms with various electron signals has always been the most important challenge in electron microscopy. It has been reported only recently that an atomic resolution secondary electron (SE) image can be achieved in an aberration corrected scanning transmission electron microscope (STEM) by Zhu

Influence of surface topography on elastically backscattered electrons

A Monte Carlo simulation, taking into account of the detailed surface roughness of a realistic solid sample, has been performed to study the surface topography influence on elastic peak intensity. To describe quantitatively the surface topography effect, here we introduce surface roughness parameter (SRP) according to the ratio of elastic peak intensities between a rough surface and an ideal planar surface. Simulation results for Al sample have shown that SRP varies with surface roughness particularly at large incidence/emission angles.