A New Analytical Method in Surface Electron Spectroscopy: Reverse Monte Carlo Method

Abstract

A reverse Monte Carlo (RMC) method is developed in this work to study the energy-loss process of signal electrons in surface electron spectroscopy. This method derives the effective energy-loss function (EELF) from a measured reflection electron energy loss spectroscopy (REELS) spectrum by an iterative Monte Carlo (MC) simulation procedure other than deconvolution procedure, in accordance with the complicated electron transport process. The method combines the Markov chain Monte Carlo (MCMC) sampling (i.e. Metropolis important sampling) of oscillator parameters with a usual MC simulation of electron interaction with solids, which acts as a single step of MCMC sampling. To examine the reliability of this method, we have performed a test which leads to derive the same EELF with different trial inputs of initial oscillator parameters. Calculation results show that EELF can be pretty well derived by the RMC method even without a proper choice of initial trial parameters. As an example the EELFs for Ag at different electron energies are derived from the measured REELS spectra by this RMS method. [DOI: 10.1380/ejssnt.2012.441]