Monte Carlo Strategies

Monte Carlo is one of the most powerful theoretical methods for evaluating the physical quantities related to the interaction of electrons with a solid target. A Monte Carlo simulation can be considered as an idealized experiment. The simulation does not investigate the fundamental principles of the interaction. It is necessary to have a good knowledge of them – in particular of the energy loss and angular deflection phenomena – to produce a good simulation. All the cross-sections and mean free paths have to be previously accurately calculated: they are then used in the Monte Carlo code in order to obtain the macroscopic characteristics of the interaction processes by simulating a large number of single particle trajectories and then averaging them. Due to the recent evolution in computer calculation capability, we are now able to obtain statistically significant results in very short calculation times.

[1]  H. Fröhlich Electrons in lattice fields , 1954 .

[2]  R. H. Ritchie Plasma Losses by Fast Electrons in Thin Films , 1957 .

[3]  J. F. Perkins Monte Carlo Calculation of Transport of Fast Electrons , 1962 .

[4]  Edward L. Garwin,et al.  Electron‐Phonon Interaction in Alkali Halides. I. The Transport of Secondary Electrons with Energies between 0.25 and 7.5 eV , 1969 .

[5]  S. Horiguchi,et al.  New model of electron free path in multiple layers for Monte Carlo simulation , 1981 .

[6]  H. Bichsel Inelastic electronic collision cross sections for Monte Carlo calculations , 1990 .

[7]  Z. Ding,et al.  Monte Carlo modelling of electron-solid interactions , 1992 .

[8]  Dapor Monte Carlo simulation of backscattered electrons and energy from thick targets and surface films. , 1992, Physical review. B, Condensed matter.

[9]  S. Santangelo,et al.  Electron scattering in microstructure processes , 1992 .

[10]  J. Ganachaud,et al.  Theoretical study of the secondary electron emission of insulating targets , 1995 .

[11]  Yung-fu Chen,et al.  Electron differential inverse mean free path for surface electron spectroscopy , 1996 .

[12]  Monte Carlo simulation study of reflection-electron-energy-loss-spectroscopy spectrum , 2000 .

[13]  C. Powell,et al.  Information depth for elastic-peak electron spectroscopy , 2004 .

[14]  C. Tung,et al.  Influence of the direction of motion on the inelastic interaction between electrons and solid surfaces , 2005 .

[15]  D. Liljequist A study of errors in trajectory simulation with relevance for 0.2 - 50 eV electrons in liquid water , 2008 .

[16]  Monte Carlo simulation of energy loss of electrons backscattered from solid surfaces , 2008 .

[17]  M. Novák On the role of the effects of interference and elastic scattering in reflection electron energy loss spectra: simulations using different approaches , 2009 .

[18]  H. Yoshikawa,et al.  Angular and Energy Dependences of Reflection Electron Energy Loss Spectra of Si , 2009 .

[19]  M. Dapor A Monte Carlo investigation of secondary electron emission from solid targets: Spherical symmetry versus momentum conservation within the classical binary collision model , 2009, 0903.4805.

[20]  H. Yoshikawa,et al.  Measurement of optical constants of Si and SiO2 from reflection electron energy loss spectra using factor analysis method , 2010 .

[21]  Kostas Kostarelos,et al.  Simple model of bulk and surface excitation effects to inelastic scattering in low-energy electron beam irradiation of multi-walled carbon nanotubes , 2011 .

[22]  S. Mao,et al.  A New Analytical Method in Surface Electron Spectroscopy: Reverse Monte Carlo Method , 2012 .

[23]  M. Dapor,et al.  Energy loss of electrons backscattered from solids: measured and calculated spectra for Al and Si , 2012 .

[24]  W. Werner,et al.  Surface excitations in electron spectroscopy. Part I: dielectric formalism and Monte Carlo algorithm , 2012, Surface and interface analysis : SIA.

[25]  D. Liljequist Contribution from inelastic scattering to the validity of trajectory methods , 2013 .

[26]  Z. M. Zhang,et al.  A reverse Monte Carlo method for deriving optical constants of solids from reflection electron energy-loss spectroscopy spectra , 2013 .

[27]  Zeshu Zhang,et al.  Method for a quick estimation of energy dependent reflection electron energy loss spectroscopy spectra for Al and Si , 2013 .

[28]  M. Dapor,et al.  Momentum transfer dependence of reflection electron energy loss spectra: theory and experiment , 2014 .