Charging effect induced by electron beam irradiation: a review

Abstract

Charging effect frequently occurs when characterizing nonconductive materials using electrons as probes and/or signals and can impede the acquisition of useful information about the material under investigation. It is not adequate to investigate it merely by experiments, but theoretical investigations, for which the Monte Carlo method is a suitable tool, are also necessary. In this paper we review Monte Carlo simulations and selected experiments, intending to provide general insight into the charging effects induced by electron beam irradiation. We will introduce categories of the charging effect, the theoretical framework that is adopted in Monte Carlo modeling of the charging effect and present some typical simulation results. At last, with the knowledge on charging effect imparted by the above contents, we will discuss the measures that can be used for minimizing it.

A theoretical characterization method for non-spherical core–shell nanoparticles by XPS

“…Monte Carlo methods have been extensively employed over recent decades to simulate the interactions between electrons and solids for signal analysis in electron microscopy and electron spectroscopy. 31–36 Simulation results were found to be in good agreement with experiments. 37–42 By combining Mott's cross section for describing the electron elastic scattering and the dielectric function for the electron inelastic scattering, we have developed and applied classic trajectory Monte Carlo (CTMC) simulation models to SEM, 43–52 AES 53–56 and reflected electron energy loss spectroscopy 57–64 with different simulation codes.…”

Transparent and Reusable Nanostencil Lithography for Organic–Inorganic Hybrid Perovskite Nanodevices

“…Notably, 50‐nm‐thick gold (Au) is deposited on the PET film to avoid the charging effect during FIB etching. [ 36 ] Figure S1 (Supporting Information) shows patterned features with and without Au deposition using the same FIB etching conditions. It can be observed that, it is practically impossible to etch the PET film without Au deposition by FIB because charging effect induces severe beam drift.…”

Establishment and validation of an electron inelastic mean free path database for narrow bandgap inorganic compounds with a machine learning approach

“…The IMFP describes the mean distance that an electron travels through a solid before losing energy and plays a critical role in experimental observation facilities, such as reflection electron energy-loss spectroscopy (REELS), [5][6][7][8][9][10][11][12][13] X-ray photoelectron spectroscopy (XPS), [14][15][16] and Auger electron spectroscopy (AES). 14,[17][18][19] Monte Carlo simulations [20][21][22][23][24][25][26] have shown how incident electrons scatter in materials, together with other important parameters used in surface science, such as the backscattering factor, 27,28 mean escape depth, 29 and surface excitation parameters. [30][31][32] Their importance in applications makes it essential to calculate electron IMFPs at electron energies above 50 eV.…”