In this paper, we have developed a Monte Carlo (MC) simulation method for calculation of scanning electron microscopy (SEM) images of rough surfaces. The roughness structure is constructed in a finite element triangulated mesh by using a Gaussian function to describe the distribution of amplitude of the random rough peaks. Further spatial subdividing can accelerate the calculation and improves MC simulation efficiency. The MC model is based on the using of the Mott cross section for description of the electron elastic scattering and the using of the full Penn algorithm in a dielectric functional approach to the electron inelastic scattering. This simulation relates directly a defined rough surface structure modeling described by exact values of roughness parameters to the contrast observed in a SEM image, enabling the investigation of the influence of line edge roughness to the critical dimension (CD) metrology of a metal-oxide-semiconductor device by SEM. Example calculation of line images with sidewall roughness demonstrates that the present MC simulation method is useful for CD metrology of nanostructures by CD-SEM and, especially, for the linewidth measurement in the integrated circuit industry.

Monte Carlo simulation methods for the study of electron beam interaction with solids have been mostly concerned with specimens of simple geometry. In this article, we propose a simulation algorithm for treating arbitrary complex structures in a real sample. The method is based on a finite element triangular mesh modeling of sample geometry and a space subdivision for accelerating simulation. Simulation of secondary electron image in scanning electron microscopy has been performed for gold particles on a carbon substrate. Comparison of the simulation result with an experiment image confirms that this method is effective to model complex morphology of a real sample.

Based on a Monte Carlo simulation method, an improved calculation of the backscattering factor in quantitative analysis by Auger electron spectroscopy has been performed by integrating several aspects of recent progresses in the related fields. The calculation used a general definition of backscattering factor, more accurate ionization cross section, up-to-date Monte Carlo model of electron inelastic scattering, and a large number of electron trajectories to ensure less statistical error. The results reveal several noticeable properties of backscattering factor, i.e., its slow variation with primary energy at higher overvoltage ratios, and dependence on the geometrical configuration of a detector. However, only for large emission angles of Auger signals a considerable angular dependence of backscattering factor is found. Specifically a calculation is carried out for detection in the solid angles of a cylindrical mirror analyzer. This backscattering factor can be less than unity for very low primary energies closing to ionization energy and/or for large incident angles. The physical cause has been detailed and analyzed.

Simulation of contrast formation in Auger electron imaging of surfaces is helpful for analyzing scanning Auger microscopy/microanalysis (SAM) images. In this work, we have extended our previous Monte Carlo model and the simulation method for calculation of scanning electron microscopy (SEM) images to SAM images of complex structures. The essentials of the simulation method are as follows. (1) We use a constructive solid geometry modeling for a sample geometry, which is complex in elemental distribution, as well as in topographical configuration and a ray-tracing technique in the calculation procedure of electron flight steps that across the different element zones. The combination of the basic objects filled with elements, alloys, or compounds enables the simulation to a variety of sample geometries. (2) Sampled Auger signal electrons with a characteristic energy are generated in the simulation following an inner-shell ionization event, whose description is based on the Castani’s inner-shell ionization cross section. This paper discusses in detail the features of simulated SAM images and of line scans for structured samples, i.e., the objects embedded in a matrix, under various experimental conditions (object size, location depth, beam energy, and the incident angle). Several effects are predicted and explained, such as the contrast reversion for nanoparticles in sizes of 10–60 nm, the contrast enhancement for particles made of different elements and wholly embedded in a matrix, and the artifact contrast due to nearby objects containing different elements. The simulated SAM images are also compared with the simulated SEM images of secondary electrons and of backscattered electrons. The results indicate that the Monte Carlo simulation can play an important role in quantitative SAM mapping.