Monte Carlo softwares are widely used to understand the capabilities of electron microscopes. To study more realistic applications with complex samples, 3D Monte Carlo softwares are needed. In this paper, the development of the 3D version of CASINO is presented. The software feature a graphical user interface, an efficient (in relation to simulation time and memory use) 3D simulation model, accurate physic models for electron microscopy applications, and it is available freely to the scientific community at this website: www.gel.usherbrooke.ca/casino/index.html. It can be used to model backscattered, secondary, and transmitted electron signals as well as absorbed energy. The software features like scan points and shot noise allow the simulation and study of realistic experimental conditions. This software has an improved energy range for scanning electron microscopy and scanning transmission electron microscopy applications.

Scanning transmission electron microscopy (STEM) was used to image gold nanoparticles on top of and below saline water layers of several micrometers thickness. The smallest gold nanoparticles studied had diameters of 1.4 nm and were visible for a liquid thickness of up to 3.3 µm. The imaging of gold nanoparticles below several micrometers of liquid was limited by broadening of the electron probe caused by scattering of the electron beam in the liquid. The experimental data corresponded to analytical models of the resolution and of the electron probe broadening, as function of the liquid thickness. The results were also compared with Monte Carlo simulations of the STEM imaging on modeled specimens of similar geometry and composition as used for the experiments. Applications of STEM imaging in liquid can be found in cell biology, e.g., to study tagged proteins in whole eukaryotic cells in liquid, and in materials science to study the interaction of solid:liquid interfaces at the nanoscale.

Li metal batteries suffer from dendrite formation which causes short circuit of the battery. Therefore, it is important to understand the chemical composition and growth mechanism of dendrites that limit battery efficiency and cycle life. In this study, in situ scanning electron microscopy was employed to monitor the cycling behavior of all-solid Li metal batteries with LiFePO4 cathodes. Chemical analyses of the dendrites were conducted using a windowless energy dispersive spectroscopy detector, which showed that the dendrites are not metallic lithium as universally recognized. Our results revealed the carbide nature of the dendrites with a hollow morphology and hardness greater than that of pure lithium. These carbide-based dendrites were able to perforate through the polymer, which was confirmed by milling the polymer using focused ion beam. It was also shown that applying pressure on the battery can suppress growth of the dendrites.

Summary A charge‐coupled device camera of an electron backscattered diffraction system in a scanning electron microscope was positioned below a thin specimen and transmission Kikuchi patterns were collected. Contrary to electron backscattered diffraction, transmission electron forward scatter diffraction provides phase identification and orientation mapping at the nanoscale. The minimum Pd particle size for which a Kikuchi diffraction pattern was detected and indexed reliably was 5.6 nm. An orientation mapping resolution of 5 nm was measured at 30 kV. The resolution obtained with transmission electron forward scatter diffraction was of the same order of magnitude than that reported in electron nanodiffraction in the transmission electron microscope. An energy dispersive spectrometer X‐ray map and a transmission electron forward scatter diffraction orientation map were acquired simultaneously. The high‐resolution chemical, phase and orientation maps provided at once information on the chemical form, orientation and coherency of precipitates in an aluminium–lithium 2099 alloy.

A new Monte Carlo program, Win X-ray, is presented that predicts X-ray spectra measured with an energy dispersive spectrometer (EDS) attached to a scanning electron microscope (SEM) operating between 10 and 40 keV. All the underlying equations of the Monte Carlo simulation model are included. By simulating X-ray spectra, it is possible to establish the optimum conditions to perform a specific analysis as well as establish detection limits or explore possible peak overlaps. Examples of simulations are also presented to demonstrate the utility of this new program. Although this article concentrates on the simulation of spectra obtained from what are considered conventional thick samples routinely explored by conventional microanalysis techniques, its real power will be in future refinements to address the analysis of sample classifications that include rough surfaces, fine structures, thin films, and inclined surfaces because many of these can be best characterized by Monte Carlo methods. The first step, however, is to develop, refine, and validate a viable Monte Carlo program for simulating spectra from conventional samples.