Simulating STEM Imaging of Nanoparticles in Micrometers-Thick Substrates

Abstract

The scanning transmission electron microscopy (STEM) can be used to image biological and other soft materials with nanometer resolution on nanoparticles in micrometers-thick specimens [1]. For the imaging of thick samples, the spatial resolution is not limited by the optics of STEM, as is the case for ultrathin amorphous substrates, but the interaction of the electron beam with the specimen plays a major role, and the resolution is limited by noise or by beam broadening. It is crucial to have knowledge of the electron beam-specimen interactions, so that the imaging settings can be optimized for maximal resolution, especially when imaging radiation-sensitive samples. Knowledge of the beam broadening can potentially be used to enhance the resolution of 3D datasets by using deconvolution procedures. A precise way to study the interaction between an electron beam and a specific specimen geometry and composition is via the use of Monte Carlo simulations. We present a STEM version of the CASINO Monte Carlo software [2]. The CASINO Monte Carlo software has been modified to include the simulation of STEM with the annular dark-field (ADF) detector [3], exhibiting atomic number (Z) contrast. The electron trajectory calculation is based on to the previous version of CASINO [4]. The electron beam model included the Poisson noise and a conical shape of the electron source, such that realistic STEM images were obtained with these simulations. By using the 3D geometry of the sample and the 3D programming of the electron beam shape and focal point position, various STEM imaging sequences were simulated, including focal series. The electron scattering physical models used in the previous version of CASINO were extended from the energy range of the SEM to energies of up to 300 keV as needed for STEM imaging. For the imaging of radiation sensitive samples, such as biological materials or polymers, it is important to optimize the achievable resolution in terms of the maximal electron dose. This optimization requires the calculation of the resolution and signal-to-noise level obtained for a specific sample and STEM imaging settings. The Monte Carlo simulation of STEM imaging presents a precise method to conduct such calculations. As an example, we have simulated line scans (one-dimensional images) for a sample consisting of gold nanoparticles placed on the top surface-with respect to the electron beam propagation direction-of a 1 mm thick carbon support substrate (see Fig. 1A). Fig. 1C shows an increased noise level compared to Fig. 1B as expected, as the number of electrons has been reduced by a factor of 50. Nanoparticles were assumed to be visible in the noise of the background when the Rose criterion [5] was satisfied, i.e., when SNR 5. In Fig. 1B,C, the dashed horizontal line indicates the signal level for SNR = 5. The smallest nanoparticle (d = 1 nm) is just visible in Fig. 1B, while it vanished in the noise in Fig. 1C. These results demonstrate that the CASINO software can be used to simulate the achievable SNR for specific sa...

Observation of Undamped 3D Brownian Motion of Nanoparticles Using Liquid‐Cell Scanning Transmission Electron Microscopy

“…To show that a different z position within the liquid‐cell can indeed lead to a blurring of the particle as shown in Figure 6 (and Figure S8, Supporting Information), we used the Monte Carlo software CASINO [ 43–45 ] to simulate ADF‐STEM images of the gold NPs as well. Figure shows the simulated ADF‐STEM images of a 77 nm gold NP at various heights z within the liquid‐cell.…”

“…Monte Carlo Simulations Using CASINO: To simulate ADF-STEM images the CASINO software was used. [43][44][45] The used physics model for the total and partial cross sections in the simulation software was that of an empirical analytical fit to the Mott cross sections by Browning et al [61] The specific parameters of the sample and the electron probe were taken to be as close to the experimental parameters as possible. For the 350 nm titania particle in GC, a layer of 2.3 m µ of glycerol carbonate was put between two 50 nm thick Si 3 N 4 windows.…”

“…To investigate whether the particle also move in the direction parallel to the STEM probe, we simulated ADF-STEM images using the experimental conditions for a 350 nm titania particle at various heights in the liquid-cell, using the CASINO software. [43][44][45] Figure 3 shows the simulated ADF-STEM images for a titania particle at the top, middle and bottom of the liquidcell. No obvious difference is observed, because at 350 nm size the particle is too large to move out of focus or be significantly influenced by beam broadening effects.…”

“…the Monte Carlo software CASINO [43][44][45] to simulate ADF-STEM images of the gold NPs as well. Figure 7 shows the simulated ADF-STEM images of a 77 nm gold NP at various heights z within the liquid-cell.…”

Tunability of Interactions between the Core and Shell in Rattle-Type Particles Studied with Liquid-Cell Electron Microscopy

“…Therefore, we are first required to simulate ADF-STEM images for a static particle. For this purpose, we simulated ADF-STEM images using the CASINO software (version 3.3.0.4). − The physics model used for the total and partial cross sections in the simulation software was that of an empirical analytical fit to the Mott cross sections by Browning et al The specific parameters of the sample and the electron probe were taken to be as close to the experimental parameters as possible. However, we chose to use 256 by 256 pixels and twice the pixel size as in the experiments (which had 512 by 512 pixels) in order to reduce the computation time.…”