Atomic-Resolution Topographic Imaging of Crystal Surfaces

Depth sectioning using environmental and atomic-resolution STEM

(Scanning) transmission electron microscopy (TEM) images of samples in gas and liquid media are acquired with an environmental cell (EC) via silicon nitride membranes. The ratio of sample signal against the background is a significant factor for resolution. Depth-sectioning scanning TEM (STEM) is a promising technique that enhances the signal for a sample embedded in a matrix. It can increase the resolution to the atomic level, thereby enabling EC-STEM applications in important areas. This review introduces depth-sectioning STEM and its applications to high-resolution EC-STEM imaging of samples in gases and in liquids.

Fast reconstruction of scanning transmission electron microscopy images using Markov random field model

In this study, we proposed a fast method of reconstruction for scanning transmission electron microscopy images. The proposed method is based on the Markov random field model and Bayesian inference, and we found that the method can reconstruct such images of sizes 512 × 512 and 264 × 240 in less than 200 ms and 100 ms, respectively. Furthermore, we showed that the method of reconstruction from multiple images without averaging them has better reconstruction performance than that from the averaged image.

The Atomic Observation of the Structural Change Process in Pt Networks in Air Using Environmental Cell Scanning Transmission Electron Microscopy

The structural change in Pt networks composed of multiple chain connections among grains was observed in air at 1 atm using atomic-resolution environmental cell scanning transmission electron microscopy. An aberration-corrected incident electron probe with a wide convergence angle made it possible to increase the depth resolution that contributes to enhancing the signal-to-noise ratio of Pt network samples in air in an environmental cell, resulting in the achievement of atomic-resolution imaging. The exposure of the Pt networks to gas molecules under Brownian motion, stimulated by electron beams in the air, increases the collision probability between gas molecules and Pt networks, and the Pt networks are more intensely stressed from all directions than in a situation without electron irradiation. By increasing the electron beam dose rate, the structural change of the Pt networks became significant. Dynamic observation on an atomic scale suggested that the structural change of the networks was not attributed to the surface atomic-diffusion-induced step motion but mainly caused by the movement and deformation of unstable grains and grain boundaries. The oxidized surface layers may be one of the factors hindering the surface atomic step motion, mitigating the change in the size of the grains and grain boundaries.

Extendible ghost imaging with high reconstruction quality in strong scattering medium

Ghost imaging (GI) possesses significant application prospects in scattering imaging, which is a classic example of underdetermined conversion problem in optical field. However, even under the framework of single-pixel imaging (SPI), a challenge remains unresolved, i.e., structured patterns may be damaged by scattering media in both the emissive and receiving optical paths. In this study, an extendible ghost imaging, a numerical reproduction of the qualitative process using deep learning (DL)-based GI is presented. First, we propose and experimentally verify a brief degradation-guided reconstruction (DR) approach with a neural network to demonstrate the degradation principle of scattering, including realistic dataset simulations and a new training structure in the form of a convolutional neural network (CNN). Then, a novel photon contribution model (PCM) with redundant parameters is proposed to generate intensity sequences from the forward direction through volumetric scattering media; the redundant parameters are constructed and relate to the special output configuration in a lightweight CNN with two branches, based on a reformulated atmospheric scattering model. The proposed scheme recovers the semantics of targets and suppresses the imaging noise in the strong scattering medium, and the obtained results are very satisfactory for applications to scattering media of more practical scenarios and are available for various scattering coefficients and work distances of an imaging prototype. After using DL methods in computational imaging, we conclude that strategies embedded in optics or broader physical factors can result in solutions with better effects for unanalyzable processes.

Atomic-Resolution STEM Image Denoising by Total Variation Regularization

Atomic-resolution electron microscopy imaging of solid state material is a powerful method for structural analysis. Scanning transmission electron microscopy (STEM) is one of the actively used techniques to directly observe atoms in materials. However, some materials are easily damaged by the electron beam irradiation, and only noisy images are available when we decrease the electron dose to avoid beam damages. Therefore, a denoising process is necessary for precise structural analysis in low-dose STEM. In this study, we propose total variation (TV) denoising algorithm to remove quantum noise in a STEM image. We defined an entropy of STEM image that corresponds to the image contrast to determine a hyperparameter and we found that there is a hyperparameter that maximize the entropy. We acquired atomic resolution STEM image of CaF2 viewed along the [001] direction, and executed TV denoising. The atomic columns of Ca and F are clearly visualized by the TV denoising, and atomic position of Ca and F are determined with the error of ± 1 pm and ± 4 pm, respectively.

Direct Observation of Atomistic Reaction Process between Pt Nanoparticles and TiO2 (110)

The catalytic activity and selectivity of heterogeneous catalysts are governed by atomic and electronic structures at the heterointerface between noble metal nanoparticles (NPs) and oxide substrates. In specific chemical reactions, it is well-known that the catalytic activity is strongly suppressed by annealing in a reducing atmosphere, so-called strong metal-support interaction (SMSI). However, it is still unclear the formation process and atomistic origin of the SMSI. By preparing well-defined platinum (Pt) NPs supported on atomically flat TiO₂ (110) substrate, we directly show the formation of chemically ordered Pt-Ti intermetallic NPs and impregnation of NPs into TiO₂ substrate at high temperatures by using atomic-resolution scanning transmission electron microscopy combined with electron energy-loss spectroscopy. Furthermore, we observed negative charge transfer from the Pt-Ti intermetallic NPs to the TiO₂ surface, which would strongly affect the catalytic activities.