Lithium-ion secondary batteries are indispensable electrochemical devices in modern society, and further performance improvement is required toward a low-carbon society. There are many interfaces inside and between the materials that compose the lithium-ion secondary battery, and lithium ions move through these interfaces for charging and discharging. In order to improve the battery performance, it is important to design and control these interface structures. A combination of scanning transmission electron microscopy and electron energy loss spectroscopy is an effective method to understand the interface structure and degradation behavior of lithium-ion secondary batteries. In this report, I present a combination of these two methods for the structural analysis of the interface inside the cathode material olivine-type lithium iron phosphate and the interface between the sulfide-based solid electrolyte and the layered cathode material in all-solid-state batteries.

Sulfide-based solid electrolytes (SEs) are among the most promising candidates for realizing all-solid-state lithium-ion batteries due to their high ionic conductivity. However, their low moisture stability is a major drawback. Air exposure causes a significant decrease in their ionic conductivity, together with a toxic H₂S gas generation, mainly from the reaction between the SEs and water molecules in the air. This is a major barrier to all-solid-state cells fabrication process cost. To develop sulfide-based SEs with high moisture durability, it is necessary to clarify their deterioration mechanism during air exposure. As a promising SE for sulfide-based all-solid-state cells, in this study, we focused on the argyrodite Li_7-xPS_6-xCl_x exhibiting high ionic conductivity. Transmission electron microscope (TEM) observations were employed in investigating the microstructure and morphology of Li_7-xPS_6-xCl_x to reveal its deterioration mechanism during air exposure. In addition, we also conducted the in situ monitoring of argyrodite under air-flow environment using a vacuum transfer TEM holder with a gas-flow system.

Scanning electrochemical microscopy (SECM) is one of scanning probe microscopic (SPM) techniques, which can analyze and quantify microscopic electrochemical reactions. Among SECM, scanning electrochemical cell microscopy (SECCM) can confines the area under sub-micrometer scale via an electrochemical cell droplet which is created by a glass pipette-based probe filled with electrolyte and a reference electrode. Here, we introduce some localized electrochemical analysis by SECCM such as redox, electrocatalytic, lithium-ion (de)intercalation, and photo-catalytic activities.

As a method for visualizing the chemical distribution of materials using SEM, electron spectroscopy using a scanning Auger electron spectrometer (AES) has been investigated. In addition to the commonly utilized Li KLL Auger peak measurement, it is also possible to detect Li in compounds by using reflection electron energy loss spectroscopy (REELS). On the other hand, the measurement throughput for data analysis and elemental distribution evaluation is still an issue in AES. Therefore, we have developed the acquisition of data cubes for simplification of measurement and sophistication of data processing. In this study, we will introduce those efforts.

As a representative organization, in cooperation with 11 implementing organizations nationwide, we built a fine structure analysis platform for the Ministry of Education, Culture, Sports, Science, and Technology’s Nanotechnology Platform Project, and were able to successfully support cutting-edge nano-characterization research for 10 years. The number of cutting-edge measurement support tasks for researchers and engineers not only in academia but also in the industry has increased dramatically compared to previous projects. The number of users not only from Japan but also from overseas researchers has increased, and it has grown steadily as an international shared facility for nano-characterization. As the visibility in Japan and overseas increased, exchanges between staff members with overseas shared facilities also progressed, and we were able to contribute to the human resource development of many researchers and engineers. The abbreviation “NanoPla” became a brand, and it was recognized both domestically and internationally as the National Research Infrastructure (NRI), which is the foundation for research and development in the fields of nanotechnology and materials. It became clear that high-level results can be produced very efficiently when the user’s cutting-edge themes and issues match the supporter’s equipment and technology.

Analysis of biological images by electron microscopy (EM) requires the segmentation which annotates target structures. The segmentation had been done manually for a long time, since simple-image processing cannot be applied for the segmentation. But the manual segmentation cannot correspond to rapidly increasing images as well as three dimensional images. Recently, deep learning (DL) allowing complex image processing has been used for the segmentation, which reduces human efforts for the segmentation significantly. For further improvement of efficiency, next subjects, reducing human efforts to prepare training dataset for DL and to correct DL results are emerging. In this commentary, I will try to explain rapidly evolving segmentation of EM images using DL as well as efforts corresponding to the next subjects. In addition, information to start the segmentation using DL and application of DL beyond the segmentation are described.

The information content of optical images is an effective figure of merit for solving the problem of optimizing the image performance of an electron microscope. This paper describes a method for accurately estimating the beam convergent angle (optimal focusing angle) that maximizes the information content of the SEM image (optical image) affected by aberration and diffraction. The method determines the optimum convergent angle of the beam, its allowable range, and attainable resolution for ultra-high resolution SEM for any combination of spherical aberration coefficient, chromatic aberration coefficient, and acceleration voltage. This method also clarifies the phenomenon that the optimum convergent angle and the attainable resolution vary with the signal-to-noise ratio of the image.

Plasma FIB system with μA order ion beam current achieves hundreds-micrometers volume 3D analysis of battery materials. Furthermore, PFIB-SEM system with TOF-SIMS realized light element analysis by milling to create cross-section and stage movement afterward. The latest PFIB system is available to change specie gas to Xenon/Argon/Oxygen/Nitrogen each can mill specimen’s surface efficiently or generate second ion to be detected by TOF-SIMS method.