High-speed atomic force microscopy (HS-AFM), established in the early 2000s, has become a pivotal tool for visualizing the conformational dynamics of single protein molecules in solution. Historically, its primary application was the visualization of surface topography, aiding in exploring protein’s function mechanisms. However, similar to traditional AFM, HS-AFM has recently broadened its utility to encompass more than just structural analysis. It now includes the quantitative measurement of mechanical properties and the manipulation of molecules using external forces. This review discusses the recent advancements in the various methods for assessing mechanical properties, ranging from semi-quantitative techniques to precise force measurements and the corresponding responses of samples. This review highlights the structural manipulation and quantitative mechanical measurements of proteins and supramolecular fibers as examples, demonstrating the enhanced capabilities of HS-AFM through the integration of quantifiable force application and superior spatiotemporal resolution.

Scanning transmission electron microscopy (STEM) is more suitable for visualizing the internal structure of thick samples compared to conventional transmission electron microscopy whose resolution is limited by the chromatic aberration of the imaging lens system, and it is often used for three-dimensional structural analysis using electron tomography. However, STEM image quality is seriously degraded by noise and artifacts, especially when pursuing rapid imaging on the order of milliseconds per frame or faster. In this paper, we report that deep learning-based denoising is effective for rapid STEM imaging, and can be applicable to rapid STEM tomography. By acquiring tilt-series images in just 5 seconds, the three-dimensional dislocation arrangement in a thick (300 nm) steel sample can be determined with sufficient accuracy. This method has enormous potential on improving in-situ or operando observation of samples in relatively thick media including liquid cells.

Electron microscopes equipped with pulsed electron guns can capture phenomena faster than the shutter speed of a camera. However, the temporal resolution is sub-picoseconds, which is often insufficient to capture the very fast motion of atoms and electrons. Recently, a novel technique, namely, the optical modulation of electron beams, has been developed in order to achieve attosecond temporal resolution, and has attracted much attention. In this paper, we review the background of the transmission electron microscopy using optically-modulated electron beams, the principle of the optical modulation, and the applications that have been reported so far. Electron microscopy with attosecond resolution should become a powerful tool for visualizing the microscopic motion of electrons and electromagnetic fields of light in and around nanomaterials, which has been difficult to achieve so far.

A scanning electron microscope (SEM) equipped with a high-brightness monochromatic photocathode was constructed to visualize high-speed phenomena occurring in localized regions on a sample surface. This photocathode has high brightness comparable to that of a Schottky-type emitter, and narrower energy width than that of a cold field emission emitter. In addition, this high-brightness NEA photocathode can generate a pulsed electron beams with a minimum duration of picoseconds. Using this prototype SEM, we performed a proof-of-principle experiment of time-resolved measurement by applying pump-probe method. A sample voltage was synchronized with an excitation light source of the photocathode. A sinusoidal periodic voltage with a period of 30 ns (frequency 33 MHz) and a voltage amplitude of 0 to +5 V was applied to a sample, and SEM images were obtained by controlling a timing of a 150-picosecond pulse electron beam. A time variation of surface potential of an AlTiC sample, which exhibits characteristic image contrast in a secondary electron image, was measured as an SEM image, and it was found that both nanosecond temporal resolution and nanometer spatial resolution are possible. (171 words)

Advancements in gene expression analysis techniques have led to a transition in the focus of analysis from tissue and organ levels to the single-cell level. This shift enables the elucidation of the heterogeneity of cellular phenotypes within tissues and the identification of rare cellular populations based on gene expression patterns in individual cells. However, in single-cell transcriptome analysis, cells are isolated from tissues, resulting in the loss of spatial information about cellular positions within the tissue. To address this, spatial transcriptomics analysis, which preserves the spatial information of cells, has been developed and is rapidly gaining popularity. Spatial transcriptomics analysis is advancing rapidly, with new analytical methods being reported continuously. Therefore, this paper aims to classify established analysis methods based on principles, explain representative analysis methods, and discuss the selection of analysis methods according to the experimental objectives, as well as outline the general flow of data analysis. (148 words)

Electron Energy-Loss Near Edge Structure (ELNES), a spectroscopy method that obtains absorption spectra from inelastic scattering of electron beams due to core electron excitation, provides valuable information about the local structure and chemical bonding characteristics. The interpretation of ELNES often relies on comparison with reference spectra, which can be costly and challenging to obtain, especially for unstable structures or unknown materials. These challenges have been partially addressed by recent advancements in theoretical calculation methods and improvements in computational performance, which have made it possible to simulate spectra to some extent. However, there are remaining challenges in terms of calculation costs and reproduction of experimental spectra. With the development of observation methods such as in-situ observation and spectrum imaging, and the acceleration of measurements, the dimension and quantity of data obtained are increasing, making the acquisition and analysis of reference spectra a bottleneck in the utilization of ELNES. The review provides an overview of the application of machine learning to ELNES which has been studied against this background, including the use of machine learning for spectrum prediction and automatic quantitative analysis, alongside improvements in reference spectrum calculations and database construction, and discusses future prospects.

Cryo-electron tomography enables us to acquire the three-dimensional structure of quick-frozen specimens within a few nanometers spatial resolution. However, because of the limited penetration of the electron beam, cryo-EM observation of cellular specimens is restricted to only the periphery. To enable cryo-EM to access deep structures such as the nucleus, cryo-FIB-SEM has been developed for micromachining of the vitreous cellular specimens. The operation of cryo-FIB-SEM for the lamella preparation is a little bit complicated due to the multiple settings and handling. Therefore, the development of an automated lamella preparation scheme is required for stable lamellae preparation in daily experiments, especially for beginners. In this paper, we will introduce our fully automated lamella milling scheme using the cryo-FIB-SEM.

This paper presents an overview of a original TEM heat transport measurement method that combines a nanothermocouple with electron beam heating. In addition to the conventional steady-state method of heat transport measurement, a new method has been developed to measure thermal diffusivity based on the phase analysis of the thermal waves in a TEM specimen by pulsing the heating source with a pulsed electron beam using an electrostatic dose modulator.