In-situ heating-and-electron tomography for materials research: from 3D (in-situ 2D) to 4D (in-situ 3D).

In-situ observation has expanded the application of transmission electron microscopy (TEM) and has made a significant contribution to materials research and development for energy, biomedical, quantum, etc. Recent technological developments related to in-situ TEM have empowered the incorporation of three-dimensional observation, which was previously considered incompatible. In this review article, we take up heating as the most commonly used external stimulus for in-situ TEM observation and overview recent in-situ TEM studies.

electron tomography for the thermally activated solid reaction of anaerobic nanoparticles.

The nanoscale characterization of thermally activated solid reactions plays a pivotal role in products manufactured by nanotechnology. Recently, observation in transmission electron microscopy combined with electron tomography, namely four-dimensional observation for heat treatment of nanomaterials, has attracted great interest. However, because most nanomaterials are highly reactive, , oxidation during transfer and electron beam irradiation would likely cause fatal artefacts; it is challenging to perform the artifact-free four-dimensional observation.

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy.

Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM's high affinity with various analytical options into account. As is well known, STEM's image acquisition time needs to be further shortened to capture a targeted phenomenon in real-time as STEM's current temporal resolution is far below the conventional TEM's. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation.

Five-second STEM dislocation tomography for 300 nm thick specimen assisted by deep-learning-based noise filtering.

Scanning transmission electron microscopy (STEM) is suitable for visualizing the inside of a relatively thick specimen than the conventional transmission electron microscopy, whose resolution is limited by the chromatic aberration of image forming lenses, and thus, the STEM mode has been employed frequently for computed electron tomography based three-dimensional (3D) structural characterization and combined with analytical methods such as annular dark field imaging or spectroscopies. However, the image quality of STEM is severely suffered by noise or artifacts especially when rapid imaging, in the order of millisecond per frame or faster, is pursued. Here we demonstrate a deep-learning-assisted rapid STEM tomography, which visualizes 3D dislocation arrangement only within five-second acquisition of all the tilt-series images even in a 300 nm thick steel specimen.