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Advancements in fast electron detectors have enabled the statistically significant sampling of crystal structures on the nanometre scale by means of Scanning Electron Nanobeam Diffraction (SEND). Characterisation of structural similarity…

Materials Science · Physics 2022-07-28 Andy Bridger , William I. F. David , Thomas J. Wood , Mohsen Danaie , Keith T. Butler

Atomic resolution imaging is key to understanding thin film growth and how a particular set of conditions influences properties. Whilst such imaging in the scanning transmission electron microscope (STEM) has had transformative impact in…

Scanning transmission electron microscopy (STEM) is the most widespread adopted tool for atomic scale characterization of two-dimensional (2D) materials. Many 2D materials remain susceptible to electron beam damage, despite the standardized…

Materials Science · Physics 2021-08-11 Sytze de Graaf , Majid Ahmadi , Ivan Lazić , Eric G. T. Bosch , Bart J. Kooi

Despite the widespread use of Scanning Transmission Electron Microscopy (STEM) for observing the structure of materials at the atomic scale, a detailed understanding of some relevant electron beam damage mechanisms is limited. Recent…

Scanning Transmission Electron Microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In…

Instrumentation and Detectors · Physics 2019-01-15 Xin Li , Ondrej Dyck , Sergei V. Kalinin , Stephen Jesse

The simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret their contrast and extract specimen features. This is especially true for high-resolution phase-contrast imaging of…

Materials Science · Physics 2021-03-30 Jacob Madsen , Timothy J. Pennycook , Toma Susi

We propose a template matching method for the detection of 2D image objects that are characterized by orientation patterns. Our method is based on data representations via orientation scores, which are functions on the space of positions…

Computer Vision and Pattern Recognition · Computer Science 2017-03-10 Erik J. Bekkers , Marco Loog , Bart M. ter Haar Romeny , Remco Duits

We propose a new scanning transmission electron microscopy (STEM) technique that can realize the three-dimensional (3D) characterization of vacancies, lighter and heavier dopants with high precision. Using multislice STEM imaging and…

Materials Science · Physics 2016-07-12 Jared M. Johnson , Soohyun Im , Jinwoo Hwang

4D-STEM-based orientation and phase mapping has enabled rapid microstructure quantification that can be directly combined with standard TEM- and STEM-based imaging modes. Typically, orientation mapping is coupled with beam precession (i.e.…

Materials Science · Physics 2026-04-01 Yichen Yang , Olivier Pierron , Josh Kacher , David Rowenhorst

Techniques for training artificial neural networks (ANNs) and convolutional neural networks (CNNs) using simulated dynamical electron diffraction patterns are described. The premise is based on the following facts. First, given a suitable…

Mesoscale and Nanoscale Physics · Physics 2021-03-08 Renliang Yuan , Jiong Zhang , Lingfeng He , Jian-Min Zuo

Contrast transfer mechanisms for electron scattering have been extensively studied in transmission electron microscopy. Here we revisit H. Rose's generalized contrast formalism from scattering theory to understand where information is…

Optics · Physics 2025-10-28 Desheng Ma , Guanxing Li , David A Muller , Steven E Zeltmann

Layered materials (LMs) are at the centre of an ever increasing research effort due to their potential use in a variety of applications. The presence of imperfections, such as bi- or multilayer areas, holes, grain boundaries, isotropic and…

Automated experimentation with real time data analysis in scanning transmission electron microscopy (STEM) often require end-to-end framework. The four-dimensional scanning transmission electron microscopy (4D-STEM) with high-throughput…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Mingyu Liu , Zian Mao , Zhu Liu , Haoran Zhang , Jintao Guo , Xiaoya He , Xi Huang , Shufen Chu , Chun Cheng , Jun Ding , Yujun Xie

Properties of crystalline materials are closely linked to microstructure arising from the spatial arrangement, orientation, and phase of nanocrystals. Rapid characterization of crystalline microstructure can accelerate the identification of…

Materials Science · Physics 2026-02-16 Kwanghwi Je , Ellis R. Kennedy , Sungin Kim , Yao Yang , Erik H. Thiede

In four-dimensional scanning transmission electron microscopy (4D STEM) a focused beam is scanned over a specimen and a diffraction pattern is recorded at each position using a pixelated detector. During the experiment, it must be ensured…

Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of…

We demonstrate a multi-beam scanning transmission electron microscopy (STEM) imaging that integrates down-sampling with super-resolution image reconstruction via a compressive sensing framework. A custom condenser aperture with six randomly…

Instrumentation and Detectors · Physics 2026-03-19 Akira Yasuhara , Takumi Sannomiya , Ryoichi Horisaki

Electron backscatter diffraction (EBSD) is a well-established method of characterisation for crystalline materials. This technique can rapidly acquire and index diffraction patterns to provide phase and orientation information about the…

Materials Science · Physics 2019-09-04 Alexander Foden , David Collins , Angus Wilkinson , Thomas Benjamin Britton

Scanning transmission electron microscopy (STEM) is an indispensable tool for atomic-resolution structural analysis for a wide range of materials. The conventional analysis of STEM images is an extensive hands-on process, which limits…

Automated experiments in 4D Scanning Transmission Electron Microscopy are implemented for rapid discovery of local structures, symmetry-breaking distortions, and internal electric and magnetic fields in complex materials. Deep kernel…

Materials Science · Physics 2022-04-22 Kevin M. Roccapriore , Ondrej Dyck , Mark P. Oxley , Maxim Ziatdinov , Sergei V. Kalinin