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Electron backscatter diffraction (EBSD) is a technique used to measure crystallographic features in the scanning electron microscope. The technique is highly automated and readily accessible in many laboratories. EBSD pattern indexing is…

Computational Physics · Physics 2018-07-18 Thomas Benjamin Britton , Vivian Tong , Jim Hickey , Alex Foden , Angus Wilkinson

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

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

Electron back-scatter diffraction (EBSD) has traditionally relied upon methods such as the Hough transform and dictionary Indexing to interpret diffraction patterns and extract crystallographic orientation. However, these methods encounter…

Materials Science · Physics 2025-11-04 Meghraj Prajapat , Alankar Alankar

Fine-grained sparsity promises higher parametric capacity without proportional per-token compute, but often suffers from training instability, load balancing, and communication overhead. We introduce STEM (Scaling Transformers with…

Polarization in ferroelectric domains arises from atomic-scale structural variations that govern macroscopic functionalities. The interfaces between these domains known as domain walls host distinct physical responses, making their…

Space charge layers (SCLs) at grain boundaries play a crucial role in modulating local electric fields and influencing the functional properties of materials, such as oxygen vacancy migration and ionic conductivity in oxide ceramics.…

Atomic-resolution scanning transmission electron microscopy (STEM) characterization requires precise tilting of the specimen to high symmetric zone axis, which is usually processed in reciprocal space by following the diffraction patterns.…

Materials Science · Physics 2024-06-04 Jiake Wei , Zhangze Xu , Wenjie Shen , Bin Feng , Ryo Ishikawa , Naoya Shibata , Yuichi Ikuhara , Xuedong Bai

Diffraction analysis in four dimensional scanning transmission electron microscopy now enables the mapping of local structures including symmetry, strain, and polarization of materials. However, measuring the distribution of these…

Materials Science · Physics 2024-06-19 Tim B. Eldred , Jacob G. Smith , Wenpei Gao

Materials characterization using electron backscatter diffraction (EBSD) requires indexing the orientation of the measured region from Kikuchi patterns. The quality of Kikuchi patterns can degrade due to pattern overlaps arising from two or…

Materials Science · Physics 2024-06-07 Ashish Chauniyal , Pascal Thome , Markus Stricker

We measured the local composition and thickness of SiO2-based glass material from diffraction. By using four dimensional scanning transmission electron microscopy (4D-STEM), we obtained diffraction at each scanning point. Comparing the…

Materials Science · Physics 2020-05-20 K. Nakazawa , K. Mitsuishi , K. Shibata , S. Amma , T. Mizoguchi

Electron backscatter diffraction (EBSD) has developed over the last few decades into a valuable crystallographic characterisation method for a wide range of sample types. Despite these advances, issues such as the complexity of sample…

Image and Video Processing · Electrical Eng. & Systems 2024-07-17 Zoë Broad , Alex W. Robinson , Jack Wells , Daniel Nicholls , Amirafshar Moshtaghpour , Angus I. Kirkland , Nigel D. Browning

Atomic resolution imaging in transmission electron microscopy (TEM) and scanning TEM (STEM) of light elements in electron-transparent materials has long been a challenge. Biomolecular materials, for example, are rapidly altered when…

Instrumentation and Detectors · Physics 2018-12-05 Fehmi S. Yasin , Tyler R. Harvey , Jordan J. Chess , Jordan S. Pierce , Colin Ophus , Peter Ercius , Benjamin J. McMorran

Scanning transmission electron microscopy (STEM) has a broad range of applications in materials characterization, including real-space imaging, spectroscopy, and diffraction, at length scales from the micron to sub-{\AA}ngstr\"om. The…

Instrumentation and Detectors · Physics 2022-06-07 Bryan D Esser , Joanne Etheridge

Latest diffusion models have shown promising results in category-level 6D object pose estimation by modeling the conditional pose distribution with depth image input. The existing methods, however, suffer from slow convergence during…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Seunghyun Lee , Tae-Kyun Kim

Here we show that compressive sensing allow 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and low fluence. The methodology needed to achieve these results compared to conventional 4-D…

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to…

Electron backscatter diffraction is a widely used technique for nano- to micro-scale analysis of crystal structure and orientation. Backscatter patterns produced by an alloy solid solution matrix and its ordered superlattice exhibit only…

Materials Science · Physics 2020-10-13 Thomas P McAuliffe , David Dye , T Ben Britton

Fine-grained image classification remains challenging due to the large intra-class variance and small inter-class variance. Since the subtle visual differences are only in local regions of discriminative parts among subcategories, part…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Runsheng Zhang , jian zhang , Yaping Huang , Qi Zou

Diffusion magnetic resonance imaging datasets suffer from low Signal-to-Noise Ratio, especially at high b-values. Acquiring data at high b-values contains relevant information and is now of great interest for microstructural and…

Computer Vision and Pattern Recognition · Computer Science 2016-06-27 Samuel St-Jean , Pierrick Coupé , Maxime Descoteaux