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Strain governs not only the mechanical response of materials but also their electronic, optical, and catalytic properties. For this reason, the measurement of the 3D strain field is crucial for a detailed understanding and for further…

Materials Science · Physics 2025-09-19 Laura Niermann , Tore Niermann , Chengyu Song , Colin Ophus

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…

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

The rigid-intensity-shift model of differential phase contrast scanning transmission electron microscopy (DPC-STEM) imaging assumes that the phase gradient imposed on the probe by the sample causes the diffraction pattern intensity to shift…

Instrumentation and Detectors · Physics 2018-04-25 L. Clark , H. G. Brown , D. M. Paganin , M. J. Morgan , T. Matsumoto , N. Shibata , T. C. Petersen , S. D. Findlay

Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent…

Stochastic microstructure reconstruction involves digital generation of microstructures that match key statistics and characteristics of a (set of) target microstructure(s). This process enables computational analyses on ensembles of…

Materials Science · Physics 2023-01-02 Anindya Bhaduri , Ashwini Gupta , Audrey Olivier , Lori Graham-Brady

Representation learning is a fundamental but challenging problem, especially when the distribution of data is unknown. We propose a new representation learning method, termed Structure Transfer Machine (STM), which enables feature learning…

Machine Learning · Computer Science 2019-08-06 Baochang Zhang , Lian Zhuo , Ze Wang , Jungong Han , Xiantong Zhen

The concept of compressive sensing was recently proposed to significantly reduce the electron dose in scanning transmission electron microscopy (STEM) while still maintaining the main features in the image. Here, an experimental setup based…

Instrumentation and Detectors · Physics 2016-03-23 Armand Béché , Bart Goris , Bert Freitag , Jo Verbeeck

Scanning transmission electron microscopy (STEM) is widely used tool for materials characterisation. However, being a scanned technique, STEM is susceptible to sample, stage or beam drift, manifesting as distortions within images or…

Instrumentation and Detectors · Physics 2026-04-23 Matthew Mosse , Jonathan J. P. Peters , Eoin Moynihan , James A. Gott , Ana M. Sanchez , Michele Conroy , Lewys Jones

In materials science, microstructures and their associated extrinsic properties are critical for engineering advanced structural and functional materials, yet their robust reconstruction and generation remain significant challenges. In this…

Materials Science · Physics 2024-10-01 Yixuan Zhang , Teng Long , Hongbin Zhang

Three-dimensional electron diffraction (3DED) is a powerful technique providing for crystal structure solutions of sub-micron sized crystals too small for structure determination via X-ray techniques. The entry requirement, however, of a…

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…

Ultrafast electron diffraction/microscopy technique enables us to investigate the nonequilibrium dynamics of crystal structures in the femtosecond-nanosecond time domain. However, the electron diffraction intensities are in general…

Materials Science · Physics 2024-07-10 Toshiya Shiratori , Jumpei Koga , Takahiro Shimojima , Kyoko Ishizaka , Asuka Nakamura

We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen…

Materials Science · Physics 2022-02-28 Thomas Friedrich , Chu-Ping Yu , Johan Verbeek , Timothy Pennycook , Sandra Van Aert

Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The…

Disordered Systems and Neural Networks · Physics 2021-06-24 Maxim Ziatdinov , Chun Yin Wong , Sergei V. Kalinin

We apply recent advances in machine learning and computer vision to a central problem in materials informatics: The statistical representation of microstructural images. We use activations in a pre-trained convolutional neural network to…

Computational Physics · Physics 2018-12-04 Nicholas Lubbers , Turab Lookman , Kipton Barros

Image downscaling is one of the key operations in recent display technology and visualization tools. By this process, the dimension of an image is reduced, aiming to preserve structural integrity and visual fidelity. In this paper, we…

Image and Video Processing · Electrical Eng. & Systems 2025-10-28 G B Kevin Arjun , Suvrojit Mitra , Sanjay Ghosh

Aberration-corrected scanning transmission electron microscopes (STEM) provide sub-angstrom lateral resolution; however, the large convergence angle greatly reduces the depth of field. For microscopes with a small depth of field,…

Materials Science · Physics 2011-12-15 Robert Hovden , Huolin L. Xin , David A. Muller

Epitaxial growth has become a promising route to achieve highly crystalline continuous two-dimensional layers. However, high-quality layer production with expected electrical properties is still challenging due to the defects induced by the…

Diffusion models have recently emerged as a powerful technique in image generation, especially for image super-resolution tasks. While 2D diffusion models significantly enhance the resolution of individual images, existing diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Bohao Chen , Yanchao Zhang , Yanan Lv , Hua Han , Xi Chen