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This paper presents a novel approach for denoising Electron Backscatter Diffraction (EBSD) patterns using diffusion models. We propose a two-stage training process with a UNet-based architecture, incorporating an auxiliary regression head…

Image and Video Processing · Electrical Eng. & Systems 2025-09-01 Nikolay Falaleev , Nikolai Orlov

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli…

The robust approach for real-time analysis of the scanning transmission electron microscopy (STEM) data streams, based on the ensemble learning and iterative training (ELIT) of deep convolutional neural networks, is implemented on an…

Disordered Systems and Neural Networks · Physics 2022-07-27 Kevin M. Roccapriore , Matthew G. Boebinger , Ondrej Dyck , Ayana Ghosh , Raymond R. Unocic , Sergei V. Kalinin , Maxim Ziatdinov

Recent advances in scanning transmission electron and scanning tunneling microscopies allow researchers to measure materials structural and electronic properties, such as atomic displacements and charge density modulations, at an Angstrom…

The recently developed information-theoretic approach to crystallographic symmetry classifications and quantifications in two dimensions (2D) from digital transmission electron and scanning probe microscope images is adapted for the…

Materials Science · Physics 2022-08-10 Peter Moeck , Lukas von Koch

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 microscopy is a powerful tool for visualizing the shapes of sub-nanometer objects. However, contrast is not in proportional to density distribution, and therefore achieving a quantitative understanding of specimens is not…

Instrumentation and Detectors · Physics 2020-05-14 Masato Tomita , Yukinori Nagatani , Kazuyoshi Murata , Atsushi Momose

Recently, deep learning technology has been successfully introduced into Automatic Modulation Recognition (AMR) tasks. However, the success of deep learning is all attributed to the training on large-scale datasets. Such a large amount of…

Machine Learning · Computer Science 2024-08-07 Dongwei Xu , Jiajun Chen , Yao Lu , Tianhao Xia , Qi Xuan , Wei Wang , Yun Lin , Xiaoniu Yang

Space-time adaptive processing (STAP) is an effective tool for detecting a moving target in the airborne radar system. Due to the fast-changing clutter scenario and/or non side-looking configuration, the stationarity of the training data is…

Information Theory · Computer Science 2010-08-26 Ke Sun , Huadong Meng , Yongliang Wang , Xiqin Wang

Ptychography has become prominent at synchrotron facilities worldwide for characterizing biological and material specimens' topological structures and properties at the nanometer or atomic scale, due to its lens - less, highly quantitative…

Image and Video Processing · Electrical Eng. & Systems 2025-01-28 Tao Liu , Bingyang Wang , JiangTao Zhao , Maik Kahnt , Fucai Zhang

Differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM) maps projected electric fields through the phase sensitivity of segmented low-angle detectors. Although typically applied to atomic-resolution…

Mechanical properties in crystals are strongly correlated to the arrangement of 1D line defects, termed dislocations. Recently, Dark field X-ray Microscopy (DFXM) has emerged as a new tool to image and interpret dislocations within crystals…

Materials Science · Physics 2026-01-13 Pin-Hua Huang , Ryan Coffee , Leora Dresselhaus-Marais

Training large AI models typically requires large-scale datasets in the machine learning process, making training and parameter-tuning process both time-consuming and costly. Some researchers address this problem by carefully synthesizing a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jiyuan Shen , Wenzhuo Yang , Kwok-Yan Lam

Strain engineering has proven to be vital for germanium-based photonics, in particular light emission. However, applying a large permanent biaxial strain to germanium has been a challenge. We present a simple, CMOS-compatible technique to…

We present annular dark field scanning transmission electron microscopy (ADF-STEM) as an efficient, fast, and non-destructive nanoscale tool for monitoring solid-state phase transition. Using metal-insulator transition in vanadium dioxide…

We show that diffraction intensity into the First Order Laue Zone (FOLZ) of a crystal can have a strong azimuthal dependence, where this FOLZ ring appears solely because of unidirectional atom position modulation. Such a modulation was…

Materials Science · Physics 2023-10-03 Aurys Silinga , Christopher S. Allen , Juri Barthel , Colin Ophus , Ian MacLaren

Anomaly detection in complex, high-dimensional data, such as UAV sensor readings, is essential for operational safety but challenging for existing methods due to their limited sensitivity, scalability, and inability to capture intricate…

Machine Learning · Computer Science 2025-10-28 Mingze Gong , Juan Du , Jianbang You

Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be…

Materials Science · Physics 2021-10-05 Kevin M. Roccapriore , Nicole Creange , Maxim Ziatdinov , Sergei V. Kalinin

Score Distillation Sampling (SDS) is a recent but already widely popular method that relies on an image diffusion model to control optimization problems using text prompts. In this paper, we conduct an in-depth analysis of the SDS loss…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Thiemo Alldieck , Nikos Kolotouros , Cristian Sminchisescu

Accurate computational ptychographic phase reconstructions are enabled by fast direct-electron cameras with high dynamic ranges used for four-dimensional scanning transmission electron microscopy (4D-STEM). The availability of open software…

Materials Science · Physics 2025-05-01 Toma Susi