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Related papers: NLSTEM: Non-local denoising for enhanced 4D-STEM p…

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We introduce a denoising method for four-dimensional scanning transmission electron microscopy (4D-STEM) that relies on processing local, scan position-independent electron event-sparse data stacks, called event-sparse stack denoising. This…

Medical Physics · Physics 2025-12-12 Gregory Nordahl , Rebekka Klemmt , Espen Drath Bøjesen

The association of scanning transmission electron microscopy (STEM) and the detection of a diffraction pattern at each probe position (so-called 4D-STEM) represents one of the most promising approaches to analyze structural properties of…

Applied Physics · Physics 2023-01-26 Leonardo Corrêa , Eduardo Ortega , Arturo Ponce , Mônica Cotta , Daniel Ugarte

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as…

The technique known as 4D-STEM has recently emerged as a powerful tool for the local characterization of crystalline structures in materials, such as cathode materials for Li-ion batteries or perovskite materials for photovoltaics. However,…

The recent development of electron sensitive and pixelated detectors has attracted the use of four-dimensional scanning transmission electron microscopy (4D-STEM). Here, we present a precession electron diffraction assisted 4D-STEM…

Instrumentation and Detectors · Physics 2021-10-04 Jiwon Jeong , Niels Cautaerts , Gerhard Dehm , Christian H. Liebscher

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D scanning transmission electron microscopy, or 4D-STEM) combined with high-speed direct…

High-throughput analysis of multidimensional transmission electron microscopy (TEM) datasets remains a significant challenge, limiting the broader impact on strategic materials research. Conventional workflows typically involve sequential,…

Materials Science · Physics 2025-07-16 Arda Genc , Ravit Silverstein

Momentum-resolved scanning transmission electron microscopy (MRSTEM) is a powerful phase-contrast technique that can map lateral magnetic and electric fields ranging from the micrometer to the subatomic scale. Resolving fields ranging from…

Development in lattice strain mapping using four-dimensional scanning transmission electron microscopy (4D-STEM) method now offers improved precision and feasibility. However, automatic and accurate diffraction analysis is still challenging…

Materials Science · Physics 2022-01-04 Sihan Wang , Tim Eldred , Jacob Smith , Wenpei Gao

Four-dimensional scanning transmission electron microscopy (4D-STEM) provides rich, atomic-scale insights into materials structures. However, extracting specific physical properties - such as polarization directions essential for…

A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass (COM) of the diffraction pattern at one probe position at a time, it is able to…

Materials Science · Physics 2021-12-15 Chu-Ping Yu , Thomas Friedrich , Daen Jannis , Sandra Van Aert , Johan Verbeeck

Orientation mapping is a widely used technique for revealing the microstructure of a polycrystalline sample. The crystalline orientation at each point in the sample is determined by analysis of the diffraction pattern, a process known as…

Mathematical Physics · Physics 2017-10-11 Peter Mahler Larsen , Søren Schmidt

Precession of a converged beam during acquisition of a 4D-STEM dataset improves strain, orientation, and phase mapping accuracy by averaging over continuous angles of illumination. Precession experiments usually rely on integrated systems,…

Instrumentation and Detectors · Physics 2025-10-20 Stephanie M. Ribet , Rohan Dhall , Colin Ophus , Karen C. Bustillo

4D-STEM, in which the 2D diffraction plane is captured for each 2D scan position in the scanning transmission electron microscope (STEM) using a pixelated detector, is complementing and increasingly replacing existing imaging approaches.…

Instrumentation and Detectors · Physics 2022-07-27 Colum M. O'Leary , Benedikt Haas , Christoph T. Koch , Peter D. Nellist , Lewys Jones

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

Accurate grain orientation mapping is essential for understanding and optimizing the performance of polycrystalline materials, particularly in energy-related applications. Lithium nickel oxide (LiNiO$_{2}$) is a promising cathode material…

Disordered Systems and Neural Networks · Physics 2025-11-26 Sebastian Wissel , Jonas Scheunert , Aaron Dextre , Shamail Ahmed , Andreas Bayer , Kerstin Volz , Bai-Xiang Xu

Four-dimensional scanning transmission electron microscopy (4D-STEM) of local atomic diffraction patterns is emerging as a powerful technique for probing intricate details of atomic structure and atomic electric fields. However, efficient…

Image and Video Processing · Electrical Eng. & Systems 2019-01-15 Xin Li , Ondrej E. Dyck , Mark P. Oxley , Andrew R. Lupini , Leland McInnes , John Healy , Stephen Jesse , Sergei V. Kalinin

Material properties strongly depend on the nature and concentration of defects. Characterizing these features may require nano- to atomic-scale resolution to establish structure-property relationships. 4D-STEM, a technique where diffraction…

Materials Science · Physics 2023-05-03 Stephanie M. Ribet , Colin Ophus , Roberto dos Reis , Vinayak P. Dravid

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

This study presents a novel integration of unsupervised learning and decision-making strategies for the advanced analysis of 4D-STEM datasets, with a focus on non-negative matrix factorization (NMF) as the primary clustering method. Our…

Machine Learning · Computer Science 2025-11-18 Junhao Cao , Nicolas Folastre , Gozde Oney , Edgar Rauch , Stavros Nicolopoulos , Partha Pratim Das , Arnaud Demortière
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