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Related papers: Defect contrast with 4D-STEM: Understanding crysta…

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In this work, non-destructive virtual diagnostics are applied to retrieve the electron beam time of arrival and energy in a relativistic ultrafast electron diffraction (UED) beamline using independently-measured machine parameters. This…

Defects in semiconductor crystals can have significant detrimental effects on their performance as radiation detectors. Defects cause charge trapping and recombination, leading to lower signal amplitudes and poor energy resolution. We have…

Instrumentation and Detectors · Physics 2024-09-30 M. Väänänen , M. Kalliokoski , R. Turpeinen , M. Bezak , P. Luukka , A. Karjalainen , A. Karadzhinova-Ferrer

The 4D scanning transmission electron microscopy (STEM) method has enabled mapping of the structure and functionality of solids on the atomic scale, yielding information-rich data sets containing information on the interatomic electric and…

Computational Physics · Physics 2020-09-24 Mark P. Oxley , Maxim Ziatdinov , Ondrej Dyck , Andrew R. Lupini , Rama Vasudevan , Sergei V. Kalinin

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely…

Materials Science · Physics 2022-04-13 Yiqun Wang , Xiao-Jie Zhang , Fei Xia , Elsa A. Olivetti , Ram Seshadri , James M. Rondinelli

In differential phase contrast scanning transmission electron microscopy (DPC-STEM), variability in dynamical diffraction resulting from changes in sample thickness and local crystal orientation (due to sample bending) can produce contrast…

Materials Science · Physics 2020-02-06 T. Mawson , A. Nakamura , T. C. Petersen , N. Shibata , H. Sasaki , D. M. Paganin , M. J. Morgan , S. D. Findlay

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…

Controlling defects in semiconductor processes is important for maintaining yield, improving production cost, and preventing time-dependent critical component failures. Electron beam-based imaging has been used as a tool to survey wafers in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Chien-Fu , Huang , Katherine Sieg , Leonid Karlinksy , Nash Flores , Rebekah Sheraw , Xin Zhang

The accuracy of the information that can be extracted from electron diffraction patterns is often limited by the presence of optical distortions. Existing distortion characterization techniques typically require knowledge of the reciprocal…

Accurately determining the crystallographic structure of a material, organic or inorganic, is a critical primary step in material development and analysis. The most common practices involve analysis of diffraction patterns produced in…

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here we…

Scientists use imaging to identify objects of interest and infer properties of these objects. The locations of these objects are often measured with error, which when ignored leads to biased parameter estimates and inflated variance.…

2D materials offer an ideal platform to study the strain fields induced by individual atomic defects, yet challenges associated with radiation damage have so-far limited electron microscopy methods to probe these atomic-scale strain fields.…

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…

This work is addressing the problem of defect anomaly detection based on a clean reference image. Specifically, we focus on SEM semiconductor defects in addition to several natural image anomalies. There are well-known methods to create a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Nati Ofir , Yotam Ben Shoshan , Ran Badanes , Boris Sherman

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

The analysis of defects and defect dynamics in crystalline materials is important for fundamental science and for a wide range of applied engineering. With increasing system size the analysis of molecular-dynamics simulation data becomes…

Computational Physics · Physics 2020-04-20 U. von Toussaint , F. J. Dominguez-Gutierrez , M. Compostella , M. Rampp

Scanning transmission electron microscopy (STEM) has been extensively used for imaging complex materials down to atomic resolution. The most commonly employed STEM modality, annular dark-field imaging, produces easily-interpretable…

The exceptional electronic, optical and chemical properties of two-dimensional materials strongly depend on the 3D atomic structure and crystal defects. Using Re-doped MoS2 as a model, here we develop scanning atomic electron tomography…

Diffuse optical imaging (DOI) offers valuable insights into scattering mediums, but the quest for high-resolution imaging often requires dense sampling strategies, leading to higher imaging errors and lengthy acquisition times. This work…

Optics · Physics 2025-04-07 Ben Wiesel , Shlomi Arnon

The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a…

Biomolecules · Quantitative Biology 2015-10-12 Tomas Ekeberg , Stefan Engblom , Jing Liu
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