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Environmental transmission electron microscopy (E-TEM) enables direct observation of nanoscale chemical processes crucial for catalysis and materials design. However, the high-energy electron probe can dramatically alter reaction pathways…

Deep learning has emerged as a technique of choice for rapid feature extraction across imaging disciplines, allowing rapid conversion of the data streams to spatial or spatiotemporal arrays of features of interest. However, applications of…

Data Analysis, Statistics and Probability · Physics 2021-01-25 Ayana Ghosh , Bobby G. Sumpter , Ondrej Dyck , Sergei V. Kalinin , Maxim Ziatdinov

Aberration-corrected Scanning Transmission Electron Microscopy (STEM) has become an essential tool in understanding materials at the atomic scale. However, tuning the aberration corrector to produce a sub-{\AA}ngstr\"om probe is a complex…

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…

We propose a new scanning transmission electron microscopy (STEM) technique that can realize the three-dimensional (3D) characterization of vacancies, lighter and heavier dopants with high precision. Using multislice STEM imaging and…

Materials Science · Physics 2016-07-12 Jared M. Johnson , Soohyun Im , Jinwoo Hwang

Four-dimensional scanning transmission electron microscopy (4D-STEM) is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly…

Applications · Statistics 2019-08-27 Xin Li , Ondrej Dyck , Stephen Jesse , Andrew R. Lupini , Sergei V. Kalinin , Mark P. Oxley

The fault diagnosis of rolling bearings is a critical technique to realize predictive maintenance for mechanical condition monitoring. In real industrial systems, the main challenges for the fault diagnosis of rolling bearings pertain to…

Machine Learning · Computer Science 2022-04-27 Zhenhua Tan , Jingyu Ning , Kai Peng , Zhenche Xia , Danke Wu

This article addresses extraction of physically meaningful information from STEM EELS and EDX spectrum-images using methods of Multivariate Statistical Analysis. The problem is interpreted in terms of data distribution in a…

Data Analysis, Statistics and Probability · Physics 2021-05-24 Pavel Potapov , Axel Lubk

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.…

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

We introduce a machine learning approach to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). Our method is…

Ultrafast electron diffraction (UED) instruments typically operate at kHz or lower repetition rates and rely on indirect detection of electrons. However, these experiments encounter limitations because they are required to use electron…

Chemical Physics · Physics 2024-08-06 Fernando Rodriguez Diaz , Mark Mero , Kasra Amini

The tracking method based on the extreme learning machine (ELM) is efficient and effective. ELM randomly generates input weights and biases in the hidden layer, and then calculates and computes the output weights by reducing the iterative…

Machine Learning · Computer Science 2018-07-27 Jing Zhang , Huibing Wang , Yonggong Ren

Understanding and controlling the chemical states both in the bulk and at the interfaces of complex oxide thin films is essential for engineering a wide range of electronic, optical, and magnetic functionalities, which arise through…

Materials Science · Physics 2025-12-30 Harish Kumarasubramanian , Jayakanth Ravichandran

Isotope labeling is a fundamental staple for the study of cellular metabolism and protein function. The conventional techniques that allow resolution and identification of isotopically-labeled biomarkers, such as mass spectrometry and…

Electron energy-loss spectroscopy (EELS) and cathodoluminescence (CL) are widely used experimental techniques for characterization of nanoparticles. The discrete dipole approximation (DDA) is a numerically exact method for simulating…

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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…

Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…

Materials Science · Physics 2021-10-06 Jian-Min Zuo , Renliang Yuan , Yu-Tsun Shao , Haw-Wen Hsiao , Saran Pidaparthy , Yang Hu , Qun Yang , Jiong Zhang

This paper addresses the task of modeling Deformable Linear Objects (DLOs), such as ropes and cables, during dynamic motion over long time horizons. This task presents significant challenges due to the complex dynamics of DLOs. To address…

Robotics · Computer Science 2025-03-10 Yizhou Chen , Yiting Zhang , Zachary Brei , Tiancheng Zhang , Yuzhen Chen , Julie Wu , Ram Vasudevan

Materials with tailored quantum properties can be engineered from atomic scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here we…