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Scanning transmission electron microscopy (STEM) is an indispensable tool for atomic-resolution structural analysis for a wide range of materials. The conventional analysis of STEM images is an extensive hands-on process, which limits…

Electron tomography offers important three-dimensional (3D) structural information which cannot be observed by two-dimensional imaging. By combining annular dark field scanning transmission electron microscopy (ADF-STEM) with aberration…

Materials Science · Physics 2023-06-29 Juhyeok Lee , Moosung Lee , YongKeun Park , Colin Ophus , Yongsoo Yang

Three-dimensional electron diffraction (3D ED) has emerged as a powerful method for solving the structures of sub-micron-sized particles down to nanoparticles. However, it faces technical challenges when applied to beam-sensitive samples or…

Atomic resolution imaging in transmission electron microscopy (TEM) and scanning TEM (STEM) of light elements in electron-transparent materials has long been a challenge. Biomolecular materials, for example, are rapidly altered when…

Instrumentation and Detectors · Physics 2018-12-05 Fehmi S. Yasin , Tyler R. Harvey , Jordan J. Chess , Jordan S. Pierce , Colin Ophus , Peter Ercius , Benjamin J. McMorran

Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal…

Transmission electron microscopy (TEM) is a potent technique for the determination of three-dimensional atomic scale structure of samples in structural biology and materials science. In structural biology, three-dimensional structures of…

This work is concerned with the following fundamental question in scientific machine learning: Can deep-learning-based methods solve noise-free inverse problems to near-perfect accuracy? Positive evidence is provided for the first time,…

Image and Video Processing · Electrical Eng. & Systems 2022-07-13 Martin Genzel , Ingo Gühring , Jan Macdonald , Maximilian März

Automated experiments in 4D Scanning Transmission Electron Microscopy are implemented for rapid discovery of local structures, symmetry-breaking distortions, and internal electric and magnetic fields in complex materials. Deep kernel…

Materials Science · Physics 2022-04-22 Kevin M. Roccapriore , Ondrej Dyck , Mark P. Oxley , Maxim Ziatdinov , Sergei V. Kalinin

Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is…

Scanning transmission electron microscopy (STEM) has advanced rapidly in the last decade thanks to the ability to correct the major aberrations of the probe forming lens. Now atomic-sized beams are routine, even at accelerating voltages as…

Directed atomic fabrication using an aberration-corrected scanning transmission electron microscope (STEM) opens new pathways for atomic engineering of functional materials. In this approach, the electron beam is used to actively alter the…

The potential energy formulation and deep learning are merged to solve partial differential equations governing the deformation in hyperelastic and viscoelastic materials. The presented deep energy method (DEM) is self-contained and…

Machine Learning · Computer Science 2022-05-05 Diab W. Abueidda , Seid Koric , Rashid Abu Al-Rub , Corey M. Parrott , Kai A. James , Nahil A. Sobh

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

We report the development of deep learning coherent electron diffractive imaging at sub-angstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying…

Materials Science · Physics 2022-04-19 Dillan J. Chang , Colum M. O'Leary , Cong Su , Salman Kahn , Alex Zettl , Jim Ciston , Peter Ercius , Jianwei Miao

Crystalline defects, such as line-like dislocations, play an important role for the performance and reliability of many metallic devices. Their interaction and evolution still poses a multitude of open questions to materials science and…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Kishan Govind , Daniela Oliveros , Antonin Dlouhy , Marc Legros , Stefan Sandfeld

Curvilinear structures frequently appear in microscopy imaging as the object of interest. Crystallographic defects, i.e., dislocations, are one of the curvilinear structures that have been repeatedly investigated under transmission electron…

Image and Video Processing · Electrical Eng. & Systems 2021-10-19 Okan Altingövde , Anastasiia Mishchuk , Gulnaz Ganeeva , Emad Oveisi , Cecile Hebert , Pascal Fua

Deep-learning algorithms enable precise image recognition based on high-dimensional hierarchical image features. Here, we report the development and implementation of a deep-learning-based image segmentation algorithm in an autonomous…

Image and Video Processing · Electrical Eng. & Systems 2020-03-26 Satoru Masubuchi , Eisuke Watanabe , Yuta Seo , Shota Okazaki , Takao Sasagawa , Kenji Watanabe , Takashi Taniguchi , Tomoki Machida

There exist two groups of electron microscopy methods that are capable of providing three-dimensional (3D) structural information of an object, i.e., electron tomography and depth sectioning. Electron tomography is capable of resolving…

Materials Science · Physics 2024-05-28 Liangze Mao , Jizhe Cui , Rong Yu

Electron tomography is a technique used in both materials science and structural biology to image features well below optical resolution limit. In this work, we present a new algorithm for reconstructing the three-dimensional(3D)…

Signal Processing · Electrical Eng. & Systems 2018-07-12 David Ren , Michael Chen , Laura Waller , Colin Ophus

The interaction of a protein with its environment can be understood and controlled via its 3D structure. Experimental methods for protein structure determination, such as X-ray crystallography or cryogenic electron microscopy, shed light on…

Machine Learning · Computer Science 2025-04-24 Axel Levy , Eric R. Chan , Sara Fridovich-Keil , Frédéric Poitevin , Ellen D. Zhong , Gordon Wetzstein