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The appearance of direct electron detectors marked a new era for electron diffraction. Their high sensitivity and low noise opens the possibility to extend electron diffraction from transmission electron microscopes (TEM) to lower energies…

Applied Physics · Physics 2025-02-18 Nikita Denisov , Andrey Orekhov , Johan Verbeeck

We develop an unsupervised machine learning algorithm for the automated discovery and identification of traveling waves in spatio-temporal systems governed by partial differential equations (PDEs). Our method uses sparse regression and…

Computational Physics · Physics 2020-05-20 Ariana Mendible , Steven L. Brunton , Aleksandr Y. Aravkin , Wes Lowrie , J. Nathan Kutz

Interface structures in complex oxides remain one of the active areas of condensed matter physics research, largely enabled by recent advances in scanning transmission electron microscopy (STEM). Yet the nature of the STEM contrast in which…

Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect analysis on the sub-nanometer scale is enabled by…

Materials Science · Physics 2021-06-03 Nik Dennler , Antonio Foncubierta-Rodriguez , Titus Neupert , Marilyne Sousa

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

Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by…

Applied Physics · Physics 2024-06-26 Aileen Luo , Tao Zhou , Martin V. Holt , Andrej Singer , Mathew J. Cherukara

Symmetry detection and discrimination are of fundamental meaning in science, technology, and engineering. This paper introduces reflection invariants and defines the directional moment to detect symmetry for shape analysis and object…

Computer Vision and Pattern Recognition · Computer Science 2017-06-02 Erbo Li , Hua Li

Given a dataset of images containing different objects with different features such as shape, size, rotation, and x-y position; and a Variational Autoencoder (VAE); creating a disentangled encoding of these features in the hidden space…

Computer Vision and Pattern Recognition · Computer Science 2022-08-10 Mohammad Haghir Ebrahimabadi

High quality scanning transmission electron microscopy (STEM) data acquisition and analysis has become increasingly important due to the commercial demand for investigating the properties of complex materials such as battery cathodes;…

For the diffraction of an incident plane electromagnetic wave by a slotted metallic film, the previous analytical calculation for a single slot [Technical Phys. 50, 1076 (2005)] is generalized into a model for an arbitrary linear array of…

Computational Physics · Physics 2011-06-21 L. David Wellems , Danhong Huang

Strain engineering enables the direct modification of the atomic bonding and is currently an active area of research aimed at improving the electrocatalytic activity. However, directly measuring the lattice strain of individual catalyst…

Materials Science · Physics 2020-04-28 Debangshu Mukherjee , Jocelyn T. L. Gamler , Sara E. Skrabalak , Raymond R. Unocic

Atomic resolution imaging is key to understanding thin film growth and how a particular set of conditions influences properties. Whilst such imaging in the scanning transmission electron microscope (STEM) has had transformative impact in…

Strain governs not only the mechanical response of materials but also their electronic, optical, and catalytic properties. For this reason, the measurement of the 3D strain field is crucial for a detailed understanding and for further…

Materials Science · Physics 2025-09-19 Laura Niermann , Tore Niermann , Chengyu Song , Colin Ophus

Understanding structure at the atomic scale is fundamental for the development of materials with improved properties. Compared to other probes providing atomic resolution, electrons offer the strongest interaction in combination with…

High-throughput phenotypic screens generate vast microscopy image datasets that push the limits of generative models due to their large dimensionality. Despite the growing popularity of general-purpose models trained on natural images for…

Quantitative Methods · Quantitative Biology 2025-10-24 Télio Cropsal , Rocío Mercado

Strong multiple scattering of the probe in scanning transmission electron microscopy (STEM) means image simulations are usually required for quantitative interpretation and analysis of elemental maps produced by electron energy-loss…

Materials Science · Physics 2019-12-25 Hamish G. Brown , Jim Ciston , Colin Ophus

Deviations from the perfect atomic arrangements in crystals play an important role in affecting their properties. Similarly, diffusion of such deviations is behind many microstructural changes in solids. However, observation of point defect…

Materials Science · Physics 2014-07-28 Jani Kotakoski , Clemens Mangler , Jannik C. Meyer

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

We propose efficient algorithms based on a band-limited version of 2D synchrosqueezed transforms to extract mesoscopic and microscopic information from atomic crystal images. The methods analyze atomic crystal images as an assemblage of…

Numerical Analysis · Mathematics 2015-09-22 Haizhao Yang , Jianfeng Lu , Lexing Ying

Variational Autoencoders (VAE) are widely used for dimensionality reduction of large-scale tabular and image datasets, under the assumption of independence between data observations. In practice, however, datasets are often correlated, with…

Machine Learning · Statistics 2024-12-25 Giora Simchoni , Saharon Rosset