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Instrumentation developments in electron energy-loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM) one decade ago paved the way for combining milli-electronvolt energy resolution in spectroscopy with…

Mesoscale and Nanoscale Physics · Physics 2024-10-15 Benedikt Haas , Christoph T. Koch , Peter Rez

Aberration-corrected optics have made electron microscopy at atomic-resolution a widespread and often essential tool for nanocharacterization. Image resolution is dominated by beam energy and the numerical aperture of the lens ({\alpha}),…

Atomic resolution electron microscopy, particularly high-angle annular dark-field scanning transmission electron microscopy, has become an essential tool for many scientific fields, when direct visualization of atomic arrangements and…

Nowadays, modern electron microscopes deliver images at atomic scale. The precise atomic structure encodes information about material properties. Thus, an important ingredient in the image analysis is to locate the centers of the atoms…

Computer Vision and Pattern Recognition · Computer Science 2017-09-13 Benjamin Berkels , Benedikt Wirth

Programmable electron-beam scanning offers new opportunities to improve dose efficiency and suppress scan-induced artifacts in scanning transmission electron microscopy. Here, we systematically benchmark the impact of non-raster…

Conventional nuclear magnetic resonance (NMR) spectroscopy relies on acquiring signal from a macroscopic ensemble of molecules to gain information about molecular structure and dynamics. Transferring this technique to nanoscale sample sizes…

Mesoscale and Nanoscale Physics · Physics 2019-02-06 Jeffrey Holzgrafe , Qiushi Gu , Jan Beitner , Dhiren Kara , Helena S. Knowles , Mete Atatüre

We report our detailed investigation of high-resolution imaging using secondary electrons (SE) with a subnanometer probe in an aberration-corrected transmission electron microscope, Hitachi HD2700C. This instrument also allows us to acquire…

Materials Science · Physics 2010-08-31 H. Inada , D. Su , R. F. Egerton , M. Konno , L. Wu , J. Ciston , J. Wall , Y. Zhu

Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) are well-established techniques that provide valuable information in a diverse set of disciplines but are currently limited to macroscopic sample volumes. Here we…

Electron tomography, as an important 3D imaging method, offers a powerful method to probe the 3D structure of materials from the nano- to the atomic-scale. However, as a grant challenge, radiation intolerance of the nanoscale samples and…

Materials Science · Physics 2020-03-30 Chunyang Wang , Guanglei Ding , Yitong Liu , Huolin L. Xin

Amplitude-modulation atomic force microscopy enables observation of fragile molecules at the nanometer scale. To shorten measurement times and capture dynamic molecules, increasing the frame rate is essential. Traditionally, maximum frame…

Applied Physics · Physics 2024-11-26 Kenichi Umeda , Noriyuki Kodera

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

The high beam current and sub-angstrom resolution of aberration-corrected scanning transmission electron microscopes has enabled electron energy loss spectroscopic (EELS) mapping with atomic resolution. These spectral maps are often…

Materials Science · Physics 2023-07-19 Paul Cueva , Robert Hovden , Julia A. Mundy , Huolin L. Xin , David A. Muller

The quantitative composition of metal alloy nanowires on InSb(001) semiconductor surface and gold nanostructures on germanium surface is determined by blind source separation (BSS) machine learning (ML) method using non negative matrix…

Mesoscale and Nanoscale Physics · Physics 2017-10-17 Benedykt R. Jany , Arkadiusz Janas , Franciszek Krok

Scanning Electron Microscopy (SEM) is critical in nanotechnology, materials science, and biological imaging due to its high spatial resolution and depth of focus. Signal-to-noise ratio (SNR) is an essential parameter in SEM because it…

Machine Learning · Computer Science 2025-10-10 K. S. Sim , I. Bukhori , D. C. Y. Ong , K. B. Gan

Scanning probe microscopy is one of the most versatile windows into the nanoworld, providing imaging access to a variety of sample properties, depending on the probe employed. Tunneling probes map electronic properties of samples, magnetic…

Mesoscale and Nanoscale Physics · Physics 2015-01-09 Thomas Häberle , Dominik Schmid-Lorch , Friedemann Reinhard , Jörg Wrachtrup

Density based representations of atomic environments that are invariant under Euclidean symmetries have become a widely used tool in the machine learning of interatomic potentials, broader data-driven atomistic modelling and the…

Chemical shifts and J-couplings are fundamental parameters in NMR spectroscopy as they provide structural information about molecules. Extracting these quantities from isotopes such as carbon or nitrogen results in reduced sensitivity due…

Quantum Physics · Physics 2025-06-23 P. Alsina-Bolívar , J. Casanova

When aiming for atomic resolution electron magnetic circular dichroism (EMCD) in STEM mode, the high convergence angle of the electron probe can lead to unforeseen artefacts and strong reductions of the signal to noise ratio (SNR) in the…

Low-loss electron energy loss spectroscopy (EELS) has emerged as a technique of choice for exploring the localization of plasmonic phenomena at the nanometer level, necessitating analysis of physical behaviors from 3D spectral data sets.…

Scanning Transmission Electron Microscopy (STEM) enables the observation of atomic arrangements at sub-angstrom resolution, allowing for atomically resolved analysis of the physical and chemical properties of materials. However, due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hesong Li , Ziqi Wu , Ruiwen Shao , Tao Zhang , Ying Fu