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High-resolution mapping of electronic properties at oxide heterointerfaces remains challenging due to probe delocalization and overlapping signals. In this work, we employ monochromated, probe-corrected scanning transmission electron…

In the present work, Cs aberration corrected and monochromated scanning transmission electron microscopy electron energy loss spectroscopy STEM-EELS has been used to explore experimental set-ups that allows bandgaps of high refractive index…

Electron microscopy has shown to be a very powerful tool to map the chemical nature of samples at various scales down to atomic resolution. However, many samples can not be analyzed with an acceptable signal-to-noise ratio because of the…

Image and Video Processing · Electrical Eng. & Systems 2018-02-28 Étienne Monier , Thomas Oberlin , Nathalie Brun , Marcel Tencé , Marta de Frutos , Nicolas Dobigeon

A technique to measure the band gap of dielectric materials with high refractive index by means of energy electron loss spectroscopy (EELS) is presented. The technique relies on the use of a circular (Bessel) aperture and suppresses…

The electronic properties of two-dimensional (2D) materials depend sensitively on the underlying atomic arrangement down to the monolayer level. Here we present a novel strategy for the determination of the band gap and complex dielectric…

Over the last two decades, Electron Energy Loss Spectroscopy (EELS) imaging with a scanning transmission electron microscope (STEM) has emerged as a technique of choice for visualizing complex chemical, electronic, plasmonic, and phononic…

The performance of electron energy-loss spectrometers can often be limited by their electron-optical aberrations. Due to recent developments in high energy-resolution and momentum-resolved electron energy loss spectroscopy (EELS), there is…

Materials Science · Physics 2023-02-28 Yueming Guo , Andrew R. Lupini

On- and off-axis electron energy loss spectroscopy (EELS) is a powerful method for probing local electronic structure on single atom level. However, many materials undergo electron-beam induced transformation during the scanning…

Materials Science · Physics 2023-10-23 Kevin M. Roccapriore , Riccardo Torsi , Joshua Robinson , Sergei V. Kalinin , Maxim Ziatdinov

Exploiting the information provided by electron energy-loss spectroscopy (EELS) requires reliable access to the low-loss region where the zero-loss peak (ZLP) often overwhelms the contributions associated to inelastic scatterings off the…

Materials Science · Physics 2020-09-14 Laurien I. Roest , Sabrya E. van Heijst , Louis Maduro , Juan Rojo , Sonia Conesa-Boj

The electronic band structure of complex nanostructured semiconductors has a considerable effect on the final electronic and optical properties of the material and, ultimately, on the functionality of the devices incorporating them. Valence…

Machine learning techniques are utilized to estimate the electronic band gap energy and forecast the band gap category of materials based on experimentally quantifiable properties. The determination of band gap energy is critical for…

Materials Science · Physics 2024-03-11 Sagar Prakash Barad , Sajag Kumar , Subhankar Mishra

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) 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…

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

Machine learning is transforming materials discovery by providing rapid predictions of material properties, which enables large-scale screening for target materials. However, such models require training data. While automated data…

Advancements in fast electron detectors have enabled the statistically significant sampling of crystal structures on the nanometre scale by means of Scanning Electron Nanobeam Diffraction (SEND). Characterisation of structural similarity…

Materials Science · Physics 2022-07-28 Andy Bridger , William I. F. David , Thomas J. Wood , Mohsen Danaie , Keith T. Butler

Scanning Transmission Electron Microscopy (STEM) offers high-resolution images that are used to quantify the nanoscale atomic structure and composition of materials and biological specimens. In many cases, however, the resolution is limited…

Signal Processing · Electrical Eng. & Systems 2021-12-23 Daniel Nicholls , Alex Robinson , Jack Wells , Amirafshar Moshtaghpour , Mounib Bahri , Angus Kirkland , Nigel Browning

The robust approach for real-time analysis of the scanning transmission electron microscopy (STEM) data streams, based on the ensemble learning and iterative training (ELIT) of deep convolutional neural networks, is implemented on an…

Disordered Systems and Neural Networks · Physics 2022-07-27 Kevin M. Roccapriore , Matthew G. Boebinger , Ondrej Dyck , Ayana Ghosh , Raymond R. Unocic , Sergei V. Kalinin , Maxim Ziatdinov

Fine structure analysis of core electron excitation spectra is a cornerstone characterization technique across the physical sciences. Spectra are most commonly measured with synchrotron radiation and X-ray spot sizes on the {\mu}m to mm…

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
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