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Related papers: Autonomous Investigations over WS$_2$ and Au{111} …

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With the continuing advances in scientific instrumentation, scanning microscopes are now able to image physical systems with up to sub-atomic-level spatial resolutions and sub-picosecond time resolutions. Commensurately, they are generating…

The nature of the atomic defects on the hydrogen passivated Si (100) surface is analyzed using deep learning and scanning tunneling microscopy (STM). A robust deep learning framework capable of identifying atomic species, defects, in the…

Materials Science · Physics 2020-02-19 Maxim Ziatdinov , Udi Fuchs , James H. G. Owen , John N. Randall , Sergei V. Kalinin

Tunneling spectroscopy played a central role in the experimental verification of the microscopic theory of superconductivity in the classical superconductors. Initial attempts to apply the same approach to high-temperature superconductors…

Superconductivity · Physics 2009-09-29 Oystein Fischer , Martin Kugler , Ivan Maggio-Aprile , Christophe Berthod , Christoph Renner

Scanning Tunneling Spectroscopy (STS) is a unique technique to probe the local density of states (LDOS) at the atomic scale by measuring the tunneling conductance between a sharp tip and a sample surface. However, the technique suffers of…

Scanning tunnelling microscopy (STM) is a powerful technique for imaging surfaces with atomic resolution, providing insight into physical and chemical processes at the level of single atoms and molecules. A regular task of STM image…

Scanning transmission electron microscopy (STEM) is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric…

Materials Science · Physics 2021-08-11 Nicole Creange , Ondrej Dyck , Rama K. Vasudevan , Maxim Ziatdinov , Sergei V. Kalinin

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. The local structures are conventionally probed using spatially resolved studies and the property correlations are usually deciphered by…

Materials Science · Physics 2024-04-11 Ganesh Narasimha , Dejia Kong , Paras Regmi , Rongying Jin , Zheng Gai , Rama Vasudevan , Maxim Ziatdinov

Atomic scale characterization and manipulation with scanning probe microscopy rely upon the use of an atomically sharp probe. Here we present automated methods based on machine learning to automatically detect and recondition the quality of…

Mesoscale and Nanoscale Physics · Physics 2018-03-26 Mohammad Rashidi , Robert A. Wolkow

Spectroscopic mapping refers to the massive recording of spectra whilst varying an additional degree of freedom, such as: magnetic field, location, temperature, or charge carrier concentration. As this involves two serial tasks,…

Materials Science · Physics 2021-11-15 Berk Zengin , Jens Oppliger , Danyang Liu , Lorena Niggli , Tohru Kurosawa , Fabian Donat Natterer

Electronic interactions present in material compositions close to the superconducting dome play a key role in the manifestation of high-Tc superconductivity. In many correlated electron systems, however, the parent or underdoped states…

Materials Science · Physics 2016-11-23 Maxim Ziatdinov , Artem Maksov , Li Li , Athena Sefat , Petro Maksymovych , Sergei Kalinin

Rapid proliferation of hyperspectral imaging in scanning probe microscopies creates unique opportunities to systematically capture and categorize higher dimensional datasets, toward new insights into electronic, mechanical and chemical…

Superconductivity · Physics 2024-04-23 Petro Maksymovych , Jiaqiang Yan , Brian Sales , Jun Wang

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…

Improving the detailed understanding of the underlying properties and functions of biomolecules has recently attracted growing interest, enabled by the possibility of real-space imaging of single, intact macromolecules using Scanning…

Mesoscale and Nanoscale Physics · Physics 2026-03-10 Tim J. Seifert , Dhaneesh Kumar , Markus Etzkorn , Stephan Rauschenbach , Klaus Kern , Kelvin Anggara , Uta Schlickum

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

Chalcogen vacancies in transition metal dichalcogenides are widely acknowledged as both donor dopants and as a source of disorder. The electronic structure of sulphur vacancies in MoS2 however is still controversial, with discrepancies in…

The Intelligent Fault Diagnosis of rotating machinery currently proposes some captivating challenges. Although results achieved by artificial intelligence and deep learning constantly improve, this field is characterized by several open…

Signal Processing · Electrical Eng. & Systems 2022-07-26 Eugenio Brusa , Cristiana Delprete , Luigi Gianpio Di Maggio

Atomic-scale defect detection is shown in scanning tunneling microscopy images of single crystal WSe2 using an ensemble of U-Net-like convolutional neural networks. Standard deep learning test metrics indicated good detection performance…

Scanning tunneling microscopy (STM) at 5 K was used to study individual Au atoms adsorbed on the surface of a WSe2 layer grown on epitaxial graphene. In line with theoretical predictions, scanning tunneling spectroscopy measurements reveal…

Mesoscale and Nanoscale Physics · Physics 2025-08-18 Hitesh Kumar , Yu-Chuan Lin , Joshua A. Robinson , Stefan Fölsch

We present an advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements. This system expertly identifies and manipulates atomic positions with high…

Computational Physics · Physics 2024-04-18 Zhuo Diao , Keiichi Ueda , Linfeng Hou , Fengxuan Li , Hayato Yamashita , Masayuki Abe

Structural defects in 2D materials offer an effective way to engineer new material functionalities beyond conventional doping in semiconductors. Specifically, deep in-gap defect states of chalcogen vacancies have been associated with…

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