most citedMic-hackathon 2024: Hackathon on Machine Learning for Electron and Scanning Probe Microscopy

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Generative Image Restoration and Super-Resolution using Physics-Informed Synthetic Data for Scanning Tunneling Microscopy

Nikola L. Kolev, Tommaso Rodani, Neil J. Curson +2

Scanning tunnelling microscopy (STM) enables atomic-resolution imaging and atom manipulation, but its utility is often limited by tip degradation and slow serial data acquisition.…

cond-mat.mtrl-sci2025★ 1 cited

Mic-hackathon 2024: Hackathon on Machine Learning for Electron and Scanning Probe Microscopy

Utkarsh Pratiush, Austin Houston, Kamyar Barakati +70

Microscopy is a primary source of information on materials structure and functionality at nanometer and atomic scales. The data generated is often well-structured, enriched with me…

cond-mat.mtrl-sci2025

Overcoming Labelled Data Scarcity for Defect Classification in Scanning Tunneling Microscopy

Nikola L. Kolev, Max Trouton, Filippo Federici Canova +4

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 sin…

cond-mat.mtrl-sci2025

Hydrogen Passivation Effects on Spatially Resolved Charge Trap Densities in Si(100)-SiO

Adam J. Czarnecki, Nikola L. Kolev, Patrick See +5

As silicon-based devices continue to shrink to the nanoscale, traps at the Si-SiO interface pose increasing challenges to device performance. These traps reduce channel carrier…

cond-mat.mtrl-sci2023

Detection Sensitivity Limit of Hundreds of Atoms with X-Ray Fluorescence Microscopy

Mateus G. Masteghin, Toussaint Gervais, Steven K. Clowes +10

We report X-ray fluorescence (XRF) imaging of nanoscale inclusions of impurities for quantum technology. A very bright diffraction-limited focus of the X-ray beam produces very hig…