STEM-Bank-26: An Open Dataset of Analytical Scanning Transmission Electron Microscopy Images and Spectra
Abstract
Scanning transmission electron microscopy (STEM) is a versatile, multi-modal method for studying materials at the nanoscale. It integrates multiple signal sources to provide atomic resolution imaging alongside spectroscopy for elemental composition and electronic structure. Despite its utility, few datasets spanning multiple years of data have been published. We introduce STEM-Bank-26, a 929 GB open dataset of 37,921 STEM images that spans 1,095 material samples across 1,499 sessions and includes energy-dispersive spectroscopy (EDS) or electron-energy loss spectroscopy (EELS) data for 65.5% of sessions. We extract microscope control trajectories by comparing metadata between sequential images and provide tools for building similar datasets from archival data. To our knowledge, this is the largest openly available dataset that integrates experimental STEM, EDS and EELS data across a broad distribution of samples and sessions.
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BibTeX
@misc{hollyer2026stembank26,
title = {{STEM-Bank-26: An Open Dataset of Analytical Scanning Transmission Electron Microscopy Images and Spectra}},
author = {George Hollyer and Eric Stach},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.36086},
eprint = {2610.36086},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.36086},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - STEM-Bank-26: An Open Dataset of Analytical Scanning Transmission Electron Microscopy Images and Spectra
AU - George Hollyer
AU - Eric Stach
PY - 2026
DA - 2026/10/26
PB - arXiv
DO - 10.48550/arxiv.2610.36086
UR - https://arxiv.org/abs/2610.36086
AB - Scanning transmission electron microscopy (STEM) is a versatile, multi-modal method for studying materials at the nanoscale. It integrates multiple signal sources to provide atomic resolution imaging alongside spectroscopy for elemental composition and electronic structure. Despite its utility, few datasets spanning multiple years of data have been published. We introduce STEM-Bank-26, a 929 GB open dataset of 37,921 STEM images that spans 1,095 material samples across 1,499 sessions and includes energy-dispersive spectroscopy (EDS) or electron-energy loss spectroscopy (EELS) data for 65.5% of sessions. We extract microscope control trajectories by comparing metadata between sequential images and provide tools for building similar datasets from archival data. To our knowledge, this is the largest openly available dataset that integrates experimental STEM, EDS and EELS data across a broad distribution of samples and sessions.
ER -