Battery Imaging Library: multi-length scale and multi-modal synchrotron and laboratory battery imaging data for all
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Supporting information
Accepted version
Author(s)
Type
Journal Article
Abstract
Battery research increasingly relies on advanced imaging, yet open access to such data remains rare, scattered across various sources, and difficult to find. The Battery Imaging Library (BIL) is the first open, curated collection of
multi-modal and multi-length scale battery imaging datasets, accompanied by a searchable, FAIR-compliant website. Distinctive features include the release of raw experimental data (radiographs, sinograms, X-ray and electron diffraction patterns) together with rare operando and multi-resolution datasets. Each dataset is linked to Zenodo DOIs with metadata, ensuring persistence and citability; open-source Python scripts for preprocessing and reconstruction are also provided for various CT modalities. BIL enables algorithm benchmarking, machine learning, and teaching using experimental and industrially relevant data. By combining coverage across modalities, length scales, and chemistries with raw data accessibility and a FAIR-aligned web platform, the Battery Imaging Library provides a foundation for openness and reproducibility in battery imaging. The library is available here: https://www.batteryimaginglibrary.com
multi-modal and multi-length scale battery imaging datasets, accompanied by a searchable, FAIR-compliant website. Distinctive features include the release of raw experimental data (radiographs, sinograms, X-ray and electron diffraction patterns) together with rare operando and multi-resolution datasets. Each dataset is linked to Zenodo DOIs with metadata, ensuring persistence and citability; open-source Python scripts for preprocessing and reconstruction are also provided for various CT modalities. BIL enables algorithm benchmarking, machine learning, and teaching using experimental and industrially relevant data. By combining coverage across modalities, length scales, and chemistries with raw data accessibility and a FAIR-aligned web platform, the Battery Imaging Library provides a foundation for openness and reproducibility in battery imaging. The library is available here: https://www.batteryimaginglibrary.com
Date Acceptance
2026-08-21
Citation
Digital Discovery
ISSN
2635-098X
Publisher
The Royal Society of Chemistry
Journal / Book Title
Digital Discovery
Copyright Statement
Copyright This paper is embargoed until publication. Once published the Version of Record (VoR) will be available on immediate open access.
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Publication Status
Accepted