New Battery Imaging Library (BIL)

We are pleased to announce the launch of the Battery Imaging Library (BIL) – www.batteryimaginglibrary.com

BIL is the first open-access collection of multi-modal and multi-length scale battery imaging datasets. A combination of laboratory and synchrotron X-ray CT (micro-CT, nano-CT, XRD-CT), neutron CT, SEM/EDX, EBSD, and S3DXRD. One unique feature is the release of raw experimental data: radiographs, sinograms, X-ray diffraction patterns, and electron Kikuchi diffraction patterns. The library already hosts more than 3.5 TB of compressed data, openly available for the community.

You can find open-access Python notebooks with example workflows at https://github.com/antonyvam/BatteryImagingLibrary

BIL has been designed to support:
• Educators who want to give students hands-on access to real experimental datasets.
• Researchers developing and benchmarking algorithms for reconstruction, denoising, segmentation and other machine learning approaches using experimental industrially relevant data.
• The wider community through FAIR principles, with all datasets permanently archived with DOIs and rich metadata.

BIL is the result of collaboration between multiple institutions and facilities including Imperial College London, Diamond Light Source, ESRF – The European Synchrotron, DESY, μ-VIS X-ray Imaging Centre (muvis), UCL Chemistry, The University of Manchester, ISIS Neutron and Muon Source, UKBIC, National Renewable Energy Laboratory and WMG, University of Warwick.  Funding for Dr Antony Vamvakeros’s work was provided by The Royal Society through their Industry Fellowship.

You can find the BIL preprint at https://chemrxiv.org/engage/chemrxiv/article-details/68d3b52b3e708a7649ffd0a5