4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique
- Submitting institution
-
University College London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 10389
- Type
- D - Journal article
- DOI
-
10.1038/s41467-019-13943-3
- Title of journal
- Nature communications
- Article number
- ARTN 777
- First page
- 777
- Volume
- 11
- Issue
- 1
- ISSN
- 2041-1723
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-019-13943-3/MediaObjects/41467_2019_13943_MOESM1_ESM.pdf
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
11
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work was conducted across international synchrotron and neutron facilities, and provided the first direct correlation of X-ray and neutron image data of lithium-batteries. Adapting algorithms originally developed for interpreting ancient scrolls, we successfully, virtually 'unrolled' battery architectures to super-impose data sets, providing new insight into the dynamic transport of lithium in working cells. The paper captured public imagination and was featured in the press (Eurek Alert, Materials Today, IOM3, Chemistry Views), as well as in a Faraday Institution science highlight (https://faraday.ac.uk/research/research-highlights/).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -