4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique
The combination of X-ray and neutron CT enables 4D studies, i.e. to explore the evolution of 3D structures with time. Here the authors apply this approach to a Li-ion primary cell, revealing elsewhere unseen trends in the spatial distribution of performance aided by a new ‘unrolling’ methodology....
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2020-02-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-019-13943-3 |
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doaj-7dfe8293b78244b886754f01238af7092021-05-11T09:15:55ZengNature Publishing GroupNature Communications2041-17232020-02-0111111110.1038/s41467-019-13943-34D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling techniqueRalf F. Ziesche0Tobias Arlt1Donal P. Finegan2Thomas M. M. Heenan3Alessandro Tengattini4Daniel Baum5Nikolay Kardjilov6Henning Markötter7Ingo Manke8Winfried Kockelmann9Dan J. L. Brett10Paul R. Shearing11Electrochemical Innovation Lab, Department of Chemical Engineering, University College LondonTechnische Universität BerlinNational Renewable Energy LaboratoryElectrochemical Innovation Lab, Department of Chemical Engineering, University College LondonGrenoble INP, CNRS, 3SR, Univ. Grenoble AlpesZuse Institute BerlinHelmholtz-Zentrum Berlin für Materialien und Energie (HZB)Technische Universität BerlinHelmholtz-Zentrum Berlin für Materialien und Energie (HZB)STFC, Rutherford Appleton Laboratory, ISIS FacilityElectrochemical Innovation Lab, Department of Chemical Engineering, University College LondonElectrochemical Innovation Lab, Department of Chemical Engineering, University College LondonThe combination of X-ray and neutron CT enables 4D studies, i.e. to explore the evolution of 3D structures with time. Here the authors apply this approach to a Li-ion primary cell, revealing elsewhere unseen trends in the spatial distribution of performance aided by a new ‘unrolling’ methodology.https://doi.org/10.1038/s41467-019-13943-3 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ralf F. Ziesche Tobias Arlt Donal P. Finegan Thomas M. M. Heenan Alessandro Tengattini Daniel Baum Nikolay Kardjilov Henning Markötter Ingo Manke Winfried Kockelmann Dan J. L. Brett Paul R. Shearing |
spellingShingle |
Ralf F. Ziesche Tobias Arlt Donal P. Finegan Thomas M. M. Heenan Alessandro Tengattini Daniel Baum Nikolay Kardjilov Henning Markötter Ingo Manke Winfried Kockelmann Dan J. L. Brett Paul R. Shearing 4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique Nature Communications |
author_facet |
Ralf F. Ziesche Tobias Arlt Donal P. Finegan Thomas M. M. Heenan Alessandro Tengattini Daniel Baum Nikolay Kardjilov Henning Markötter Ingo Manke Winfried Kockelmann Dan J. L. Brett Paul R. Shearing |
author_sort |
Ralf F. Ziesche |
title |
4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique |
title_short |
4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique |
title_full |
4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique |
title_fullStr |
4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique |
title_full_unstemmed |
4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique |
title_sort |
4d imaging of lithium-batteries using correlative neutron and x-ray tomography with a virtual unrolling technique |
publisher |
Nature Publishing Group |
series |
Nature Communications |
issn |
2041-1723 |
publishDate |
2020-02-01 |
description |
The combination of X-ray and neutron CT enables 4D studies, i.e. to explore the evolution of 3D structures with time. Here the authors apply this approach to a Li-ion primary cell, revealing elsewhere unseen trends in the spatial distribution of performance aided by a new ‘unrolling’ methodology. |
url |
https://doi.org/10.1038/s41467-019-13943-3 |
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