DOI > 10.5291/ILL-DATA.1-06-2

Please note

The full details of this dataset is not yet available to the public as it still under its embargo period. As such there are only a few details publically exposed. To find out more about how the ILL governs the release of data, please go here. Thank you for your understanding.

Title

High-speed 4D neutron computed tomography for mass transport in proton exchange membrane water electrolysers

Abstract

Energy demand and environmental pollution have become the two major problems to which societies are seeking immediate remedies. Proton exchange membrane water electrolysers (PEMWEs) are a potential solution to the increasing demand for inconsistent renewable energy technologies and seasonal storage. One of the long-standing challenges for efficient and reliable PEMWE performance is accomplishing effective mass transport of water and product gas. Novel flow-field and liquid-gas diffusion layer designs serve as a simple and effective means of optimising the mass transport processes. However, an appropriate characterisation tools for studying of the water dynamics within operating PEMWEs has not been established. The aim of this proposal is to use the unique benefits of NeXT-Grenoble instruments to provide the first-ever report of the 4D operando water distribution across different parts of PEMWEs. This has major implications for PEMWEs design and operation and be of interest to academics and technology developers alike.

Experimental Report

Download Data

The data is currently only available to download if you are a member of the proposal team.

Download Data

Data Citation

The recommended format for citing this dataset in a research publication is in the following format:

Y WU; BRETT Dan; JOHNSTONE-HACK Jennifer; MALONE Iain; SHEARING Paul; TENGATTINI Alessandro; Yue Wen and Ralf F. Ziesche. (2023). High-speed 4D neutron computed tomography for mass transport in proton exchange membrane water electrolysers. Institut Laue-Langevin (ILL) doi:10.5291/ILL-DATA.1-06-2

Cited by

This data has not been cited by any articles.

Metadata

Experiment Parameters

This data is not yet public

Sample Parameters

This data is not yet public