Experimental data: Optimizing alkaline solvent regeneration through bipolar membrane electrodialysis for carbon capture
doi:10.4121/3c24cd14-e0fc-4b66-802d-3315ffc4fffa.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/3c24cd14-e0fc-4b66-802d-3315ffc4fffa
doi: 10.4121/3c24cd14-e0fc-4b66-802d-3315ffc4fffa
Datacite citation style:
Philipp Kuntke; Hubertus V.M. Hamelers; Shu, Qingdian; Blauw, Robert; Vallejo Castaño, Sara et. al. (2024): Experimental data: Optimizing alkaline solvent regeneration through bipolar membrane electrodialysis for carbon capture. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/3c24cd14-e0fc-4b66-802d-3315ffc4fffa.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
usage stats
123
views
74
downloads
categories
geolocation
Wetsus, Leeuwarden
time coverage
July 2022 to January 2023
licence
CC BY 4.0
This dataset contains data collected during experiments on optimising alkaline solvent regeneration through bipolar membrane electrodialysis for carbon capture. It is being made public both to act as supplementary data for publication and in order for other researchers to use this data in their own work.
This work was performed at Wetsus, European Centre of Excellence for Sustainable Water Technology, between July 2022 and January 2023.
history
- 2024-04-03 first online, published, posted
publisher
4TU.ResearchData
format
CSV
funding
- ConsenCUS (grant code 101022484) [more info...] Horizon 2020 research and innovation programme
organizations
Wetsus, European Centre of Excellence for Sustainable Water TechnologyEnvironmental Technology, Wageningen University & Research
Center for Energy Resources Engineering (CERE), Department of Chemical and Biochemical Engineering, Technical University of Denmark
DATA
files (2)
- 3,708 bytesMD5:
95eb2b5ebf533f081148581f619b1ee2
README.txt - 5,104 bytesMD5:
3d05e476b2faa32b0f271fa8ec98f389
2023_dataset_parametric_study_BPED_CO2_regneration.csv -
download all files (zip)
8,812 bytes unzipped