Research data supporting "Dielectrocapillarity for exquisite control of fluids"
Description
This directory contains the research data supporting the manuscript:
"Dielectrocapillarity for exquisite control of fluids"
Authors: Bui, Anna; Cox, Stephen
Paper published at: Nature Communications
Preprint: https://arxiv.org/abs/2503.09855
It contains source data for the figures in the manuscript, example simulation inputs and the training data for the neural density functionals.
For detailed information of the dataset and models, please refer to the README.md files in the sub-directories and the manuscript.
For script to train the models and do hyper-DFT calculations, see:
https://github.com/annatbui/dielectrocapillarity-cdft
Files
Files
(349.9 MB)
| Name | Size | Download all |
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md5:706a7aca053bf73180f7909ba29d648c
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349.9 MB | Download |
Additional details
Funding
- Royal Society
- Royal Society University Fellowship URF\R1\211144
- University of Cambridge
- Ernest Oppenheimer Scholarship
- University of Cambridge
- Peterhouse Postgraduate Studentship
Software
- Repository URL
- https://github.com/annatbui/dielectrocapillarity-cdft
- Programming language
- Python