Published January 26, 2026 | Version v1
Dataset Open

Research data supporting "Dielectrocapillarity for exquisite control of fluids"

  • 1. ROR icon University of Cambridge
  • 2. ROR icon Durham University

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)

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md5:706a7aca053bf73180f7909ba29d648c
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