Machine learning proves that graphene is hydrophobic
Institute for Basic SciencePeer-Reviewed Publication
For more than a decade, a fundamental mystery has surrounded graphene—the one-atom-thick “wonder material” known for its exceptional strength, conductivity, and transparency. Despite its seemingly simple structure, one basic question has remained unresolved: does graphene attract water, or repel it?
The answer has proven surprisingly elusive. In some experiments, water droplets bead up on graphene, suggesting a hydrophobic (water-repellent) surface. In others, water spreads out, implying hydrophilic (water-attracting) behavior. This contradiction has fueled a long-running scientific debate and created uncertainty for applications such as desalination membranes, hydrogen fuel cells, and nanoelectronic devices, where precise control of water at interfaces is essential.
A research team led by Director CHO Minhaeng and Professor Stefan RINGE at the Center for Molecular Spectroscopy and Dynamics within the Institute for Basic Science, in collaboration with Korea University, has now resolved this puzzle. Using machine-learning–enhanced molecular simulations, the researchers demonstrate that pristine graphene is intrinsically hydrophobic and microscopically not wetting transparent.- Journal
- Nature Communications
- Funder
- Institute for Basic Science