Machine learning molecular simulation reveals the role of atomic-scale roughness in hydrophilicity

Machine Learning


Simulations comparing aluminum oxide models with different amounts of corrugation demonstrated the importance of hydroxyl groups in water interactions.

Hydrophilicity governs important processes in catalysis, corrosion, and energy materials. However, the molecular origin of hydrophilicity is still not well understood. Experiments have shown that even in common materials such as aluminum oxide, different crystal planes can behave very differently when interacting with water.

Choutipalli et al. used machine learning molecular simulations to characterize the structure and dynamics of hydrogen bond networks on three different alumina surfaces. The group used data-trained neural network potentials using density functional theory to evaluate the nanosecond molecular dynamics of water on three alumina crystal faces at the surface, showing how atomic-scale roughness and hydroxyl group placement determine hydrophilicity.

Traditional simulations are typically too short or insufficiently accurate to capture multiple structural and dynamic observations to decipher hydrophilicity at the atomic level. The team sought to overcome these limitations using machine learning.

“Our results establish a mechanistic basis for hydrophilicity that can be extended to other oxides and heterogeneous interfaces,” said author Venkata Surya Kumar Chotipalli. “The relationships identified between surface corrugation, hydrogen bond strength, and water order provide a quantitative framework for designing materials with tunable wetting properties. This has the potential to impact a wide range of applications, from catalyst supports and antifouling coatings to membranes and energy storage interfaces.”

Water diffusion, density variations, hydrogen bond lifetimes, and vibrational spectra demonstrated that the more corrugated the surface, the more hydrophilic it is. The most corrugated surface (0112) traps water most strongly and forms the strongest hydrogen bonds.

“These results show that surface topography and hydroxyl arrangement, as well as chemistry, govern how water is attached and organized, and provide a microscopic picture that integrates structural, dynamic, and vibrational observations,” said Chotipalli.

They next work to investigate amorphous and defect-rich alumina surfaces, where local disorder and roughness can further enhance hydrophilicity.

sauce: “On the origin of hydrophilic interactions on alumina surfaces,” by Venkata Surya Kumar Chotipalli, Michael L. Klein, and Mark DelloStritto. chemical physics journal (2025). This article can be accessed from: https://doi.org/10.1063/5.0294178 .





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