One of the most iconic properties of ice is its slipperiness. While humans exploit this property at a large scale in various sports, such as hockey and figure skating, we have yet to reach a clear scientific consensus on why ice is so slippery.
Ultimately, the slipperiness of ice is an emergent phenomenon stemming from the interactions of the atoms at the interface between the sliding body and the ice. Therefore, in this proposal, the project sought the computing time needed to simulate the underlying process of metal sliding on ice at the atomic level.
To reach the long length- and time scales needed to study this phenomenon under operating conditions, the projects used a highly scalable state-of-the-art neural network-based molecular dynamics approach. To study this phenomenon accurately, this model will be parameterised from first principles calculations at the hybrid DFT level of theory. Through the trajectories of the water molecules, the project will unravel the molecular mechanism behind the slipperiness of ice.
University of Oslo, Norway.