Novel approach using AI to study with unprecedented resolution the phase behaviors of superionic water found on ice giants

LLNL scientists have developed a new approach using machine learning to study with unprecedented resolution the phase behaviors of superionic water found in ice giants.

 

The interiors of Uranus and Neptune each contain about 50,000 times the amount of water in Earth’s oceans, and a form of water known as superionic water is believed to be stable at depths greater than approximately one-third of the radius of these ice giants.

 

Superionic water is a phase of H2O where hydrogen atoms become liquid-like while oxygen atoms remain solid-like on a crystalline lattice. Although superionic water was proposed over three decades ago, its optical properties and oxygen lattices were only accurately measured recently in experiments by LLNL’s Marius Millot and Federica Coppari, and many properties of this hot “black ice” are still uncharted.

Read the full article at: scitechdaily.com