Uranus and Neptune each contain about 50,000 times as much water as the Earth’s ocean, and the form of water called superionic water makes up about a third of the radius of these ice giants. It is believed to be stable at greater depths.
Super ionized water is phase H2O where the hydrogen atom will be like a liquid oxygen atom It remains as a solid on the crystal lattice. Super ionized water was proposed over 30 years ago, optical properties The oxygen grid has only recently been accurately measured in experiments with Marius Millot and Federica Coppari of the LLNL, and many properties of this Hot âblack iceâ has yet to be elucidated.
Scientists at Lawrence Livermore National Laboratory (LLNL) have developed a new approach to study the phase behavior of superionized water at unprecedented resolution using machine learning.
Being buried deep within the core of the planet, much of the water in the universe can be superionic, and understanding its thermodynamic and transport properties is important for planetary science, but experimentally or study theoretically.
Under the pressure and temperature found on giant ice planets, most of this water was predicted to be in the superionic phase by First Principle Molecular Dynamics (FPMD) simulations. However, such quantum mechanics simulations have traditionally been limited to short simulation times (tens of picoseconds) and small system sizes (hundreds of atoms), resulting in significant imperfections in the location of the boundary limits. phase such as merge lines. Brings certainty.
In experiments with superionized water, sample preparation is very difficult, hydrogen cannot be located, and temperature measurements in dynamic compression experiments are not easy. Experiments often benefit from the guidance provided by quantum molecular dynamics simulations, both in the design phase and in the interpretation of the results.
In the latest study, the team dramatically improved their ability to handle large system sizes and long-term scales by learning atomic interactions from quantum mechanical calculations using machine learning techniques. paddy field. Then take advantage of this machine learning potential. Molecular Dynamics It uses an advanced free energy sampling method to allow precise determination of phase boundaries.
âWe use machine learning and the free energy method to overcome the limitations of quantum mechanical simulation and characterize hydrogen diffusion, superion transitions and phase behavior of water. Extreme state, “said LLNL physicist SÃ©bastien Hamel Physics of nature..
The team found that phase boundaries consistent with existing experimental observations help resolve the proportions of isolated ice, various superionic phases, and liquid water in giant ice planets.
Building efficient interatomic potentials that maintain the accuracy of quantum mechanical calculations is a daunting task. The framework developed here is common and is used in other complex materials such as battery electrolytes, plastics, nanocrystalline diamonds used in ICF capsules, as well as ammonia, salts, hydrocarbons, silicates and others. . It can be used to discover and / or characterize new phases of the mixture. It is related to planetary science.
âQuantitative Understanding of Superion Water It sheds light on the internal structure, evolution, magnetic fields and even the increasing number of extrasolar planets such as ice, like Uranus and Neptune,â Hamel said.
Researchers from the University of Cambridge, the University of Lyon and the University of Tohoku also contributed to this treatise. The LLNL part of the study is funded by the R & D project led by the Institute âUnderstanding the Physics and Chemistry of Low Z Mixtures at Extreme Pressures and Temperaturesâ and the Institutional Computing Grand Challenge program.
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Cheng, B. et al. Phase behavior of superionic water under planetary conditions. Nut physics (2021). doi.org/10.1038/s41567-021-01334-9
Lawrence Livermore National Laboratory
Quote: On entering, the water is superionic (2021, September 23). Obtained from https://phys.org/news/2021-09-superionic.html on September 23, 2021.
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