The new research, conducted at the Georgia Institute of Technology, uses machine learning models to better understand the phase changes of water and opens up new opportunities for better theoretical understanding of various substances.
Water has puzzled scientists for decades. For the past 30 years, they hypothesized that when water is cooled to a very low temperature of -100 degrees Celsius, it can split into two liquid phases of different densities. Like oil and water, these phases do not mix and may help explain some of the other wonders of water’s behavior, such as the fact that it becomes less dense as it cools.
However, it is almost impossible to study this phenomenon in the laboratory, because at such low temperatures water quickly crystallizes into ice.
Using the new technique, the researchers found compelling computational evidence that could be applied to real systems that use water to work, to support the transition of water to the liquid state.
“We do this with the help of very detailed quantum chemistry calculations, where we try to get as close as possible to the actual physics and physical chemistry of water.”said Thomas Gartner, an associate professor in the School of Chemical and Biomolecular Engineering at the Georgia Institute of Technology. “This is the first time this transition has been studied with such precision.”.
Source: Port Altele
