Scientists have been wondering about water for a long time. They think that if water is cooled down to really cold temperatures, like -100C, it might be able to turn into two types of liquid that are different densities. These two types of liquid don't mix, like oil and water, and they might help explain some of water's other strange behaviors, like how it becomes less dense when it gets colder. It's almost impossible to study this in a laboratory, though, because water turns into ice very quickly at these low temperatures. Now, researchers at the Georgia Institute of Technology have used machine learning models to better understand how water changes under different conditions.

Water has puzzled scientists for decades. For the last 30 years or so, they have theorized that when cooled down to a very low temperature like -100C, water might be able to separate into two liquid phases of different densities. Like oil and water, these phases don't mix and may help explain some of water's other strange behavior, like how it becomes less dense as it cools. It's almost impossible to study this phenomenon in a lab, though, because water crystallizes into ice so quickly at such low temperatures. Now, new research from the Georgia Institute of Technology uses machine learning models to better understand water's phase changes, opening more avenues for a better theoretical understanding of various substances. With this technique, the researchers found strong computational evidence in support of water's liquid-liquid transition that can be applied to real-world systems that use water to operate.