Fleeting phenomenon of water autoionisation pinned down by neural network simulations

Scientists in China have combined molecular dynamics with machine learning to carry out precise nanosecond-scale simulations of water ionisation,¹ shedding light on a process that has been known for over a century but was tricky to understand because the events involved are so rare and hard to follow. ‘The extremely scarce probability of observing water ionisation under natural conditions obstructs direct experimental probing and poses a great challenge to the theoretical community for characterising the free-energy profile and revealing the reaction mechanism,’ says Ling Liu from Nanjing University, who is part of the team. He explains that although water autoionisation plays an important role in many chemical and biological processes, ambiguities surrounding the mechanism of this reaction have led to limited understanding of some of these events. The new findings could be used to study such systems in more detail, he adds.