Machine learning and physics merge to enhance liquid-gas phase transition predictions

Combining concepts from statistical physics with machine learning, researchers at the University of Bayreuth have shown that highly accurate and efficient predictions can now be made as to whether a substance will be liquid or gaseous under given conditions. They have published their findings in Physical Review X.