Machine learning cracks the oxidation states of crystal structures

Chemists voting on the oxidation states of metal-organic frameworks. Credit: David Abbasi Pérez. Chemical engineers at EPFL have developed a machine-learning model that can predict a compound's oxidation state, a property that is so essential that many chemists argue it must be included in the periodic table. Chemical elements make up pretty much everything in the physical world. As of 2016, we know of 118 elements, all of which can be found categorized in the famous periodic table that hangs in every chemistry lab and classroom. Each element in the periodic table appears as a one-, two-letter abbreviation (e.g. O for oxygen, Al for aluminum) along with its atomic number, which shows how many protons there are in the element's nucleus.