Predicting the Solubility of Inorganic Ions Pairs in Water

Polyoxometalates (POMs), ranging in size from 1 to 10's of nanometers, resemble building blocks of inorganic materials. Elucidating their complex solubility behavior with alkali-counterions can inform natural and synthetic aqueous processes. In the study of POMs ([Nb24O72H9](15-), Nb-24) we discovered an unusual solubility trend (termed anomalous solubility) of alkali-POMs, in which Nb-24 is most soluble with the smallest (Li+) and largest (Rb/Cs+) alkalis, and least soluble with Na/K+. Via computation, we define a descriptor (sigma-profile) and use an artificial neural network (ANN) to predict all three described alkali-anion solubility trends: amphoteric, normal (Li+>Na+>K+>Rb+>Cs+), and anomalous (Cs+>Rb+>K+>Na+>Li+). Testing predicted amphoteric solubility affirmed the accuracy of the descriptor, provided solution-phase snapshots of alkali-POM interactions, yielded a new POM formulated [Ti6Nb14O54](14-), and provides guidelines to exploit alkali-POM interactions for new POMs discovery.