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 ([Nb24 O72 H9 ]15- , Nb24 ) we discovered an unusual solubility trend (termed anomalous solubility) of alkali-POMs, in which Nb24 is most soluble with the smallest (Li+ ) and largest (Rb/Cs+ ) alkalis, and least soluble with Na/K+ . Via computation, we define a descriptor (σ-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 [Ti6 Nb14 O54 ]14- , and provides guidelines to exploit alkali-POM interactions for new POMs discovery.

Predicting the Solubility of Inorganic Ion Pairs in Water

Department of Chemistry Oregon State University  Corvallis OR 97331 USA

Institute of Chemical Research of Catalonia (ICIQ) Barcelona Institute of Science &amp; Technology (BIST)  Av. Països Catalans 16 43007 Tarragona Spain