Predicting the Solubility of Inorganic Ions Pairs in Water

Using alkali-polyoxometalate salts, a previously-undescribed solubility trend in polyoxometalate chemistry was discovered, termed anomalous solubility. Mapping charge-density on inorganic polyatomic anions along with an artificial neural network accurately describes and predicts solubility trends of alkali-anion pairs. Solubility experiments to validate computation leads to new POMs discovery.

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⁻, 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 [Ti₆Nb₁₄O₅₄]¹⁴⁻, and provides guidelines to exploit alkali–POM interactions for new POMs discovery.