Computational insights into aqueous speciation of metal-oxide nanoclusters: an in-depth study of the Keggin phosphomolybdate.

ABSTRACT: Herein, we present a new computational methodology that unlocks the prediction of the complex multi-species multi-equilibria processes involved in the formation of complex metal-oxo nanoclusters. Relying on our recently introduced method named POMSimulator, we extended its capabilities and challenged its accuracy with the well-known phosphomolybdate [PMo₁₂O₄₀]^3- Keggin anion system. We show how the use of statistical techniques enabled the processing of a vast number of speciation models and their associated systems of non-linear equations efficiently and in a scalable manner. Subsequently, this approach is applied to generate statistically averaged speciation diagrams and their associated error bars. Then, we unveil the previously unreported speciation pha

SUBMITTER: Buils J 

PROVIDER: S-EPMC11325188 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature