Uncovering Polyoxometalate Speciation in Hydrothermal Systems by Combining Computational Simulation with X-ray Total Scattering

A systematic approach for understanding the pH-dependent speciation of molecular metal-oxide nanoclusters beyond ambient conditions, which combines computational predictions with X-ray total scattering experiments, is presented. We demonstrate that temperature-dependent water properties have a significant impact on molecular energies derived from implicit solvent modeling and propose an efficient correction strategy. Based on this, we expand our methodology toward the elevated temperatures and pressures characteristic of hydrothermal synthesis. Correlating these computational results with experimental observations reveals a remarkable synergy between the two approaches, which helps to differentiate closely related polyoxometalates coexisting in solution. We find that qualitative trends are directly reproduced computationally, while the intricate nature of polyoxometalate speciation is best captured by adjusting computational predictions based on experimental insights. The derived knowledge of the clusters present under various conditions enables us to rationalize the crystallization of h-MoO₃ at high temperatures and very acidic pH. With this, our study highlights the potential of hybrid approaches for elucidating solution-based oxide formation under extreme conditions.