POMSimulator: An open-source tool for predicting the aqueous speciation and self-assembly mechanisms of polyoxometalates.

Elucidating the speciation (in terms of concentration versus pH) and understanding the formation mechanisms of polyoxometalates remains a significant challenge, both in experimental and computational domains. POMSimulator is a new methodology that tackles this problem from a purely computational perspective. The methodology uses results from quantum mechanics based methods to automatically set up the chemical reaction network, and to build speciation models. As a result, it becomes possible to predict speciation and phase diagrams, as well as to derive new insights into the formation mechanisms of large molecular clusters. In this work we present the main features of the first open-source version of the software. Since the first report [Chem. Sci. 2020, 11, 8448-8456], POMSimulator has undergone several improvements to keep up with the growing challenges that were tackled. After four years of research, we recognize that the source code is sufficiently stable to share a polished and user-friendly version. The Python code, manual, examples, and install instructions can be found at https://github.com/petrusen/pomsimulator.

Multi-Time-Scale Simulation of Complex Reactive Mixtures: How Do Polyoxometalates Form?

Understanding the dynamics of reactive mixtures still challenges both experiments and theory. A relevant example can be found in the chemistry of molecular metal-oxide nanoclusters, also known as polyoxometalates. The high number of species potentially involved, the interconnectivity of the reaction network, and the precise control of the pH and concentrations needed in the synthesis of such species make the theoretical/computational treatment of such processes cumbersome. This work addresses this issue relying on a unique combination of recently developed computational methods that tackle the construction, kinetic simulation, and analysis of complex chemical reaction networks. By using the Bell-Evans-Polanyi approximation for estimating activation energies, and an accurate and robust linear scaling for correcting the computed pKa values, we report herein multi-time-scale kinetic simulations for the self-assembly processes of polyoxotungstates that comprise 22 orders of magnitude, from tens of femtoseconds to months of reaction time. This very large time span was required to reproduce very fast processes such as the acid/base equilibria (at 10-12 s), relatively slow reactions such as the formation of key clusters such as the metatungstate (at 103 s), and the very slow assembly of the decatungstate (at 106 s). Analysis of the kinetic data and of the reaction network topology shed light onto the details of the main reaction mechanisms, which explains the origin of kinetic and thermodynamic control followed by the reaction. Simulations at alkaline pH fully reproduce experimental evidence since clusters do not form under those conditions.

A redox-active inorganic crown ether based on a polyoxometalate capsule.

Cation-uptake has been long researched as an important topic in materials science. Herein we focus on a molecular crystal composed of a charge-neutral polyoxometalate (POM) capsule [MoVI72FeIII30O252(H2O)102(CH3CO2)15]3+ encapsulating a Keggin-type phosphododecamolybdate anion [α-PMoVI12O40]3-. Cation-coupled electron-transfer reaction occurs by treating the molecular crystal in an aqueous solution containing CsCl and ascorbic acid as a reducing reagent. Specifically, multiple Cs+ ions and electrons are captured in crown-ether-like pores {MoVI3FeIII3O6}, which exist on the surface of the POM capsule, and Mo atoms, respectively. The locations of Cs+ ions and electrons are revealed by single-crystal X-ray diffraction and density functional theory studies. Highly selective Cs+ ion uptake is observed from an aqueous solution containing various alkali metal ions. Cs+ ions can be released from the crown-ether-like pores by the addition of aqueous chlorine as an oxidizing reagent. These results show that the POM capsule functions as an unprecedented "redox-active inorganic crown ether", clearly distinguished from the non-redox-active organic counterpart.

Computational Prediction of Speciation Diagrams and Nucleation Mechanisms: Molecular Vanadium, Niobium, and Tantalum Oxide Nanoclusters in Solution.

Understanding the aqueous speciation of molecular metal-oxo-clusters plays a key role in different fields such as catalysis, electrochemistry, nuclear waste recycling, and biochemistry. To describe the speciation accurately, it is essential to elucidate the underlying self-assembly processes. Herein, we apply a computational method to predict the speciation and formation mechanisms of polyoxovanadates, -niobates, and -tantalates. While polyoxovanadates have been widely studied, polyoxoniobates and -tantalates lack the same level of understanding. First, we propose a pentavanadate cluster ([V5O14]3-) as a key intermediate for the formation of the decavanadate. Our computed phase speciation diagram is in particularly good agreement with the experiments. Second, we report the formation constants of the heptaniobate, [Nb7O22]9-, decaniobate, [Nb10O28]6-, and tetracosaniobate [H9Nb24O72]15-. Additionally, we compute the speciation and phase diagram of niobium, which so far was restricted to Lindqvist derivates. Finally, we predict the formation constant of the decatantalate ([Ta10O26]6-) in water, even though it had only been synthesized in toluene. Furthermore, we also calculate the corresponding speciation and phase diagrams for polyoxotantalates. Overall, we show that our method can be successfully applied to different families of molecular metal oxides without any need for readjustments; therefore, it can be regarded as a trustworthy tool for exploring polyoxometalates' chemistry.

Predicting the Solubility of Inorganic Ion 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 ([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.

Unlocking Phase Diagrams for Molybdenum and Tungsten Nanoclusters and Prediction of their Formation Constants.

Understanding and controlling aqueous speciation of metal oxides are key for the discovery and development of novel materials, and challenge both experimental and computational approaches. Here we present a computational method, called POMSimulator, which is able to predict speciation phase diagrams (Conc. vs pH) for multispecies chemical equilibria in solution, and which we apply to molybdenum and tungsten isopolyoxoanions (IPAs). Starting from the MO4 monomers, and considering dimers, trimers, and larger species, the chemical reaction networks involved in the formation of [H32Mo36O128]8- and [W12O42]12- are sampled in an automatic manner. This information is used for setting up ∼105 speciation models, and from there, we generate the speciation phase diagrams, which show an insightful picture of the behavior of IPAs in aqueous solution. Furthermore, we predict the values of 107 formation constants for a diversity of molybdenum and tungsten molecular oxides. Among these species, we could include several pentagonal-shaped species and very reactive tungsten intermediates as well. Last but not least, the calibration employed for correcting the density functional theory (DFT) Gibbs energies is remarkably similar for both metals, which suggests that a general rule might exist for correcting computed free energies for other metals.

Unveiling a Photoinduced Hydrogen Evolution Reaction Mechanism via the Concerted Formation of Uranyl Peroxide.

We present a density functional theory study for the photochemical water oxidation reaction promoted by uranyl nitrate upon sunlight radiation. First, we explored the most stable uranyl complex in the absence of light. The reaction in a dark environmen proceeds through the condensation of uranyl monomers to form dimeric hydroxo-bridged species, which is the first step toward a hydrogen evolution reaction (HER). We found a triplet-state-driven mechanism that leads to the formation of uranyl peroxide and hydrogen gas. To describe in detail this reaction path, we characterized the singlet and triplet low-lying states of the dimeric hydroxo-bridged species, including minima, transition states, minimal energy crossing points, and adiabatic energies. Our computational results provide mechanistic insights that are in good agreement with the experimental data available.

Performance of group additivity methods for predicting the stability of uranyl complexes.

Herein, we investigated the viability of two group additivity methods for predicting Gibbs energies of a set of uranyl complexes. In first place, we proved that both density functional theory (DFT)-based methods and Serezhkin's stereoatomic model provide equivalent answers in terms of stability. Moreover, we proposed a novel methodology based on Mayer's population analysis for estimating Serezhkin's empirical parameters theoretically. On the other hand, we showed that Cheong and Persson linear algebra methodology can be successfully applied to uranyl complexes, and analyzed its performance in connection with the chemical nature of the compounds employed in the model.

Nucleation mechanisms and speciation of metal oxide clusters.

The self-assembly mechanisms of polyoxometalates (POMs) are still a matter of discussion owing to the difficult task of identifying all the chemical species and reactions involved. We present a new computational methodology that identifies the reaction mechanism for the formation of metal-oxide clusters and provides a speciation model from first-principles and in an automated manner. As a first example, we apply our method to the formation of octamolybdate. In our model, we include variables such as pH, temperature and ionic force because they have a determining effect on driving the reaction to a specific product. Making use of graphs, we set up and solved 2.8 × 105 multi-species chemical equilibrium (MSCE) non-linear equations and found which set of reactions fitted best with the experimental data available. The agreement between computed and experimental speciation diagrams is excellent. Furthermore, we discovered a strong linear dependence between DFT and empirical formation constants, which opens the door for a systematic rescaling.

Strategic Capture of the {Nb7 } Polyoxometalate.

Group V Nb-polyoxometalate (Nb-POM) chemistry generally lacks the elegant pH-controlled speciation exhibited by group VI (Mo, W) POM chemistry. Here three Nb-POM clusters were isolated and structurally characterized; [Nb14 O40 (O2 )2 H3 ]14- , [((UO2 )(H2 O))3 Nb46 (UO2 )2 O136 H8 (H2 O)4 ]24- , and [(Nb7 O22 H2 )4 (UO2 )7 (H2 O)6 ]22- , that effectively capture the aqueous Nb-POM species from pH 7 to pH 10. These Nb-POMs illustrate a reaction pathway for control over speciation that is driven by counter-cations (Li+ ) rather than pH. The two reported heterometallic POMs (with UO2 2+ moieties) are stabilized by replacing labile H2 O/HO-Nb=O with very stable O=U=O. The third isolated Nb-POM features cis-yl-oxos, prior observed only in group VI POM chemistry. Moreover, with these actinide-heterometal contributions to the burgeoning Nb-POM family, it now transects all major metal groups of the periodic table.