Issue 35, 2024

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 phase diagram under varying [Mo]/[P] ratios vs. pH. Our findings align well with experimental data, indicating the prevalence of the Keggin {PMo12} as the primary species at low pH, but the lacunary {PMo11}and Strandberg {P2Mo5} anions also emerge as major species at other concentration ratios. Finally, from 7 × 104 speciation models we inferred a plausible reaction network across the diverse nuclearities present within the system, which underlines the role of trimers as key intermediate building blocks.

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

Supplementary files

Transparent peer review

To support increased transparency, we offer authors the option to publish the peer review history alongside their article.

View this article’s peer review history

Article information

Article type
Edge Article
Submitted
20 May 2024
Accepted
23 Jul 2024
First published
27 Jul 2024
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2024,15, 14218-14227

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

J. Buils, D. Garay-Ruiz, M. Segado-Centellas, E. Petrus and C. Bo, Chem. Sci., 2024, 15, 14218 DOI: 10.1039/D4SC03282A

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. You can use material from this article in other publications, without requesting further permission from the RSC, provided that the correct acknowledgement is given and it is not used for commercial purposes.

To request permission to reproduce material from this article in a commercial publication, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party commercial publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements