Issue 8, 2025

Prediction of NMR parameters and geometry in 133Cs-containing compounds using density functional theory

Abstract

The need to immobilize low-level nuclear waste, in particular 137Cs-bearing waste, has led to a growing interest in geopolymer-based waste matrices, in addition to optimization attempts of cement matrix compositions for this specific application. Although the overall phase composition and structure of these matrices are well characterized, the binding sites of Cs in these materials have not been clearly identified. Recent studies have suggested that combining the sensitivity of solid-state nuclear magnetic resonance (SSNMR) to the local atomic structure with other structural techniques provides insights into the mode of Cs binding and release. Density functional theory (DFT) can provide the connection between spectroscopic parameters and geometric properties. However, the reliability of DFT results strongly relies on the choice of a suitable exchange–correlation functional, which for 133Cs, the NMR surrogate for such studies, is not well-established. In this work we benchmark various functionals against their performance in predicting the geometry of various simple Cs compounds, their NMR quadrupolar coupling constants, and their chemical shift values, while prioritizing the ability to incorporate dispersion interactions and maintaining low computational cost. We examined Cs salts, Cs oxides, perovskites, caged materials, a borate glass and a cesium fluoroscandate. While no single functional performs equally well for all parameters, the results show rev-vdW-DF2 and PBEsol+D3 to be leading candidates for these systems, in particular with respect to geometry and chemical shifts, which are of high importance for Cs-immobilization matrices.

Graphical abstract: Prediction of NMR parameters and geometry in 133Cs-containing compounds using density functional theory

Supplementary files

Article information

Article type
Paper
Submitted
03 Sep 2024
Accepted
28 Jan 2025
First published
29 Jan 2025
This article is Open Access
Creative Commons BY-NC license

Phys. Chem. Chem. Phys., 2025,27, 4187-4201

Prediction of NMR parameters and geometry in 133Cs-containing compounds using density functional theory

N. Manukovsky, N. Vaisleib, M. Arbel-Haddad and A. Goldbourt, Phys. Chem. Chem. Phys., 2025, 27, 4187 DOI: 10.1039/D4CP03451A

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