Combining Brillouin spectroscopy and machine learned interatomic potentials to probe mechanical properties of metal organic frameworks

TL;DR

This study integrates Brillouin spectroscopy with machine-learned interatomic potentials and DFT simulations to analyze the elastic properties of a new MOF material, GUT2, providing detailed insights into its anisotropic elasticity.

Contribution

It introduces a combined experimental and computational approach using Brillouin scattering and machine learning-based simulations to determine elastic tensors of complex MOFs.

Findings

Successful application of Brillouin scattering to a complex MOF

Correlation of experimental signals with sound velocities

Approximate elastic tensor components derived from combined methods

Abstract

The mechanical properties of metal-organic frameworks (MOFs) are of high fundamental and also practical relevance. A particularly intriguing technique for determining anisotropic elastic tensors is Brillouin scattering, which so far has rarely been used for highly complex materials like MOFs. In the present contribution, we apply this technique to study a newly synthesized MOF-type material, referred to as GUT2. We show that when combining the experiments with state-of-the-art simulations of elastic properties and phonon bands (based on machine-learned force fields and dispersion-corrected density-functional theory). This provides a comprehensive understanding of the experimental signals, which are correlated with the longitudinal and transverse sound velocities. Moreover, even when dealing with comparably small single crystals, which limit the range of accessible experimental data, combining the insights from simulations and experiments allows the determination of approximate values for the components of the elastic tensor of the studied material.