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

Florian P. Lindner, Nina Strasser, Martin Schultze, Sandro Wieser, Christian Slugovc, Kareem Elsayad, Kristie J. Koski, Egbert Zojer, Caterina Czibula
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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.
结合布里渊光谱学和机器学习原子间电位来探测金属有机框架的机械特性
金属有机框架(MOFs)的力学性能具有很高的基础性和实用性。布里渊散射是确定各向异性弹性张量的一种特别有趣的技术,但迄今为止还很少用于 MOFs 这种高度复杂的材料。在本论文中,我们应用这种技术研究了一种新合成的 MOF 类材料,即 GUT2。我们的研究表明,将实验与最先进的弹性特性和声子带模拟(基于机器学习力场和弥散校正密度函数理论)相结合,可以全面理解实验结果。这样就能全面了解与纵向和横向声速相关的实验信号。此外,即使在处理限制了可获得的实验数据范围的相当小的单晶体时,结合模拟和实验的见解也能确定所研究材料的弹性张量分量的近似值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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