Davis Computational Spectroscopy workflow - from structure to spectra

Metal-organic frameworks (MOF) hold great promise in applications on gas adsorption and catalysis because of their porous structure and modularity. Despite having a symmetrical and apparently well-organized structure formed by metal clusters connected via organic linkers, these materials have low thermal, mechanical, and chemical stability, yielding a high defect density and disorder. To overcome the stability problem, a zirconium-based MOF called UiO-66 was presented as a solution due to its high connectivity with 12 connected clusters. However, a better understanding of the nature of defects and disorder in UiO-66 MOFs is still required.

Inelastic Neutron Scattering (INS) has been proven to be a good ally in the investigation of structural and dynamic disorder but it requires detailed modeling of the system to characterize peak positions and intensities, and subsequently materials properties. The high computational cost of the electronic modeling has limited investigations with INS to crystalline materials, dampening the study of disordered large systems such as MOFs.

To address the trade-off between simulation cost and accuracy, we developed an automated workflow that connects various atomic simulation tools in order to investigate the relationship between material properties, lattice dynamics, and INS spectra. This workflow allows an accurate and efficient method of calculating phonon modes and the INS spectrum with the use of a broad range of quantum mechanical approximations. We have implemented a machine-learned force field based on Chebyshev polynomials to improve the accuracy of the DFTB simulations with a 100x reduction in computational expense while retaining most of the accuracy of DFT. Besides the benefits of a tool that automates the simulation and consequent analysis of the INS spectrum, our efforts expand the possibilities of investigating more complex structures that would be unfeasible with ab initio methods.