Graph Neural Network for Metal Organic Framework Potential Energy Approximation: Energy Landscape Database and Rigidity

Metal Organic Frameworks (MOFs) are molecules that consist of metal ion clusters with organic ligands. Despite their widespread potential usage ranging from hydrogen storage to gas purification, MOFs are not predominately used in these sectors since they are mechanically unstable. To design these mechanical properties, a universal forcefield specific for MOFs is needed as well as a theory capable of assessing the mechanical stability given these forcefields. The forcefield for a single MOF is captured by a database of ground state energies vs atomic configurations. We have generated such a database using density functional theory(DFT) for the MOF, ‘FIGXAU’. In a second talk by Shehtab Zaman (Binghamton University), we will discuss the generation of a preliminary universal forcefield from this database. Finally, we show how a rigidity matrix formalism is ideally suited to studying the stability of MOFs and that MOFs in general are fine-tuned so that their nearest neighbor bonds, viewed as springs, are near the isostatic point in Maxwell constraint counting. We conclude with implications of our work for the design of MOFs for application purposes.