Reaching quantum accuracy at the mesoscale in spatially disordered metal-organic frameworks by developing transferable interaction potentials based on active machine learning Ghent University
Metal-organic frameworks (MOFs) are modular networks made up of metallic bricks and organic ligands. These materials possess unique and interesting properties that make them highly promising for a myriad of applications in industry, e.g., gas sorption, catalysis and nanosensing devices. In the last decade, tremendous computational efforts were invested in attempts to unravel the mechanisms governing macroscopic MOF behaviour. However, current ...