Simulating MOFs
Metal-organic frameworks (MOFs) have extraordinary properties due to their unique structure in the form of microporous crystals, which have a very large surface area despite their small size. This makes them extremely interesting for research and practical applications, such as gas storage, heat conduction and CO2 sequestration, for example. However, MOFs are very complex systems that have so far required a great deal of time and computing power to simulate accurately. Now, a team led by Egbert Zojer from the Institute of Solid State Physics at Graz University of Technology (TU Graz; Austria; www.tugraz.at) has significantly improved these simulations using machine learning, which greatly accelerates the development and application of novel MOFs. The researchers published their method in the Nature journal, npj Computational Materials. ❐