Scientist advance simulation of metal-organic frameworks with machine learning

Hydrogen storage, heat conduction, gas storage, CO2 and water sequestration—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. However, MOFs are very complex systems that have so far required a great deal of time and computing power to simulate accurately. Hydrogen storage, heat conduction, gas storage, CO2 and water sequestration—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. However, MOFs are very complex systems that have so far required a great deal of time and computing power to simulate accurately. Condensed Matter Phys.org – latest science and technology news stories