Machine learning can be used to predict the properties of a group of materials which, according to some, could be as important to the 21st century as plastics were to the 20th.
Based on news that University of Cambridge published, Researchers have used machine learning techniques to accurately predict the mechanical properties of metal-organic frameworks (MOFs), which could be used to extract water from the air in the desert, store dangerous gases or power hydrogen-based cars.
The researchers, led by the University of Cambridge, used their machine learning algorithm to predict the properties of more than 3000 existing MOFs, as well as MOFs which are yet to be synthesised in the laboratory.
The results, published in the inaugural edition of the Cell Press journal Matter, could be used to significantly speed up the way materials are characterised and designed at the molecular scale.
MOFs are self-assembling 3D compounds made of metallic and organic atoms connected together. Like plastics, they are highly versatile, and can be customised into millions of different combinations. Unlike plastics, which are based on long chains of polymers that grow in only one direction, MOFs have orderly crystalline structures that grow in all directions.
This crystalline structure means that MOFs can be made like building blocks: individual atoms or molecules can be switched in or out of the structure, a level of precision that is impossible to achieve with plastics.
The structures are highly porous with massive surface area: a MOF the size of a sugar cube laid flat would cover an area the size of six football fields. Perhaps somewhat counterintuitively however, MOFs make highly effective storage devices. The pores in any given MOF can be customised to form a perfectly-shaped storage pocket for different molecules, just by changing the building blocks.
“That MOFs are so porous makes them highly adaptable for all kinds of different applications, but at the same time their porous nature makes them highly fragile,” said Dr David Fairen-Jimenez from Cambridge’s Department of Chemical Engineering and Biotechnology, who led the research.
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metal-organic frameworks (MOFs):
Metal–organic frameworks (MOFs) are a class of compounds consisting of metal ions or clusters coordinated to organic ligands to form one-, two-, or three-dimensional structures. They are a subclass of coordination polymers, with the special feature that they are often porous.
More formally, a metal–organic framework is a coordination network with organic ligands containing potential voids. A coordination network is a coordination compound extending, through repeating coordination entities, in one dimension, but with cross-links between two or more individual chains, loops, or spiro-links, or a coordination compound extending through repeating coordination entities in two or three dimensions; and finally a coordination polymer is a coordination compound with repeating coordination entities extending in one, two, or three dimensions.
Edited and contributed by: S. Marjani
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