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GNoME AI From DeepMind Invents Millions Of New Materials
Science fiction authors are famous for their clever innovation in the design of fictional materials; see a long list at Dictionary of Material Terms in Science Fiction.
It appears, however, that the legendary creativity of our finest human authors pales against the mathematical indefatigability of GNoME. GNoME, which stands for Graph Networks for Materials Exploration, trained on data from the Materials Project, an open-access database founded at the Lawrence Berkeley National Laboratory.
“GNoME’s discovery of 2.2 million materials would be equivalent to about 800 years’ worth of knowledge and demonstrates an unprecedented scale and level of accuracy in predictions,” Amil Merchant and Ekin Dogus Cubuk, study authors and Google DeepMind researchers, add.
(Via FreeThink)
Consider, for example, super light materials. Science fiction authors take a back seat to no one for creating evocative names for such fictional materials. Consider alohydrolium from Ralph 124c 41 + (1911) by Hugo Gernsback, lux from The Black Star Passes (1930) by John W. Campbell, helio-beryllium from Out Around Rigel (1931) by Robert H. Wilson, sodaluminum from Exiles of the Moon (1931) by Nat Schachner (w. AL Zagat) and harbenite from Tarzan at the Earth's Core (1929) by Edgar Rice Burroughs. And don't forget nothing from It was Nothing - Really! (1969) by Theodore Sturgeon.
All told, GNoME predicted 2.2 million new materials. Of those, around 380,000 are considered the most stable and will be prime candidates for synthesis moving forward. Examples of these potential inorganic crystals include layered, graphene-like compounds that may help develop advanced superconductors, and lithium-ion conductors that could improve battery performance.
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