AI looks into matter at microscopic level, could help design unique materials to tap clean energy

A team of scientists at the Artificial Intelligence company DeepMind may have found a new dimension into the world of Chemistry. The new understanding could help in the development of new materials needed for producing clean electricity or developing high-temperature superconductors in the 21st century. "Although DFT proves a mapping exists, for more than 50 years the exact nature of this mapping between electron density and interaction energy — the so-called density functional — has remained unknown and has to be approximated," DeepMind said in a statement. "By using a neural network to represent the functional and tailoring our training dataset to capture the fractional electron behaviour expected for the exact functional, we found that we could solve the problems of delocalization and spin symmetry-breaking," the company said. "As technology increasingly turns to the quantum scale to explore questions about materials, medicines, and catalysts, including those we’ve never seen or even imagined, deep learning shows promise to accurately simulate matter at this quantum mechanical level," scientists at DeepMind said.