Traditional math heavy calculations are just too slow
AI can help chemists crack the molecular structure of crystals much faster than traditional modelling methods, according to research published in Nature Communications on Monday.
Scientists from the Ecole Polytechnique Fédérale de Lausanne (EPFL), a research institute in Switzerland, have built a machine learning programme called ShiftML to predict how the atoms in molecules shift when exposed to a magnetic field.
Nuclear magnetic resonance (NMR) is commonly used to work out the structure of compounds. Groups of atoms oscillate at a specific frequencies, providing a tell-tale sign of the number and location of electrons each contains. But the technique is not good enough to reveal the full chemical structure of molecules, especially complex ones that can contain thousands of different atoms.
Another technique known as Density functional theory (DFT) is needed. It uses complex quantum chemistry calculations to map the density of electrons in a given area, and requires heavy computation.
