Machine learning methods are now used in the simulation of the building blocks of matter: from the electronic- to the molecular-level structure. These tools have boosted well-known computational methods such as density functional theory or molecular dynamics simulation, and are expected to lead to new physical insights which, in turn, can enable the engineering of exotic new materials.
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