Séminaire IRFM – Machine learning and big computers are making atomistic simulation of materials [even more!] useful

Ever since the first supercomputers, classical molecular dynamics simulations (MD) of atomic trajectories have been used to gain unique insights into the behavior of materials.  However, for much of that time, the insights gained were purely qualitative, due to the limited accuracy of the interatomic potentials.

In the last decade, machine learning potentials and exascale computers have delivered the long-awaited best of both worlds: the accuracy of quantum methods and the scale of classical MD.

In his talk, Dr. Thompson will also put an emphasis on current and future applications to plasma-material interactions.

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