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UID:ca0d5d70-5686-4aa8-ae6e-de1a25d52d02@support.access-ci.org
DTSTAMP:20261030T115129Z
DTSTART:20261102T203000Z
DTEND:20261102T230000Z
SUMMARY:ACES: Machine-Learned Potentials for Atomistic Simulation
DESCRIPTION:Machine-learned interatomic potentials are rapidly emerging too
 ls for atomistic simulation that offer first-principles accuracy at a frac
 tion of the computational cost. In this short course, we will introduce th
 e basic ideas behind machine-learned interatomic potentials and demonstrat
 e how to use several modern models, including MACE, AIMNet2, and UMA/FairC
 hem. Participants will learn how to set up these models, optimize molecula
 r structures, evaluate energies and forces, and use them in practical atom
 istic simulation workflows. Hands-on demonstrations will include examples 
 from both molecular and materials systems.Read more at https://hprc.tamu.e
 du/training/mlAtomicSimulation.html
URL:https://support.access-ci.org/events/9369
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