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SMU Chemist and Colleagues Develop Machine Learning Model for Atomic-level Interactions

Machine learning interatomic potentials (MLIP)s have become an efficient and less expensive alternative to traditional quantum chemical simulations.

Oak ridgeUnited statesRyan jadrichOlexandr isayevSergei tretiakKipton barrosJustin smithElfi krakaRichard messerlyErin prather staffordShuhao zhangBenjamint nebgenNicholas lubbersOak ridge national laboratoryNational science foundationCarnegie mellon university

SMU Chemist Leads in Creating Machine Learning Model for Atoms

SMU Chemist Leads in Creating Machine Learning Model for Atoms
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Oak ridgeUnited statesOlexandr isayevKipton barrosElfi krakaNicholas lubbersRyan jadrichJustin smithShuhao zhangRichard messerlySergei tretiakBenjamint nebgenOak ridge national laboratoryNational science foundationComputational and theoretical chemistry groupCarnegie mellon university