首页|Harvard University Reports Findings in Machine Learning (Transferability and Acc uracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic Potentials)
Harvard University Reports Findings in Machine Learning (Transferability and Acc uracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic Potentials)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Cambridge, Massachusetts , by NewsRx journalists, research stated, “Ionic liquids (ILs) arean exciting c lass of electrolytes finding applications in many areas from energy storage to s olvents, wherethey have been touted as ‘designer solvents’ as they can be mixed to precisely tailor the physiochemicalproperties. As using machine learning in teratomic potentials (MLIPs) to simulate ILs is still relativelyunexplored, sev eral questions need to be answered to see if MLIPs can be transformative for ILs .”
CambridgeMassachusettsUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine Learning
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