首页|Northwestern University Reports Findings in Machine Learning (Thermomechanical P roperties of Transition Metal Dichalcogenides Predicted by a Machine Learning Pa rameterized Force Field)
Northwestern University Reports Findings in Machine Learning (Thermomechanical P roperties of Transition Metal Dichalcogenides Predicted by a Machine Learning Pa rameterized Force Field)
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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 out of Evanston, Illinois, by NewsRx editors, research stated, “The mechanical and thermal propertiesof tran sition metal dichalcogenides (TMDs) are directly relevant to their applications in electronics,thermoelectric devices, and heat management systems. In this stu dy, we use a machine learning (ML)approach to parametrize molecular dynamics (M D) force fields to predict the mechanical and thermaltransport properties of a library of monolayered TMDs (MoS, MoTe, WSe, WS, and ReS).”
EvanstonIllinoisUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine Learning
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