首页|Reports Outline Machine Learning Findings from North Dakota State University (No nadiabatic Dynamics In Two-dimensional Perovskites Assisted By Machine Learned F orce Fields)
Reports Outline Machine Learning Findings from North Dakota State University (No nadiabatic Dynamics In Two-dimensional Perovskites Assisted By Machine Learned F orce Fields)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Machine Learning have be en published. According to news reportingfrom Fargo, North Dakota, by NewsRx jo urnalists, research stated, “An exploration of the ‘on-the-fly’nonadiabatic cou plings (NACs) for nonradiative relaxation and recombination of excited states in 2D Dion-Jacobson (DJ) lead halide perovskites (LHPs) is accelerated by a machin e learning approach. Specifically,ab initio molecular dynamics (AIMD) of nanost ructures composed of heavy elements is performed with theuse of machine-learnin g force-fields (MLFFs), as implemented in the Vienna Ab initio Simulation Package (VASP).”
FargoNorth DakotaUnited StatesNort h and Central AmericaCyborgsEmerging TechnologiesMachine LearningMolecul ar DynamicsPhysicsNorth Dakota State University
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