首页|New Machine Learning Findings from University of Twente Discussed (Phase Transitions of Lamno3 and Srruo3 From Dft + U Based Machine Learning Force Fields Simulations)
New Machine Learning Findings from University of Twente Discussed (Phase Transitions of Lamno3 and Srruo3 From Dft + U Based Machine Learning Force Fields Simulations)
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A new study on Machine Learning is now available. According to news reporting out of Enschede, Netherlands, by NewsRx editors, research stated, “Perovskite oxides are known to exhibit many magnetic, electronic, and structural phases as function of doping and temperature.” Financial support for this research came from Netherlands Organization for Scientific Research (NWO). Our news journalists obtained a quote from the research from the University of Twente, “These materials are theoretically frequently investigated by the DFT + U method, typically in their ground state structure at T = 0. We show that by combining machine learning force fields (MLFFs) and DFT + U based molecular dynamics, it becomes possible to investigate the crystal structure of complex oxides as function of temperature and U. Here, we apply this method to the magnetic transition metal compounds LaMnO3 and SrRuO3. We show that the structural phase transition from orthorhombic to cubic in LaMnO3, which is accompanied by the suppression of a Jahn-Teller distortion, can be simulated with an appropriate choice of U. For SrRuO3, we show that the sequence of orthorhombic to tetragonal to cubic crystal phase transitions can be described with great accuracy.”
EnschedeNetherlandsEuropeCyborgsEmerging TechnologiesMachine LearningUniversity of Twente
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