首页|Researchers from SRM Institute of Science and Technology De- scribe Findings in Machine Learning (Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides)
Researchers from SRM Institute of Science and Technology De- scribe Findings in Machine Learning (Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides)
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NETL
NSTL
Amer Chemical Soc
2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting out of Tamil Nadu, India, by NewsRx editors, research stated, “The computational design of suitable mul- tiferroic double perovskite oxides requires finding materials that exhibit sizable polarization, magnetization, and coupling between them. Oxides with the chemical formula of AA ‘ BB ‘ O-6 with building blocks of ABO(3) single perovskite oxides in centrosymmetric Pnma symmetry are strong candidates that have been reported to satisfy such criteria.” Funders for this research include United States Department of Energy (DOE), Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ORNL), United States Department of Energy (DOE), United States Department of Energy (DOE), National Supercomputing Mission.
Tamil NaduIndiaAsiaAnionsCyborgsEmerging TechnologiesMachine LearningOxidesOxygen CompoundsSRM Institute of Science and Technology
NETL
NSTL
Amer Chemical Soc
