首页|Investigators from Quzhou University Report New Data on Machine Learning (Machin e Learning and Theoretical Prediction of Highly Spin-polarized Cr2cox Mxene With Enhanced Curie Temperature)
Investigators from Quzhou University Report New Data on Machine Learning (Machin e Learning and Theoretical Prediction of Highly Spin-polarized Cr2cox Mxene With Enhanced Curie Temperature)
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Current study results on Machine Learn ing have been published. According to news reporting from Quzhou, People's Repub lic of China, by NewsRx journalists, research stated, "2D magnetic materials wit h high spin polarization and Curie temperature are highly desirable for ultrathi n spintronic devices. This study utilizes first-principles methods to systematic ally investigate 225 O adsorption configurations, demonstrating that Cr2COx MXen e consistently maintains a long-range-ordered ferromagnetic arrangement with hig h spin polarization, irrespective of the O adsorption configuration." Funders for this research include National Natural Science Foundation of China ( NSFC), Key Laboratory of Advanced Fuel Cells and Electrolyzers Technology of Zhe jiang Province. The news correspondents obtained a quote from the research from Quzhou Universit y, "Most configurations also display Curie temperature (T-C) exceeding room temp erature, with the possibility of further enhancement by reducing O coverage. Mac hine learning models are developed to accurately predict O adsorption configurat ions, exchange interaction energies, and T-C. A novel approach of stripping F an d OH groups to create Cr2COx on Cr-based MXene surfaces is proposed to address t he difficulty in achieving long-range-ordered magnetic structures by manipulatin g surface adsorbates in MXene."
QuzhouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningQuzhou University
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