Machine Learning and Theoretical Prediction of Highly Spin‐Polarized Cr2COx MXene with Enhanced Curie Temperature

2D magnetic materials with high spin polarization and Curie temperature are highly desirable for ultrathin spintronic devices. This study utilizes first‐principles methods to systematically investigate 225 O adsorption configurations, demonstrating that Cr2COx MXene consistently maintains a long‐range‐ordered ferromagnetic arrangement with high spin polarization, irrespective of the O adsorption configuration. Most configurations also display Curie temperature (TC) exceeding room temperature, with the possibility of further enhancement by reducing O coverage. Machine learning models are developed to accurately predict O adsorption configurations, exchange interaction energies, and TC. A novel approach of stripping F and OH groups to create Cr2COx on Cr‐based MXene surfaces is proposed to address the difficulty in achieving long‐range‐ordered magnetic structures by manipulating surface adsorbates in MXene. This approach enhances the ability to control the magnetic properties of MXenes and paves the way for their application in ultrathin spintronic devices. 2D magnetic materials with high spin polarization and Curie temperature are ideal for ultrathin spintronic devices. This study, integrating first‐principles calculations with machine learning methods, demonstrates that Cr2COx MXene consistently exhibits high spin polarization and elevated Curie temperatures across various O adsorption configurations. These findings highlight Cr2COx MXene as a promising candidate for advanced ultrathin spintronic applications.