A Machine Learning Approach to Decipher the Origin of Magnetic Anisotropy in Three-Coordinate Cobalt Single-Ion Magnets

Single Molecule Magnets (SMMs) emulate permanent magnets and are highly regarded for their role in compact information storage and molecular spintronics. Their behavior is primarily governed by magnetic anisotropy, expressed through parameters like the axial zero-field splitting (D) and orientation of magnetic anisotropy (gx, gy, gz) in mononuclear transition metal complexes. Low-coordinate mononuclear transition metal complexes stand out for their substantial anisotropy and higher blocking temperatures. However, understanding the intricate interplay between these parameters poses a significant challenge, often beyond traditional magneto-structural correlations. Hence, machine learning (ML) tools have been embraced to address these complexities. By employing an ML model based on Co-ligand bond length and angle relative to the pseudo-C3 axis, this study effectively rationalizes variations in D values, g-factors, and rhombic anisotropy, crucial for determining magnetic properties. Leveraging a dataset of 627 molecules, the research explores ML\u27s potential in predicting magnetic anisotropy parameters in three-coordinate Co(II) complexes, achieving a minimal mean absolute error (MAE) of approximately 17 cm⁻¹ and high accuracy levels exceeding 95% for classification tasks. These insights offer valuable guidance for the development of innovative single-ion magnets

Achieving Ambient Stability and Suppressing Spin-Phonon Coupling in Dyprosocenium SIMs via MOF Encapsulation

Detailed ab initio CASSCF calculations coupled with periodic DFT studies on [(Cp*)Dy(CpiPr5)]molecule encapsulated in a metal-organic framework found that MOF encapsulation offers stability to these fragile molecules keeping intact the Ueff values. Most importantly, this encapsulation suppresses the key vibrations responsible for reducing the blocking temperature offering a hitherto unknown strategy for a new generation of SIM-based devices