A Theoretical Approach for Computing Magnetic Anisotropy in Single Molecule Magnets

Abstract

We present a theoretical approach to calculate the molecular magnetic anisotropy parameters, $D_M$ and $E_M$ for single molecule magnets in any eigenstate of the exchange Hamiltonian, treating the anisotropy Hamiltonian as a perturbation. Neglecting inter-site dipolar interactions, we calculate molecular magnetic anisotropy in a given total spin state from the known single-ion anisotropies of the transition metal centers. The method is applied to $M{n}_{12}Ac$ and $F{e}_8$ in their ground and first few excited eigenstates, as an illustration. We have also studied the effect of orientation of local anisotropies on the molecular anisotropy in various eigenstates of the exchange Hamiltonian. We find that, in case of $M{n}_{12}Ac$, the molecular anisotropy depends strongly on the orientation of the local anisotropies and the spin of the state. The $D_M$ value of $M{n}_{12}Ac$ is almost independent of the orientation of the local anisotropy of the core $Mn(IV)$ ions. In the case of $F{e}_8$, the dependence of molecular anisotropy on the spin of the state in question is weaker.

8 pages, 12 figures, 2 tables

References in corpus (5)

• The origin of second-order transverse magnetic anisotropy in Mn12-acetate
• Quantum Coherence in Fe8 Molecular Nanomagnets
• Properties of low-lying states in some high-nuclearity Mn, Fe and V clusters: Exact studies of Heisenberg models
• Magnetic ordering, electronic structure and magnetic anisotropy energy in the high-spin Mn${}_{10}$ single molecule magnet
• Fully Symmetrized VB Based Technique for Solving Exchange Hamiltonians of Molecular Magnets

Cited by in corpus (4)

• Role of local short-scale correlations in the mechanism of negative magnetization
• Modeling Magnetic Anisotropy of Single Chain Magnets in $|d/J|\ge 1$ Regime
• Modeling Molecular Magnets with Large Exchange and On-Site Anisotropies
• Study of magnetization relaxation in molecular spin clusters using an innovative kinetic Monte Carlo method