Magnetization reversal in conventional ferro‐ and ferrimagnetic materials takes place through the growth of the energetically favorable domain state, which occurs at the expense of the less favorable domain state. This process results in the cancellation of the overall magnetization when the coercive field is reached. The mechanisms of magnetization reversal are crucial for numerous applications. Interestingly, the ability to control domains on demand during magnetization reversal represents a significant area of innovation, specifically in the field of antiferromagnetic spintronics, which has rendered ferromagnetic and antiferromagnetic nanoparticles both intriguing and highly beneficial. Herein, we report an advanced numerical approach based on matrix continued fractions to investigate the dynamics of magnetization reversal in single‐domain ferromagnetic and antiferromagnetic nanoparticles. By averaging the Gilbert–Langevin equation for individual particles, we establish the equilibrium correlation's set of linear differential‐recurrence relations by passing the traditional Fokker–Planck equation. Solving this system enables us to determine the relaxation time. Building upon earlier studies, the present work extends the analysis to a multiobjective framework that simultaneously accounts for extreme damping, reduced energy barriers, and field orientation effects, enabling a unified and quantitative comparison of relaxation pathways in ferro‐ and antiferromagnetic nanoparticles beyond previously reported regimes. Furthermore, unlike nanoparticles with uniaxial anisotropy, we demonstrate an inherent geometric dependence of the time of relaxation on the parameter's damping, which results from the reciprocal exchange between the longitudinal and transverse relaxation modes. While similarities between ferromagnetic and antiferromagnetic relaxation times in the high‐damping regime have been reported previously, the present work provides a unified and systematic multiparameter analysis that clarifies the roles of damping, geometry, and field orientation within a single computational framework.
Alhashem et al. (Sun,) studied this question.