Unveiling a Scaling and Universal Behavior for the Magnetocaloric Effect in Cubic Crystal Structures: A Monte Carlo Simulation.

The magnetocaloric effect and the universal character for the magnetic entropy change regarding the cubic crystal structures (SC, BCC, FCC) were investigated, in a qualitative way, using Monte Carlo simulations. A classical Heisenberg Hamiltonian with nearest neighbors, and next nearest neighbors interactions was implemented. In order to compute the critical temperature of the system depending on the coordination number, it was calculated the dependence of the magnetization and magnetic susceptibility as a function of temperature. Magnetic field dependence on the magnetization for isothermal processes was performed considering a magnetocrystalline anisotropy term. In this way, the magnetic entropy change (ΔSm) was computed. Results show that the rescaled ΔSm as well as the exponent (n) characterizing the field dependence of the magnetic entropy change curves, collapse onto a single curve for the studied crystal structures. By this reason, it can be assured that ΔSm exhibits a universal behavior regarding the strength and contribution of the magnetic exchange energy to the total magnetic energy.

Optimal phase space sampling for Monte Carlo simulations of Heisenberg spin systems.

We present an adaptive algorithm for the optimal phase space sampling in Monte Carlo simulations of 3D Heisenberg spin systems. Based on a golden rule of the Metropolis algorithm which states that an acceptance rate of [Formula: see text] is ideal to efficiently sample the phase space, the algorithm adaptively modifies a cone-based spin update method keeping the acceptance rate close to [Formula: see text]. We have assessed the efficiency of the adaptive algorithm through four different tests and contrasted its performance with that of other common spin update methods. In systems at low and high temperatures and anisotropies, the adaptive algorithm proved to be the most efficient for magnetization reversal and for the convergence to equilibrium of the thermal averages and the coercivity in hysteresis calculations. Thus, the adaptive algorithm can be used to significantly reduce the computational cost in Monte Carlo simulations of 3D Heisenberg spin systems.

Critical and compensation behavior of a mixed spin-5/2 and spin-3/2 Ising antiferromagnetic system in a core/shell nanowire.

In this work, Monte Carlo simulations based on metropolis algorithm were performed to study the critical and compensation temperatures of a core-shell nanowire with spins [Formula: see text] and [Formula: see text], respectively, considering an Ising antiferromagnetic system. The influence of nearest neighbors exchange interactions and crystal field anisotropy on the critical and compensation behaviors of the system has been analyzed. The effects of the nanowire height in the critical and compensation temperatures were evaluated. The results show that, for a system with given values of exchange interaction constants and crystal field anisotropy, a compensation point only appears if two requirements are satisfied. First, the weight of the core magnetization in the total magnetization must be greater than the weight of the shell magnetization at zero temperature. And second, the exchange constant of shell ions must be greater than a certain value. This value is, at the same time, greater than the exchange constant of core ions. The critical and compensation temperatures are very sensitive to variations in the exchange constant of the shell ions and core ions, respectively, while the crystal field anisotropy affects both temperatures.