Optimizing Heating Efficiency of Hyperthermia: Specific Loss Power of Magnetic Sphere Composed of Superparamagnetic Nanoparticles
Magnetic nanoparticle (MNP) based thermal therapies have shown importance in clinical applications. However, it lacks a compromise between its robustness and limitations. We developed theoretical strategies to enhance the heating efficiency, which could be utilized in thermal therapies and calculated parameter dependence for superparamagnetic MNPs (approximative ellipsoid-shaped) within a sphere-shaped ball. Then we calculated specific loss power (SLP) for magnetic particles in a magnetic ball. The dependency of features of the nanoparticles (such as mean particle size, a number of particles, frequency and the amplitude of the exposed field, relaxation time, and volume gap between particles and a sphere-shaped ball) on the SLP or the heating effect in superparamagnetic MNPs was analyzed. In this study, optimal parameter values were calculated using Kneedle Algorithm as the optimization technique to represent the accurate heating efficiency. The influence of a number of particles in a sphere-shaped ball shows that SLP of magnetic particles increases with the increasing number of particles (N); however, after N = 10 particles, the SLP increment is insignificant. The most remarkable result arising from this analysis is that when particles are more closer together (less volume gap of a sphere-shaped ball), high SLP is found for the same number of particles. This model also predicts that the frequency dependency on the SLP is negligible when the frequency is higher than 10 kHz depending on the size of a sphere-shaped ball and nanoparticle parameters. This analysis has shown that the SLP of MNPs in a sphere-shaped ball strongly depends on magnetic parameters and properties of the particles. In brief, we have demonstrated, for the first time, impact on SLP of the accumulation of ellipsoid-shaped superparamagnetic nanoparticles into a sphere-shaped ball. This finding has essential suggestions for developing links between heating properties with loose aggregate and dense aggregate scenarios in the superparamagnetic condition.