Magnetization reversals in core-shell sphere clusters: finite-element micromagnetic simulation and machine learning analysis.

Recently developed permanent magnets, featuring specially engineered microstructures of inhomogeneous magnetic phases, are being considered as cost-effective alternatives to homogeneous single-main-phase hard magnets composed of Nd2Fe14B, without compromising performance. In this study, we conducted a comprehensive examination of a core-shell sphere cluster model of Ce-substituted inhomogeneous Nd2-δCeδFe14B phases versus homogeneous magnetic phases, utilizing finite-element micromagnetic simulation and machine learning methods. This involved a meticulous, sphere-by-sphere analysis of individual demagnetization curves calculated from the cluster model. The grain-by-grain analyses unveiled that these individual demagnetization curves can elucidate the overall magnetization reversal in terms of the nucleation and coercive fields for each sphere. Furthermore, it was observed that Nd-rich spheres exhibited much broader ranges of nucleation and coercive field distributions, while Nd-lean spheres showed relatively narrower ranges. To identify the key parameter responsible for the notable differences in the nucleation fields, we constructed a machine learning regression model. The model utilized numerous hyperparameter sets, optimized through the very fast simulated annealing algorithm, to ensure reliable training. Using the kernel SHapley Additive eXplanation (SHAP) technique, we inferred that stray fields among the 11 parameters were closely related to coercivity. We further substantiated the machine learning models' inference by establishing an analytical model based on the eigenvalue problem in classical micromagnetic theory. Our grain-by-grain interpretation can guide the optimal design of granular hard magnets from Nd2Fe14B and other abundant rare earth transition elements, focusing on extraordinary performance through the careful adjustment of microstructures and elemental compositions.

Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing.

The macroscopic properties of permanent magnets and the resultant performance required for real implementations are determined by the magnets' microscopic features. However, earlier micromagnetic simulations and experimental studies required relatively a lot of work to gain any complete and comprehensive understanding of the relationships between magnets' macroscopic properties and their microstructures. Here, by means of supervised learning, we predict reliable values of coercivity (µ0Hc) and maximum magnetic energy product (BHmax) of granular NdFeB magnets according to their microstructural attributes (e.g. inter-grain decoupling, average grain size, and misalignment of easy axes) based on numerical datasets obtained from micromagnetic simulations. We conducted several tests of a variety of supervised machine learning (ML) models including kernel ridge regression (KRR), support vector regression (SVR), and artificial neural network (ANN) regression. The hyper-parameters of these models were optimized by a very fast simulated annealing (VFSA) algorithm with an adaptive cooling schedule. In our datasets of randomly generated 1,000 polycrystalline NdFeB cuboids with different microstructural attributes, all of the models yielded similar results in predicting both µ0Hc and BHmax. Furthermore, some outliers, which deteriorated the normality of residuals in the prediction of BHmax, were detected and further analyzed. Based on all of our results, we can conclude that our ML approach combined with micromagnetic simulations provides a robust framework for optimal design of microstructures for high-performance NdFeB magnets.

Spin-wave duplexer studied by finite-element micromagnetic simulation.

We conceptually designed a robust nano-scale waveguide structure suitable for potential use as a spin-wave duplexer that allows signal propagation only of selected narrow-band frequencies and duplex transmission in a three-port device comprising a receiver, a transmitter, and their common antenna. The waveguide structure combines three different arms and a circular ring, both made of nanostrip waveguides and a single magnetic material for reliably controllable propagations of spin waves. We attribute the observed duplex transmission of spin waves of narrow pass bands to scattering of spin waves by edge solitons placed at contact areas between the arms and the circular ring. This work proposes the first concept of nano-scale magnonic duplexers operating beyond GHz-frequency ranges.

Initial effect of an elastic chest band during inspiratory exercise on chest function improvement in people with limited rib mobility: a randomized controlled pilot trial.

BACKGROUND AND PURPOSE: While performing respiratory training, an elastic chest band has great benefits for clinical use due to its safety and easy application. However, to our knowledge, there is no published data on the clinical use of an elastic chest band into inspiratory training for people with limited rib mobility. This study aimed to investigate the effects of an elastic chest band integrated into inspiratory exercise for people with decreased chest function. METHOD: Sixteen subjects with limited rib mobility were randomly assigned to either experimental group (EG) or control group (CG), with eight subjects in each group. All subjects received an inspiratory exercise using incentive spirometer for 30 minutes. For the subjects of the EG, an elastic chest band was incorporated into the inspiratory exercises to provide compressive resistance to the chest. The chest function was measured using an electronic spirometer to determine the vital capacity (VC), tidal volume (TV), inspiratory reserve volume (IRV), expiratory reserve volume, forced vital capacity (FVC), forced expiratory volume (FEV), FEV in 1-second (FEV1) and the ratio of FEV1 to FVC (FEV1 %). RESULTS: Significant differences were found for the VC, TV, IRV, FVC and FEV1 between pre-test and post-test in the two groups (p < 0.05). Further, the changes in the values of VC (0.47 L vs. 0.22 L), FVC (0.55 L vs. 0.25 L) and FEV1 (0.65% vs. 0.21%) in the EG subjects were significantly greater than those in the CG subjects (p < 0.05). CONCLUSIONS: These findings suggest that an elastic chest band combined with inspiratory exercise produces additional positive effect on improving chest function in people with limited rib mobility.