Magnetochemistry

16 pages, 2248 KB

Open AccessArticle

Core Loss Prediction Model of High-Frequency Sinusoidal Excitation Based on Artificial Neural Network

by Cunhao Lu, Fanjie Meng, Jiajie Zhang and Zeyuan Zhang

Magnetochemistry 2025, 11(11), 93; https://doi.org/10.3390/magnetochemistry11110093 (registering DOI) - 25 Oct 2025

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Abstract

The magnitude of core loss is a crucial factor affecting the efficiency of power converters. Due to the complex mechanism of core loss, diverse influencing factors, and the strong coupling characteristics between materials and operating conditions, traditional core loss prediction models struggle to achieve high-precision prediction of core loss. Based on the Artificial Neural Network (ANN), this paper investigates core loss under high-frequency sinusoidal excitation. The core loss training data is processed using a logarithmic transformation method, and an ANN core loss prediction model is established with temperature, frequency, and magnetic flux density as features. The results show that, compared with non-logarithmic processing, logarithmic transformation of the data can effectively improve the prediction accuracy (PA) of the ANN model. Within the ±10% error range, the maximum PA of the ANN prediction model reaches 98.48%, and the minimum Mean Absolute Percentage Error (MAPE) can be as low as 2.58%. In addition, a comparison with the Steinmetz Equation (SE) and K-nearest neighbor (KNN) prediction models reveals that, for four materials, within the ±10% error range of the true core loss values, the minimum PA of the ANN model is 93.33% with an average of 95.38%; the minimum PA of the KNN model is 43.94% with an average of 62.07%; and the minimum PA of the SE model is 14.91% with an average of 19.83%. Furthermore, the MAPE of the ANN model is within 5%. Full article

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16 pages, 17336 KB

Open AccessArticle

Effect of Magnetic Field on Electrochemical Corrosion Behavior of H62 Brass Alloy

by Hexiang Huang, Dazhao Yu, Hongjun Zhao, Aiguo Gao, Yanan Li and Jiantao Qi

Magnetochemistry 2025, 11(11), 92; https://doi.org/10.3390/magnetochemistry11110092 (registering DOI) - 24 Oct 2025

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Abstract

This study investigates the influence of magnetic fields on the electrochemical corrosion behavior of aerospace-grade H62 brass alloy in 3.5 wt% NaCl solution and its underlying 10 mechanisms. Employing electrochemical testing techniques combined with surface characterization methods, we explored the effects of magnetic field intensity (25–100 mT) and orientation (parallel and perpendicular to electrode surface) on the corrosion kinetics and corrosion product evolution of H62 brass alloy. Results demonstrate that magnetic fields significantly accelerate the corrosion process of H62 brass alloy. Under parallel magnetic field (100 mT), the corrosion current density increased from 0.49 μA/cm² to 3.66 μA/cm², approximately 7.5 times that of the non-magnetic condition, while perpendicular magnetic field increased it to 1.73 μA/cm², approximately 3.5 times the baseline value. The charge transfer resistance decreased from 3382 Ω·cm² to 1335 Ω·cm². Magnetic field orientation determines the fundamental differences in corrosion acceleration mechanisms. Parallel magnetic fields primarily enhance mass transfer processes through Lorentz force-driven magnetohydrodynamic (MHD) effects, resulting in intensified uniform corrosion; perpendicular magnetic fields alter interfacial ion distribution through magnetic gradient forces, inducing localized corrosion tendencies. Magnetic fields promote the transformation of protective Cu₂O films into porous Cu₂(OH)₃Cl, reducing the protective capability of corrosion product layers. Full article

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17 pages, 1816 KB

Open AccessArticle

Investigating Magnetic Nanoparticle–Induced Field Inhomogeneity via Monte Carlo Simulation and NMR Spectroscopy

by Song Hu, Yapeng Zhang and Bin Zhang

Magnetochemistry 2025, 11(11), 91; https://doi.org/10.3390/magnetochemistry11110091 - 23 Oct 2025

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Abstract

Magnetic nanoparticles (MNPs) perturb magnetic field homogeneity, influencing transverse relaxation and the full width at half maximum (FWHM) of nuclear magnetic resonance (NMR) spectra. In Nuclear Magnetic Resonance (NMR), this appears as decay of the free induction decay (FID) signal, whose relaxation rate determines spectral FWHM. In D₂O containing MNPs, both nanoparticles and solvent molecules undergo Brownian motion and diffusion. Under a vertical main field (

B_{0}

), MNPs respond to their magnetization behavior, evolving toward a dynamic steady state in which the time-averaged distribution of local field fluctuations remains stable. The resulting spatial magnetic field can thus characterize field homogeneity. Within this framework, Monte Carlo simulations of spatial field distributions approximate the dynamic environment experienced by nuclear spins. NMR experiments confirm that increasing MNP concentration and particle size significantly broadens FWHM, while stronger

B_{0}

enhances sensitivity to MNP-induced inhomogeneities. Full article

(This article belongs to the Section Magnetic Nanospecies)

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Magnetochemistry, Volume 11, Issue 11 (November 2025) – 3 articles

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