Published

2025-07-22

RESPUESTA DE IMPEDANCIA DE LAS CINTAS AMORFAS Fe70Nb10B20 Y [(Fe50Co50)75B20Si5]96Nb4 OBTENIDA POR MEDIO DE LA RESONANCIA DE UN PEQUEÑO SOLENOIDE

IMPEDANCE RESPONSE OF THE AMORPHOUS RIBBONS Fe70Nb10B20 AND [(Fe50Co50)75B20Si5]96Nb4 OBTAINED BY RESONANCE OF A SMALL SOLENOID

Keywords:

materiales magnéticos blandos, vidrios metálicos, impedancia, efecto piel, resonancia ferromagnética (es)
soft magnetic materials, metallic glasses, impedance response, skin effect, ferromagnetic resonance (en)

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En este trabajo, presentamos un estudio de la respuesta de la impedancia longitudinal de muestras de los vidrios metálicos Fe70Nb10B20 y [(Fe50Co50)75B20Si5]96Nb4 mediante el uso de la resonancia de un solenoide pequeño. Las medidas de impedancia longitudinal en función de la frecuencia se realizaron en el rango de 0 < f < 30 MHz para campos magnéticos de HDC = 0,5, 10, 20, 30 y 40 Oe a temperatura ambiente. Las curvas obtenidas presentan incrementos en la amplitud de los picos de impedancia en torno a la región de resonancia del solenoide. Con base en esto, se propone un circuito equivalente y un ajuste polinómico generado por inteligencia artificial (IA) para modelar la respuesta de impedancia de estos sistemas.

In this work, we present a study of the longitudinal impedance response of samples of the metallic glasses Fe70Nb10B20 and [(Fe50Co50)75B20Si5]96Nb4 by using the resonance of a small solenoid. Longitudinal impedance measurements as a function of frequency were performed in the range 0 < f < 30 MHz for DC magnetic fields HDC = 0, 5, 10, 20, 30 and 40 Oe at room temperature. The curves obtained show increases in the amplitude of the impedance peaks around the solenoid resonance region. Based on this, an equivalent circuit and a polynomial adjustment generated by artificial intelligence (AI) are proposed to model the impedance response of these systems.

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References

A. Antonov, S. Gadetskii, and et al., Phys. Met. Metallogr. 83, 612 (1997). https://www.researchgate.net/publication/283167600_Giant_magnetoimpedance_in_amorphous_and_nanocrystalline_multilayers

F. L. A. Machado, C. S. Martins, and S. M. Rezende, Phys. Rev. B 51, 3926 (1995). https://journals.aps.org/prb/abstract/10.1103/PhysRevB.51.3926

L. V. Panina and K. Mohri, Appl. Phys. Lett. 65, 1189 (1994). https://pubs.aip.org/aip/apl/article-abstract/65/9/1189/64067/Magneto-impedance-effect-in-amorphous-wires?redirectedFrom=fulltext

M. Vázquez, J. Magn. Magn. Mater. 226-230, 693 (2001). https://www.sciencedirect.com/science/article/abs/pii/S0304885301000130?via%3Dihub

Z. C. Wang, F. F. Gong, and et al., J. Appl. Phys. 87, 4819 (2000). https://www.sciencedirect.com/science/article/abs/pii/S0304885301000130?via%3Dihub

Z. Wu, L. Liu, and et al., Physica B: Condens. Matter. 405, 327 (2010). https://www.sciencedirect.com/science/article/abs/pii/S0921452609008382?via%3Dihub

A. Yelon, D. Ménard, and et al., Appl. Phys. Lett. 69, 3084 (1996). https://www.sciencedirect.com/science/article/abs/pii/S0921452609008382?via%3Dihub

A. Rosales-Rivera, Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales 46, 656–674 (2022). https://raccefyn.co/index.php/raccefyn/article/view/exponentes_criticos_estaticos_efectos_de_anisotropia_hall_y_magn

A. Rosales R., R. F. González S., and et al., IEEE T. Magn. 57, 1 (2021). https://raccefyn.co/index.php/raccefyn/article/view/exponentes_criticos_estaticos_efectos_de_anisotropia_hall_y_magn

D. F. Gómez Montoya, Estudio de las propiedades magneto - eléctricas de materiales magnéticamente blandos en forma de cintas, basados en hierro (Tesis de Maestría. Universidad Nacional de Colombia (2015). https://repositorio.unal.edu.co/handle/unal/56233

Y. Zhang, D. Chen, and C. Ye, Toward Deep Neural Networks: WASD Neuronet Models, Algorithms, and Applications (2019). https://www.taylorfrancis.com/books/mono/10.1201/9780429426445/toward-deep-neural-networks-yunong-zhang-dechao-chen-chengxu-ye

O. Caylak and N. Derebasi, J. Optoelectronics Adv. Mat. 10, 2916 (2008). https://www.researchgate.net/publication/289567871_Prediction_of_giant_magneto_impedance_on_As-cast_and_post_production_treated_Fe43Co682Si125B15_amorphous_wires_using_neural_network

N. Derebasi, J. Supercond. Nov. Magn. 26, 1075 (2013). https://link.springer.com/article/10.1007/s10948-012-1923-4

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