Correo Electrónico
DNINFOA - SIA
Bibliotecas
Convocatorias
Identidad U.N.
Published
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
DOI:
https://doi.org/10.15446/mo.n71.112866Keywords:
materiales magnéticos blandos, vidrios metálicos, impedancia, efecto piel, resonancia ferromagnética (es)soft magnetic materials, metallic glasses, impedance response, skin effect, ferromagnetic resonance (en)
Downloads
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.
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 DOI: https://doi.org/10.1063/1.112104
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 DOI: https://doi.org/10.1063/1.117312
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 DOI: https://doi.org/10.18257/raccefyn.1686
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 DOI: https://doi.org/10.1109/TMAG.2021.3138295
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
How to Cite
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Download Citation
License
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Those authors who have publications with this journal, accept the following terms:
a. The authors will retain their copyright and will guarantee the publication of the first publication of their work, which will be subject to the Attribution-SinDerivar 4.0 International Creative Commons Attribution License that permits redistribution, commercial or non-commercial, As long as the Work circulates intact and unchanged, where it indicates its author and its first publication in this magazine.
b. Authors are encouraged to disseminate their work through the Internet (eg in institutional telematic files or on their website) before and during the sending process, which can produce interesting exchanges and increase appointments of the published work.
