High-frequency absorption and shielding of the Ni0.5Zn0.5Fe2O4 spinel ferrite ceramics: synergy effect of domain wall and grain boundary contributions
Source abstract
Abstract
A method allowing quantitative estimation of the magnetic and dielectric contributions to the free-space shielding efficiency, microwave absorption and attenuation coefficient of magnetic dielectrics in the high-frequency range (HF, 100 kHz – 3 GHz) is proposed. The method is based on the independent measurements of the complex HF dielectric permittivity and magnetic permeability used for further model calculations. This method is applied to the Ni 0.5 Zn 0.5 Fe 2 O 4 (NZF) spinel ferrite ceramics. Both dielectric grain boundary (GB) and magnetic domain wall (DW) dynamics are found to contribute to the HF absorption and shielding parameters of NZF. High values of permittivity and permeability, and their dispersion in the HF range provide synergistic values of the complex refractive index, attenuation coefficient and penetration depth. Very high values of loss tangent and attenuation coefficient (up to ∼600 m −1 at 1 GHz) of NZF evidence a high absorption of electromagnetic (EM) radiation above 100 MHz. Overlapping of the magnetodielectric resonances (tunable by the thickness of the NZF layer), dielectric and magnetic loss mechanisms and high value of the refractive index are shown to be responsible for broad frequency bands of the enhanced shielding efficiency and microwave absorption. For comparison, the same parameters were estimated also for the non-magnetic ZnFe 2 O 4 spinel ferrite ceramics. The synergy of magnetic DW and dielectric GB excitations interacting with EM waves allow us to consider Ni 0.5 Zn 0.5 Fe 2 O 4 as a promising polycrystalline magnetic dielectric for microwave applications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Magnetic Properties and Synthesis of Ferrites · Electromagnetic wave absorption materials · Metallic Glasses and Amorphous Alloys
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (37)
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