Confined In-Situ Encapsulation of Co/C Composites with Increased Heterogeneous Interface Polarization for Enhanced Electromagnetic Performance

It is an urgent problem to realize reliable microwave absorption materials (MAMs) with low density. To address this issue, a series of controlled experiments w ere carried out, which indicated that the tubular structure enables excellent microwave absorption properties with a lower powder filling rate. This performance is attributable to the combined dielectric and magnetic loss mechanisms provided by Co/C and the interface polarization facilitated by multiple heterogeneous interfaces. Particularly, Co@C nanotubes, benefiting from the enhanced heterointerface polarization due to their abundant specific surface area and the reduced electron migration barrier induced by their 1D stacked structure, effectively achieved a dual enhancement of dielectric loss and polarization loss at lower powder filling ratios. Furthermore, the magnetic coupling effect of magnetic nanoparticle arrays in tubular structures is demonstrated by micromagnetic simulation, which have been few reported elsewhere. These propertied enable Co@C nanotubes to achieve minimum reflection loss and maximum effective absorption broadband values of 61.0 dB and 5.5 GHz, respectively, with a powder filling ratio of 20 wt% and a thickness of 1.94 mm. This study reveals the significance of designing 1D structures in reducing powder filling ratio and matching thickness, providing valuable insights for developing MAMs with different microstructures. Hollow structured 1D Co@C nanotubes are synthesized by utilizing CTAB micelle as sacrificial templates. These nanotubes possess a locally conductive network formed by their tubular structure, exceptional magnetic properties confirmed through micromagnetic simulation. Experimental outcomes and RCS simulation validate that the synergistic effect of multiple loss mechanisms and optimized impedance matching contributes to the outstanding electromagnetic wave absorption capabilities.image