Bioinspired Hollow/Hollow Architecture with Flourishing Dielectric Properties for Efficient Electromagnetic Energy Reclamation Device

The exploitation of advanced electromagnetic functional devices is perceived as the effective prescription to deal with environmental contamination and energy deficiency. From the perspective of observing and imitating nature, pine branch-like zirconium dioxide/cobalt nanotubes@nitrogen-doped carbon nanotubes are synthesized victoriously through maneuverable electrospinning process and follow-up thermal treatments. In particular, introducing carbon nanotubes on the surface of hollow nanofibers to construct hierarchical architecture vastly promoted the material's dielectric properties by significantly augmenting specific surface area, generating abundant heterogeneous interfaces, and inducing the formation of defects. Supplemented by the synergistic effect between each constituent, ultra-strong attenuation capacity and perfect impedance matching characteristics are implemented simultaneously, and jointly made contributions to the splendid microwave absorption performance with a minimum reflection loss of -67.9 dB at 1.5 mm. Moreover, this fibrous absorber also exhibited promising potential to be utilized as a green and efficient electromagnetic interference shielding material when the filler loading is enhanced. Therefore, this design philosophy is destined to inspire the future development of energy conversion and storage devices, and provide theoretical direction for the creation of sophisticated electromagnetic functional materials. Inspired by bionics, a unique hollow/hollow architecture with flourishing dielectric properties is designed for an efficient electromagnetic energy reclamation device. Through electrospinning and follow-up thermal treatments, carbon nanotubes are grown in situ on the surface of zirconium dioxide/cobalt nanotubes, successfully satisfying the requirements of "efficient, broadband, and lightweight" for new-generation dielectric-dominated microwave absorbent.image