Wenhui Jin, Ping Wang, Xiaopeng An, Congcong Zhu, Yongfei Li, Yan Wang
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引用次数: 0
Abstract
Efficient microwave absorbers are needed to address the electromagnetic pollution caused by the proliferation of new radio technologies and equipment. Excellent microwave absorption performance can be achieved by controlling the dielectric constant. Heteroatom-doped bimetallic materials are promising electromagnetic wave absorption (EMA) materials due to their tunable structures and low cost. In particular, the presence of anionic sites significantly affects their dielectric constant and electrical conductivity. Herein, a 1D carbon nanofiber material is prepared by encapsulating FeCo nanoparticles in a fiber cavity by electrostatic spinning. Subsequently, tellurization, vulcanization, and selenization processes are carried out. FeTe2/ CoTe2@C exhibits stronger conductivity and dielectric loss due to the lower electronegativity of Te. The clever configuration of FeTe2, CoTe2, and C heterostructures obtained by Te doping generates multi-heterogeneous interfaces that facilitate charge migration and enhance interfacial polarization, obtaining excellent EMA performance. FeTe2/CoTe2@C exhibits an optimum minimum reflection loss (RLmin) of -51.1 dB with a matching thickness of 2.0 mm, and the effective absorption bandwidth (EAB) reaches 4.2 GHz. Radar cross-section (RCS) calculations show the great potential of FeTe2/CoTe2@C for practical military stealth technology. This study offers novel guidance for improving the EMA properties of transition metal matrix composites via anionic coordination modulation.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.