Jing Lin, Yuhui Peng, Jingyuan Luo, Zhiqiang Xiong, Jun Huang, Xiaojun Zeng, Liping Wu, Jinbin Peng, Chongbo Liu
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引用次数: 0
Abstract
MXenes are 2D materials known for their unique electromagnetic wave absorption (EMWA) properties arising from their varied composition and structure. In this study, a one-step ice-assisted process is utilized to directly transform 2D MXene into 3D single-layer MXene aerogels (SMAs). Furthermore, the interlayer spacing of the SMAs is optimized by incorporating helical carbon nanotubes (HCNTs). Because of the van der Waals interaction between the MXene nanosheets and HCNTs, the assembled HCNT@MXene aerogels (HMAs) exhibited a regular porous structure and moderate conductivity, leading to significantly enhanced electromagnetic responses, as demonstrated by finite element simulation. The HMAs showed an exceptional EMWA, with a minimum reflection loss of -51.45 dB and an effective absorption bandwidth of 6.48 GHz at 3.0 wt.% filler ratio. Additionally, visualization of surface charge distribution and power loss density characteristics clarified the underlying EMWA mechanisms. By employing a hollow structure gradient metamaterial design, the effective EMWA bandwidth is further expanded to 13.98 GHz. Additionally, HMAs exhibited the maximum radar cross-section reduction values with 27.08 dB m2. Moreover, the HMAs exhibited excellent thermal insulation capability. This paper presents a straightforward yet effective method for fabricating MXene aerogels and offers valuable insights for the development and application of MXene-aerogel-based EMW absorbers.
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.