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Cited by 313

The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.

Graphene‐Based Materials toward Microwave and Terahertz Absorbing Stealth Technologies

Chen, Honghui, Ma, Wenle, Huang, Zhiyu, Zhang, Yi, Huang, Yi, Chen, Yongsheng·2019·Advanced Optical Materials

Abstract

Electromagnetic wave absorbing materials play an increasingly important role in consumer electronics and military defense. The remarkable merits of atomically thin graphene structures and their exotic optoelectronic properties provide new opportunities to design high‐performance electromagnetic wave absorbers. This progress report summarizes the recent advances in graphene‐based microwave and terahertz stealth materials. In the first section, the theory of electromagnetic wave absorption and the evaluation methods for absorption performance are briefly introduced. Then, representative graphene‐based microwave and terahertz absorber systems are presented with an emphasis on the selection of the absorbent component and structural design. In the last section, the perspectives and future research directions of this promising field are discussed.

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Crossref · 10.1002/adom.201801318

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Metadata

Authors
Chen, H., Ma, W., Huang, Z., Zhang, Y., Huang, Y., & Chen, Y.
Venue
Advanced Optical Materials
Publisher
Wiley
Published
2019-02-17
Volume
7
Issue
8
ISSN
2195-1071 (ISSN-L)
OpenAlex
W2915364460
Cited by
313
References
90
FWCI
10.91
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Graphene‐Based Materials toward Microwave and Terahertz Absorbing Stealth Technologies. https://app.cochat.ai/papers/10.1002/adom.201801318
The paper
Chen, H., Ma, W., Huang, Z., Zhang, Y., Huang, Y., & Chen, Y. (2019). Graphene‐Based Materials toward Microwave and Terahertz Absorbing Stealth Technologies. Advanced Optical Materials. https://doi.org/10.1002/adom.201801318

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.