Статья

Atomic‐Molecular Engineering Tailoring Graphene Microlaminates to Tune Multifunctional Antennas

Jin‐Cheng ShuSchool of Materials Science and Engineering Beijing Institute of Technology Beijing 100081 P. R. ChinaMao‐Sheng CaoSchool of Materials Science and Engineering Beijing Institute of Technology Beijing 100081 P. R. ChinaYan‐Lan ZhangSchool of Materials Science and Engineering Beijing Institute of Technology Beijing 100081 P. R. ChinaYuze WangSchool of Materials Science and Engineering Beijing Institute of Technology Beijing 100081 P. R. ChinaQuanliang ZhaoSchool of Mechanical and Material Engineering North China University of Technology Beijing 100144 P. R. ChinaXiao‐Yong FangSchool of Science Yanshan University Qinhuangdao Qinhuangdao 066004 P. R. ChinaShuhui YangDepartment of Communication Engineering Communication University of China Beijing 100024 P. R. ChinaYong QinChinese Acad Sci Inst Coal Chem State Key Lab Coal Convers 27 Taoyuan South Rd Taiyuan Shanxi 030001 P. R. ChinaJie YuanSchool of Information Engineering Minzu University of China Beijing 100081 P. R. China

2023en

ABI

Аннотация

Abstract Atomic‐molecular engineering is an effective way to accurately tailor the microstructures and components of materials at the micro‐nano scale, which can be applied to flexibly manipulate their electromagnetic (EM) response. Herein, graphene microlaminates with multi‐layer structure are fabricated by atomic cluster engineering and oxidative molecular layer deposition for the first time. The microlaminates enable a tunable EM loss (from 0.93 to 3.94 for imaginary permittivity and from 0.17 to 0.25 for imaginary permeability) by changing poly(3,4‐ethylenedioxythiophene) cycles, and the attenuation constant reaches 160. On this basis, multifunctional antennas are conceived, achieving frequency‐selective response that enables steady harvest of > 90% of EM energy from signal source, and tactfully recycling waste heat energy and mechanical energy. This study will furnish a new horizon for information transmission and artificial intelligence in the future.

Перевод пока недоступен

Идентификаторы

DOI: 10.1002/adfm.202212379

Цитирования и источники

Цитирований: 3Использованных источников: 0

Показатели — AkademScholar