With the development of the miniaturization of electronic equipment and lightweight weapon equipment, there are new requirements for electromagnetic wave absorption material (EMWAM). EMWAM has outstanding electromagnetic wave absorption properties and lightweight characteristics become an important direction of research. In this study, graphene/g-C₃N₄ (GGCN) EMWAM was first synthesized in situ by simple heat treatment, in which the g-C₃N₄ had a porous structure and dispersed on the surface of graphene. The impedance matching of the GGCN was well adjusted by decreasing the dielectric constant and attenuation constant due to the g-C₃N₄ semiconductor property and the graphite-like structure. The EMW loss mechanism of GGCN was also analyzed by simulating GGCN’s electric field mode distribution and resistance loss power density. The analysis result shows that the distribution of g-C₃N₄ among GGCN sheets can produce more polarization effects and relaxation effects by increasing the lamellar spacing. Furthermore, the polarization loss of GGCN could be increased successfully by porous g-C₃N₄. Ultimately, the EMW absorption property of GGCN is optimized significantly, and GGCN exhibits excellent EMW absorption performance. When the thickness is 2 mm, the effective absorption bandwidth (EAB) can reach 4.6 GHz, and when the thickness is 4.5 mm, the minimum reflection loss (RL_min) at 4.56 GHz can reach −34.69 dB. Moreover, the practical application of EMWAM was studied by radar cross-section (RCS) simulation, showing that GGCN has a good application prospect.

随着电子设备小型化和武器装备轻量化的发展，对电磁波吸收材料（EMWAM）提出了新的要求。EMWAM具有突出的电磁波吸收性能和轻量化特性成为重要的研究方向。本研究首次通过简单热处理原位合成了石墨烯/gC ₃ N _{4 (GGCN) EMWAM，其中gC 3} N ₄具有多孔结构并分散在石墨烯表面。_{由于gC 3} N ₄半导体特性和类石墨结构，通过降低介电常数和衰减常数，可以很好地调节GGCN的阻抗匹配。通过模拟GGCN的电场模式分布和电阻损耗功率密度，分析了GGCN的EMW损耗机理。_{分析结果表明，gC 3} N ₄分布在GGCN片之间，可以通过增加片层间距产生更多的偏振效应和弛豫效应。此外，多孔gC ₃ N ₄可以成功地增加GGCN的偏振损耗。最终，GGCN的EMW吸收性能得到显着优化，GGCN表现出优异的EMW吸收性能。当厚度为2 mm时，有效吸收带宽（EAB）可达4.6 GHz，当厚度为4.5 mm时，4.56 GHz处的最小反射损耗（RL _min）可达-34.69 dB。此外，通过雷达截面（RCS）仿真研究了EMWAM的实际应用，表明GGCN具有良好的应用前景。