Additive Manufactured Multi-Material 3D metasurfaces for broadband achromatic electromagnetic focusing

• A multi-layer metasurface unit design based on equivalent circuit theory is proposed to achieve 17–35 GHz broadband achromatic electromagnetic focusing, with an effective bandwidth utilization of 69.2 %. • Nano Dimension DragonFly IV additive manufacturing technology is used to prepare complex multi-material metasurface structures with high precision, breaking through the limitations of traditional PCB processes. • Deep Conditional Generative Adversarial Network (DCGAN) is introduced to efficiently achieve reverse rapid design of metasurface structure parameters, significantly improving the efficiency of metasurface design. • The simulation and experimental results are highly consistent, demonstrating an innovative path for the deep integration of artificial intelligence and material design, and providing new ideas for the next generation of material design. In this paper, a broadband achromatic focusing metasurface design scheme based on the equivalent circuit theory and optimized by a deep learning method is proposed. The designed metasurface element consists of multilayer metal rings and a grounding layer, and the phase modulation effect of achromatic aberration in a wide frequency range is realized by precisely controlling the distance between the layers. The preparation of this complex structure is realized by using additive manufacturing technology, which effectively overcomes the limitations of traditional printed circuit board technology in manufacturing complex structures. To further improve the design efficiency, deep conditional generative adversarial network is introduced in this paper to quickly determine the structural parameters and realize the inverse design, which significantly improves the efficiency and accuracy of the metasurface structure design. The experimental results show that the metasurface possesses good focusing performance in the 17 to 35 GHz band with an effective bandwidth utilization of 69.2 %. The design method proposed in this study combines artificial intelligence and additive manufacturing technology, which provides new design ideas for applications in the fields of communication, optics and wireless energy transmission.