Tunable 1D–2D Carbon Nanomaterials for Broadband and High-Performance Microwave Absorption via Ultrasonic Spray Ice Template
Maoyu Yi, Bo Liang, Hang Xiao, Wei Tan, Wenjie Yang, He Xian, Yijing Stehle, Jianghuai Hu, Ke Zeng, Gang Yang
Abstract
Polymer-based one- and two-dimensional (1D–2D) carbon nanomaterials are considered promising microwave-absorbing materials (MAMs) due to their high atomic utilization efficiency and tunable microscopic/macroscopic morphology. The tunable design of 1D–2D carbon nanomaterials through a facile method to meet the requirements of advanced MAMs remains a challenge. In this work, the environmentally friendly processing method of ultrasonic spray ice template (USIT) is employed to fabricate porous carbon nanomaterials based on Kapton-type polyimide, which exhibit the intriguing morphology of both 1D nanowires and 2D nanosheets. Under subsequent carbonization at 700 and 800 °C, the obtained carbon nanomaterials inherit the original morphology. Furthermore, the 1D or 2D nanomorphology can be readily controlled by adjusting the concentration of the precursor solution. For samples fabricated with lower precursor concentrations (0.1%), 1D nanowire structures are predominant. Interconnected conductive networks and heterogeneous interfaces are formed by intertwining and stacking nanowires, thereby enhancing the conductivity loss. Additionally, the abundant porous structure provides an effective channel for electromagnetic wave entrance, significantly improving the impedance matching ability. The results show that the 1D nanowire-dominated samples (700 °C carbonization) show excellent electromagnetic microwave absorption performance. The reflection loss minimum (RL min ) is −67.2 dB at 8.1 GHz and 4.65 mm, and the maximum effective absorption bandwidth (<−10 dB) is 7.7 GHz at 3.03 mm. Exemplified by MAMs, the USIT strategy has broad prospects, providing enormous potential for various practical applications and bridging the gap between polymer precursors and 1D/2D tunable carbon nanomaterials.