Study on wave absorption characteristics and optimization of multilayer structure of two-dimensional Ti3C2Tx-MXenes material

2D transition metal Ti₃C₂Tx-MXene, a new type of graphene-like two-dimensional material, had shown excellent properties and potential application prospects in the field of microwave absorbing materials due to its special structure, physical and chemical properties. However, at present, most scholars pay attention to the synthesis of Ti₃C₂Tx, but the mechanism of absorbing properties of its multilayer structure is still unclear. Further studies are needed to improve the absorbing properties of MXene materials. Herein, the multilayer Ti₃C₂Tx-Mxene material are prepared by etching Ti₃AlC₂, and its physical properties are characterized and analyzed. Then the transmission line method (TLM) and the four-terminal network equivalence (FTNE) are used to study the relationship between the reflection loss and the thickness of the material. Finally, the absorbing performance of single multilayer Ti₃C₂Tx particles was simulated by COMSOL software in nanometer space, and the particle swarm optimization (PSO) algorithm was used to optimize the calculation and analysis of single multilayer Ti₃C₂Tx particles. The result showed that: when 50% of the paraffin-based material is mixed with Ti₃C₂Tx and the thickness is 3.5 mm, it has a strong microwave absorption performance and a large effective absorption bandwidth. The reflection loss RL_min reaches − 56.76 dB at 5.97 GHz, and the effective absorption bandwidth is 1.87 GHz. The microwave absorption performance of multilayer Ti₃C₂Tx in nano-sized space was analyzed by four-terminal network equivalence and COMSOL simulation. The absorbing performance of single multilayer Ti₃C₂Tx particles decreases with the increase of the number of layers, but tends to be relatively stable after 50 layers, and the reflectivity does not change significantly with the increase of layers. In addition, the reflectivity of multi-layer Ti₃C₂Tx is − 6.40 ~ − 9.47 dB optimized by particle swarm optimization (PSO) algorithm.