基于化学反应神经网络的纳米Al-PTFE复合体系反应动力学建模研究

To understand the chemical reaction mechanism of nano aluminum-polytetrafluoroethylene (Al-PTFE), based on the experimental data of thermogravimetry (TG), the chemical reaction neural network (CRNN) is used to model the reaction mechanism of nano Al-PTFE. The CRNN method can establish a kinetics model with 4 intermediate products and 4 reaction pathways at least, which is able to predict the TG curves of nano Al-PTFE. Combined with the existing kinetic process of Al-PTFE system, to speculate the main reaction pathways and intermediate products of the reaction system. The results show that there may be 5-step basic reactions in the pyrolysis process of Al-PTFE, the decomposition and gasification of C₂F₄, the breakage of Al₂O₃ film, the release of internal Al as the main reaction, and the activation energy is 200.9kJ/mol. Intermediate substances may include CF, CF₂, CF₃ and other substances, solid products are Al₄C₃ and C, and gaseous products may be CO₂ and CO. Chemical reaction neural network can model the pyrolysis reaction of nano Al-PTFE, and predict the possible reaction mechanism and corresponding kinetic parameters.