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

Translated title of the contribution: A Reaction Kinetic Model of Nano Al-PTFE Composite from Chemical Reaction Neural Networks

Ya Bei Xu, Qing Zhao Chu, Dong Ping Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

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.

Translated title of the contributionA Reaction Kinetic Model of Nano Al-PTFE Composite from Chemical Reaction Neural Networks
Original languageChinese (Traditional)
Pages (from-to)800-810
Number of pages11
JournalHuozhayao Xuebao/Chinese Journal of Explosives and Propellants
Volume44
Issue number6
DOIs
Publication statusPublished - Dec 2022

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Xu, Y. B., Chu, Q. Z., & Chen, D. P. (2022). 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. Huozhayao Xuebao/Chinese Journal of Explosives and Propellants, 44(6), 800-810. https://doi.org/10.14077/j.issn.1007-7812.202108038