Abstract:

The adiabatic accelerating rate calorimetry (ARC) mainly adopts model-fitting method based on single experimental data for kinetic prediction, which is difficult to be applied to unknown mechanism and complex reactions. In this study, the reactions of n-order and Kamal autocatalytic model under adiabatic conditions are generated by numerical simulations, and the kinetic parameters are estimated by Vyazovkin and Friedman conversional methods. Then, under different onset temperatures and isothermal conditions, the adiabatic and isothermal reactions are predicted by using the kinetic parameters solved by the model-free methods, and compared with the simulated data. The results show that ARC can use the model-free methods to carry out adiabatic and isothermal kinetic prediction, and it has good prediction accuracy. The maximum relative error of Vyazovkin method is 39.9% and that of Friedman method is over 100%, and the Vyazovkin method is more suitable for prediction than Friedman method. It is recommended to carry out experimental measurements within the predicted temperature range of ±40℃. Kinetic predictions using the model-free methods have good accuracy and efficiency, which is of great significance for the kinetic analysis of new chemicals and complex reactions. This will effectively support the risk assessment of thermal runaway and the accident simulation.

Key words: chemical reaction, stability, adiabatic accelerating rate calorimetry, Friedman method, Vyazovkin method, kinetic prediction, numerical simulation

摘要：

绝热加速量热主要采用基于单一实验数据的模型拟合方法进行动力学预测，难以应用于未知机理反应和复杂反应。为此，通过数值模拟方法在绝热条件下产生n级反应与Kamal自催化反应数据，采用Vyazovkin和Friedman等转化率方法进行动力学求解；然后在不同起始温度和等温条件下，采用无模型动力学参数进行绝热和等温动力学预测，并与模拟数据对比。结果表明，绝热加速量热采用Vyazovkin方法预测最大相对误差为39.9%，Friedman方法预测最大误差超100%，前者更适合进行预测；建议在预测温度±40℃范围内进行实验测量。这为未知化学物质和复杂反应热失控风险评估及化工事故模拟等提供了有效手段。

关键词: 化学反应, 稳定性, 绝热加速量热, Friedman方法, Vyazovkin方法, 动力学预测, 数值模拟