Degradation Kinetics of Polycarbonate Composites: Kinetic Parameters and Artificial Neural Network
Degradation Kinetics of Polycarbonate Composites: Kinetic Parameters and Artificial Neural Network
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DOI：
10.15255/cabeq.2017.1173
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发表时间：
2018-01-01
影响因子：
1.5
通讯作者：
Shimpi, N. G.
中科院分区：
文献类型：
--
作者：
Charde, S. J.;Sonawane, S. S.;Shimpi, N. G.
为了设计反应器，采用热重分析法（TGA）研究了聚碳酸酯/CaCO3复合材料的降解动力学，同时采用无模型法和模型法，得到了E、a、δ S*、δ H*和δ G*（动力学参数）。使用非等温模型方法（Coats-Redfern）对系统进行了所有可用机制的测试。这种方法允许选择模型，否则很难简单地基于回归拟合方法来决定模型。提出的机制是一个简单的n阶。在神经网络设计中应用人工神经网络可以快速确定动力学参数。
In order to design a reactor, kinetics of degradation of polycarbonate/CaCO3 composites was investigated here by thermogravimetric analysis (TGA), applying model-free and modelistic methods together, to obtain E, A, Delta S*, Delta H* and Delta G* (kinetic parameters). The system was tested with all the mechanisms available using non-isothermal modelistic method (Coats-Redfern). This approach allowed choosing the models, which are otherwise difficult to decide upon simply based on regression fit methods. The mechanism proposed was a simple nth order. Application of artificial neural network supported in designing a neural network could lead to a quick determination of kinetic parameters.