摘要
本文使用双螺杆挤出机制备了β成核聚丙烯(β-PP)/有机蒙脱土(OMMT)纳米复合材料。采用FTIR、XRD和SEM分析了复合材料的微观结构与形貌特征,考察了OMMT、β成核剂(β-NA)及增容剂用量对复合材料冲击强度和弯曲强度的影响,并对比研究了标准BP神经网络模型和LM-BP神经网络模型对力学性能的预测能力。结果表明,增容剂与OMMT表面形成了强相互作用,提高了复合体系的相容性,黏土片以插层结构分散在β-PP基体内。OMMT、β-NA及增容剂用量对复合材料的力学性能均产生了一定影响,其中添加30%增容剂时复合材料的冲击强度约为不添加时的4倍,而弯曲强度仅降低了28.39%。此外,与标准BP神经网络模型相比,LM-BP神经网络模型具有更快的收敛速度和更高的预测精度。该研究为优化PP基纳米复合材料的制备及力学性能预测提供了参考。
In this paper,β-nucleated polypropylene(β-PP)/organic montmorillonite(OMMT)nanocomposites were prepared by twin-screw extruder.The microstructure and morphology of the composites were analyzed by FTIR,XRD and SEM.The effects of OMMT,β-nucleating agent(β-NA)and compatibilizer on the impact strength and flexural strength of the composites were investigated.And comparatively studying the standard BP neural network model and LM-BP neural network model for prediction ability of mechanical properties.The results showed that the compatibilizer forms a strong interaction at the surface of OMMT,which improves the compatibility of the composite system,and the clay sheets with intercalated structures are dispersed inβ-PP matrix.The amount of OMMT,β-NA and compatibilizer all has a certain effect on the mechanical properties of composites.Among them,the impact strength of composite with 30%compatibilizer is about 4 times when which is not added,while the tensile strength is only reduced by 28.39%.In addition,the LM-BP neural network model has fast convergence rate and high prediction precision compared with the standard BP neural network model.This study provides reference for optimizing the preparation and the mechanical properties prediction of PP-based nanocomposites.
作者
刘金月
孟静
祝宝东
LIU Jin-yue;MENG Jing;ZHU Bao-dong(Computer and Information Technology College,Northeast Petroleum University,Daqing 163318,China;College of Chemistry and Chemical Engineering,Northeast Petroleum University,Daqing 163318,China;Exploration and Development Research Institute of Daqing Oilfield Co.,Ltd.,Daqing 163712,China)
出处
《化学工程师》
CAS
2024年第3期99-103,共5页
Chemical Engineer
基金
东北石油大学引导性创新基金(2020YDL-10)。
关键词
聚丙烯
有机蒙脱土
Β成核剂
增容剂
LM算法
BP神经网络
polypropylene
organic montmorillonite
β-nucleating agent
compatibilizer
LM algorithm
BP neural network
