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Predictive calculation of carbon dioxide solubility in polymers

机译:聚合物中二氧化碳溶解度的预测计算

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摘要

The solubility of carbon dioxide in polymers has attracted great attention from scientists because it is an important application of green chemistry, and it is widely applied in extraction, separation and the preparation of new materials. In this work, a new solubility prediction model with both good accuracy and efficiency, called CEAPSO KHM RBF ANN, is developed. In the CEAPSO KHM RBF ANN model, an accelerated particle swarm optimization (APSO) algorithm with chaotic disturbance is employed to trim the radial basis function artificial neural network (RBF ANN) connection weights and biases in order to reduce the premature convergence problem, and the K-harmonic means (KHM) clustering method is used to tune the hidden centers and spreads of the radial basis function. The proposed model is employed to investigate the solubility of CO2 in polymers including polypropylene, polystyrene, poly(vinyl acetate), carboxylated polyesters and poly(butylene succinate-co-adipate). The results indicate that the proposed model is an effective method for solubility prediction with better performance and higher efficiency compared with the other methods, and should contribute to the understanding of the phase behaviour of the gas/polymer system and for the design and optimization of processing techniques.
机译:二氧化碳在聚合物中的溶解度引起了科学家的极大关注,因为它是绿色化学的重要应用,并且广泛应用于萃取,分离和新材料的制备。在这项工作中,开发了一种新的溶解度预测模型,具有良好的准确性和效率,称为Ceapso KHM RBF ANN。在CeAPSO KHM RBF Ann模型中,采用加速粒子群优化(APSO)具有混沌扰动的径向基函数人工神经网络(RBF ANN)连接权重和偏置,以降低过早收敛问题,以及K-Harmonic手段(KHM)聚类方法用于调整隐藏的中心和径向基函数的传播。所提出的模型用于研究CO 2在包含聚丙烯,聚苯乙烯,聚(乙酸乙烯酯),羧化聚酯和聚(丁二酸丁酸酯 - 共己酸酯)中的聚合物中的溶解度。结果表明,与其他方法相比,该拟议模型是溶解度预测的有效预测,更好的性能和更高的效率,并且应该有助于了解气体/聚合物系统的相位行为以及加工的设计和优化技巧。

著录项

  • 来源
    《RSC Advances》 |2015年第94期|共8页
  • 作者

    Xia Ru-Ting; Huang Xing-Yuan;

  • 作者单位

    Taizhou Univ Sch Mech Engn Taizhou 318000 Zhejiang Peoples R China;

    Nanchang Univ Coll Mech &

    Elect Engn Nanchang 330029 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化学;
  • 关键词

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