| 李孟山,黄兴元,柳和生,陈炳生,袁寿财.化学通报,2016,79(7):610-615. |
| 超临界CO2在聚合物中的溶解计算研究进展 |
| Research Progress of Prediction of supercritical carbon dioxide solubility in polymers |
| 投稿时间：2015-11-09 修订日期：2015-12-30 |
| DOI： |
| 中文关键词: 溶解计算 聚合物 混合神经网络 状态方程 经验方程 |
| 英文关键词:Solubility Prediction Polymer Hybrid Neural Network Equation of State Empirical Equation |
| 基金项目:国家自然科学基金(51163011, 51102131, 51377025) |
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| 中文摘要: |
| 超临界CO2作为治理环境污染和发展绿色化学的重要材料成为“绿色”介质的宠儿，其在聚合物中的溶解性质广泛用在萃取分离、聚合物改性和新材料制备等领域。以超临界CO2在聚合物中的溶解计算模型为例，综述了状态方程、经验方程和人工神经网络计算方法的实现原理、研究现状和优缺点；依据人工神经网络预测方法存在的问题，重点阐述基于混合智能方法的神经网络溶解计算模型；并对溶解计算研究进行了总结和展望。 |
| 英文摘要: |
| As the beloved of green medium, supercritical carbon dioxide (CO2) is the important materials for environmental pollution and green chemistry, its solubility property is widely used for extraction separation, polymer modification, polymer blending, microcellular foaming, particle production and polymerization, etc. In this review, the prediction methods of supercritical CO2 solubility in polymers such as equations of state, empirical equation and artificial neural networks are summarized, and the details of their implementation principle, progress, merits and faults are discussed. Motivated and inspired by the problems of the artificial neural networks, the solubility prediction models based on hybird artificial neural networks are discussed. Then the prospect of solubility prediction is proposed. |
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