关键词:

萃取精馏溶剂, 定量的结构-性质关系, 分子连接性指数, 人工神经网络模型

Abstract:

In order to select the optimum solvents of extractive distillation on the basis of molecular simulation, a mathematical model must be firstly established for describing the quantitative structure-property relationships (QSPR) of the solvents.In this paper the molecular connectivity indexes (MCI) were used to express two-dimensional molecular topological structure, which could indicate not only the kind and number of atoms or groups composing the solvent molecule but also the inter-connective characteristics among them.The major solvent properties, such as selectivity and solubility were the functions of infinite dilution activity coefficients, γ∞.Because of the extraordinary complexity between molecular structure and γ∞, an artificial neural network (ANN) model was used for the QSPR.An appropriate database was established and the back-propagation (BP) algorithm was used to train the ANN model, and the well-trained ANN model proved to be more accurate in calculating γ∞ than the prevailing UNIFAC method.

Key words:

萃取精馏溶剂, 定量的结构-性质关系, 分子连接性指数, 人工神经网络模型