离子液体双水相体系相平衡的动态参数模拟

基于离子液体双水相体系相平衡组成的高度不对称性,提出了"动态参数"模拟的概念,以体系在298.2K、308.2K和323.2K温度下的数据为样本,建立了神经网络关联模型,经比较,其精度优于文献中的Othmer-Tobias/Bancroft方程.此外,模型对实验数据的依赖性较弱,在一定的范围内,具有对体系相平衡组成进行直接预测的能力.

Dynamic Parameters Modeling of the Phase Equilibria of Aqueous Two-Phase Systems Based on Ionic Liquid

The concept of dynamic parameters has been proposed to obtain the neural network model,which was employed to correlate the phase equilibrium data(T=298.2K,308.2K,323.2K)of the aqueous two-phase systems containing the ionic liquids and citrate.The comparison in terms of calculation accuracy between the neural network model and the Othmer-Tobias/Bancroft equations used in the literature shows that the former gives better result.Furthermore,due to its weak dependence on the experimental data,the suggested model is capable of direct predicting the phase equilibrium compositions for the systems investigated here in an appropriate temperature range.