Dynamic Parameters Modeling of the Phase Equilibria of Aqueous Two-Phase Systems Based on Ionic Liquid
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摘要:
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.
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.
作者:
吕会超 王艳飞
机构地区:
安阳工学院化学与环境工程学院
出处:
《betway官方app 学报：自然科学版》 CAS 北大核心 2015年第4期74-78,共5页
基金:
国家自然科学基金(21406002)
关键词:
离子液体 双水相体系 相平衡 动态参数 神经网络
ionic liquid aqueous two-phase system phase equilibrium dynamic parameters neural network
分类号:
O642.4 [理学—物理化学]
