Multiobjective Optimization of PCP-SAFT Parameters for Water and Alcohols Using Surface Tension Data,Journal of Chemical & Engineering Data

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Multiobjective Optimization of PCP-SAFT Parameters for Water and Alcohols Using Surface Tension Data
Journal of Chemical & Engineering Data ( IF 2.0 ) Pub Date : 2020-09-22 , DOI: 10.1021/acs.jced.0c00684
Philipp Rehner ₁ , Joachim Gross ₁

Affiliation

With predictive methods, such as classical density functional theory and predictive density gradient theory (pDGT), it is possible to model bulk phase properties and interfacial tensions using the same model. For nonassociating fluids, these models can be used to predict interfacial properties for systems that lack experimental data. For associating components, however, predictions often show large deviations to experiments, which is at least partially rooted in highly correlated pure component parameters. Therefore, we use interfacial properties for discriminating pure component parameters by amending the PCP-SAFT parameter estimation for water and alcohols by including surface tension data in the objective function. To obtain a comprehensive comparison between different association models, a multiobjective optimization is performed. By analyzing the resulting pareto fronts, it is shown that including a fitted dipole moment improves the results for water but not for alcohols. The result of the multiobjective optimization is inconclusive about the optimal choice of association scheme for water as the preferred model changes along the pareto front. For small alcohols, in contrast to chemical intuition, the 4C association scheme gives the best results. For longer alcohols, the pareto analysis shows the limits of the homosegmented modeling approach.

中文翻译：

利用表面张力数据对水和醇PCP-SAFT参数进行多目标优化

使用预测方法，例如经典密度泛函理论和预测密度梯度理论（pDGT），可以使用相同的模型对体相特性和界面张力进行建模。对于非缔合流体，这些模型可用于预测缺少实验数据的系统的界面特性。但是，对于关联的组件，预测通常会显示出与实验的较大偏差，这至少部分源于高度相关的纯组件参数。因此，我们通过在目标函数中包括表面张力数据来修改水和醇的PCP-SAFT参数估计，从而使用界面属性来区分纯组分参数。为了获得不同关联模型之间的全面比较，执行了多目标优化。通过分析所得的对角线前沿，可以看出，包括一个合适的偶极矩可以改善水的结果，但不能改善酒精的结果。多目标优化的结果尚不确定水的关联方案的最佳选择，因为首选模型沿Pareto前沿变化。对于小分子醇，与化学直觉相反，4C缔合方案可提供最佳结果。对于更长的酒精，pareto分析显示了同段建模方法的局限性。与化学直觉相反，4C关联方案可提供最佳结果。对于更长的酒精，pareto分析显示了同段建模方法的局限性。与化学直觉相反，4C关联方案可提供最佳结果。对于更长的酒精，pareto分析显示了同段建模方法的局限性。

更新日期：2020-09-22

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