Marshall Bennett D, Li Wenjun, Lively Ryan P
ExxonMobil Technology and Engineering Company, Annandale, NJ 08801, USA.
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Membranes (Basel). 2022 Jul 12;12(7):705. doi: 10.3390/membranes12070705.
In this work we apply dry glass reference perturbation theory (DGRPT) within the context of fully mutualized diffusion theory to predict the temperature and pressure dependent separations of complex liquid mixtures using SBAD-1 glassy polymer membranes. We demonstrate that the approach allows for the prediction of the membrane-based separation of complex liquid mixtures over a wide range of temperature and pressure, using only single-component vapor sorption isotherms measured at 25 °C to parameterize the model. The model was then applied to predict the membrane separation of a light shale crude using a structure oriented lumping (SOL) based compositional model of petroleum. It was shown that when DGRPT is applied based on SOL compositions, the combined model allows for the accurate prediction of separation performance based on the trend of both molecular weight and molecular class.
在这项工作中,我们在完全互扩散理论的背景下应用干玻璃参考微扰理论(DGRPT),以使用SBAD - 1玻璃态聚合物膜预测复杂液体混合物的温度和压力依赖性分离。我们证明,该方法能够仅使用在25°C下测量的单组分蒸汽吸附等温线对模型进行参数化,从而在很宽的温度和压力范围内预测基于膜的复杂液体混合物的分离。然后,该模型被应用于使用基于结构导向集总(SOL)的石油组成模型来预测轻质页岩原油的膜分离。结果表明,当基于SOL组成应用DGRPT时,组合模型能够根据分子量和分子类别趋势准确预测分离性能。