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    多尺度模拟揭示极性项对PC-SAFT模型影响机理

    Mechanistic Insights into Polar Term Effects on PC-SAFT via Multiscale Simulation

    • 摘要: PC-SAFT模型由硬球、硬链、色散、极性和缔合贡献组成,从微观和宏观角度评价极性贡献对PC-SAFT模型预测能力的影响。将27种具有代表性的极性物质分为4类,使用高斯软件从分子角度模拟27种物质的分子表面静电势(MESP)和分子极性指数(MPI)。通过饱和蒸气压、液体密度和蒸发焓的实验数据从宏观热力学角度评价包含极性修正项的PPC-SAFT状态方程(PPC-SAFT EoS)和不包含极性修正项的PC-SAFT状态方程(PC-SAFT EoS)的预测能力。分子模拟微观结果表明,醛类、酮类、氯代烷类和醚类4类物质的极性依次降低,而同一类物质的极性随着碳链长度或取代基的增加而降低。随着极性的降低,PPC-SAFT和PC-SAFT模型对饱和蒸气压等宏观热力学性质预测结果逐渐趋近,说明极性作用的贡献减弱。根据微观和宏观模拟结果确定MESP和MPI的阈值以判断PC-SAFT是否采用极性贡献项,避免对PC-SAFT模型非必要的参数化,有助于提高模型计算效率。

       

      Abstract: The PC-SAFT model consists of hard-sphere, hard chain, dispersion, polarity, and association contributions. The influence of the polarity contribution on the predictive ability of the PC-SAFT model is evaluated from both microscopic and macroscopic perspectives. 27 representative polar substances are classified into four categories. Gaussian software is employed to simulate the molecular electrostatic potential (MESP) and molecular polarity index (MPI) for the 27 substances. The predictive capability of PPC-SAFT EoS with polarity terms and PC-SAFT EoS without polarity terms are evaluated with macroscopic properties, such as saturated vapor pressure, liquid density, and enthalpy of evaporation. The microscopic results of molecular simulation indicate that the polarity of the four categories decreases in the following order: aldehydes, ketones, chloroalkanes, and ethers. The polarity of the same type of substance decreases as the length of the carbon chain or the number of substituents increase. As the polarity decreases, the prediction results of macroscopic thermodynamic properties such as saturated vapor pressure by the PPC-SAFT and PC-SAFT models gradually close, and the contribution of the polarity effect weakens. The threshold values for MESP and MPI are determined to judge whether the PC-SAFT model should adopt the polar contribution terms according to the evaluation results. This conclusion can assist in avoiding unnecessary parameterization of complex systems and enhancing the computational efficiency in process simulations.

       

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