In this work, we developed the electrolyte perturbed-chain statistical associating fluids theory (ePC-SAFT) coupled with free volume theory (FVT) using an ion-based approach (i.e., treating IL cation and anion as distinct species) to model the viscosities of 72 ionic liquids (ILs) across various temperatures and pressures. To evaluate the model performance, we compared the ePC-SAFT-FVT model employing a molecular-based approach (i.e., treating IL as a single pure substance) developed in our previous work. The results indicate that the ion-based approach demonstrates desirable performance, achieving an average ARD of 8.73%. This is comparable to the molecular-based approach, which has an average ARD of 6.09%. Importantly, the ion-based approach requires fewer adjustable parameters, reducing the number from 216 to 81 for 72 ILs, and offers enhanced flexibility by allowing the combination of both cation and anion parameters for predictions. Additionally, the ion-specific ePC-SAFT-FVT model was employed to predict the viscosities of IL mixtures, which were then compared to experimental data of 19 IL mixtures. The findings reveal that the model effectively predicts the viscosity of most IL mixtures, achieving an average ARD of 9.1%. Furthermore, the ion-based approach demonstrates superior predictive performance compared to the molecule-specific ePC-SAFT-FVT model. This study indicates that the ePC-SAFT-FVT model, using an ion-based approach, reliably represents the viscosity of pure ILs and IL mixtures, leveraging the flexibility of cation and anion parameter combinations to enhance predictive capabilities.

中文翻译：

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使用 ePC-SAFT 和基于离子的方法的自由体积理论对离子液体及其混合物的粘度进行建模


在这项工作中，我们开发了电解质扰动链统计关联流体理论 （ePC-SAFT） 与自由体积理论 （FVT） 耦合，使用基于离子的方法（即将 IL 阳离子和阴离子视为不同的物种）来模拟 72 种离子液体 （ILs） 在不同温度和压力下的粘度。为了评估模型性能，我们比较了采用基于分子的方法（即将 IL 视为单一纯物质）的 ePC-SAFT-FVT 模型，该模型在我们之前的工作中开发。结果表明，基于离子的方法表现出理想的性能，平均 ARD 为 8.73%。这与基于分子的方法相当，后者的平均 ARD 为 6.09%。重要的是，基于离子的方法需要更少的可调参数，将 72 个 IL 的数量从 216 个减少到 81 个，并通过允许结合阳离子和阴离子参数进行预测来提供增强的灵活性。此外，采用离子特异性 ePC-SAFT-FVT 模型预测 IL 混合物的粘度，然后将其与 19 种 IL 混合物的实验数据进行比较。研究结果表明，该模型有效地预测了大多数 IL 混合物的粘度，平均 ARD 为 9.1%。此外，与分子特异性 ePC-SAFT-FVT 模型相比，基于离子的方法表现出卓越的预测性能。这项研究表明，ePC-SAFT-FVT 模型使用基于离子的方法，可靠地表示纯 ILs 和 IL 混合物的粘度，利用阳离子和阴离子参数组合的灵活性来增强预测能力。