{"title":"Modeling the Viscosity of Ionic Liquids and Their Mixtures Using ePC-SAFT and Free Volume Theory with an Ion-Based Approach","authors":"Zhida Zuo, Xiaohua Lu, Xiaoyan Ji","doi":"10.1021/acs.iecr.4c04260","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"24 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial & Engineering Chemistry Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1021/acs.iecr.4c04260","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
ndustrial & Engineering Chemistry, with variations in title and format, has been published since 1909 by the American Chemical Society. Industrial & Engineering Chemistry Research is a weekly publication that reports industrial and academic research in the broad fields of applied chemistry and chemical engineering with special focus on fundamentals, processes, and products.