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Yu G, Dai C, Liu N, Xu R, Wang N, Chen B. Hydrocarbon Extraction with Ionic Liquids. Chem Rev 2024; 124:3331-3391. [PMID: 38447150 DOI: 10.1021/acs.chemrev.3c00639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Separation and reaction processes are key components employed in the modern chemical industry, and the former accounts for the majority of the energy consumption therein. In particular, hydrocarbon separation and purification processes, such as aromatics extraction, desulfurization, and denitrification, are challenging in petroleum refinement, an industrial cornerstone that provides raw materials for products used in human activities. The major technical shortcomings in solvent extraction are volatile solvent loss, product entrainment leading to secondary pollution, low separation efficiency, and high regeneration energy consumption due to the use of traditional organic solvents with high boiling points as extraction agents. Ionic liquids (ILs), a class of designable functional solvents or materials, have been widely used in chemical separation processes to replace conventional organic solvents after nearly 30 years of rapid development. Herein, we provide a systematic and comprehensive review of the state-of-the-art progress in ILs in the field of extractive hydrocarbon separation (i.e., aromatics extraction, desulfurization, and denitrification) including (i) molecular thermodynamic models of IL systems that enable rapid large-scale screening of IL candidates and phase equilibrium prediction of extraction processes; (ii) structure-property relationships between anionic and cationic structures of ILs and their separation performance (i.e., selectivity and distribution coefficients); (iii) IL-related extractive separation mechanisms (e.g., the magnitude, strength, and sites of intermolecular interactions depending on the separation system and IL structure); and (iv) process simulation and design of IL-related extraction at the industrial scale based on validated thermodynamic models. In short, this Review provides an easy-to-read exhaustive reference on IL-related extractive separation of hydrocarbon mixtures from the multiscale perspective of molecules, thermodynamics, and processes. It also extends to progress in IL analogs, deep eutectic solvents (DESs) in this research area, and discusses the current challenges faced by ILs in related separation fields as well as future directions and opportunities.
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Affiliation(s)
- Gangqiang Yu
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
| | - Chengna Dai
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
| | - Ning Liu
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
| | - Ruinian Xu
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
| | - Ning Wang
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
| | - Biaohua Chen
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
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2
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Song Z, Chen J, Cheng J, Chen G, Qi Z. Computer-Aided Molecular Design of Ionic Liquids as Advanced Process Media: A Review from Fundamentals to Applications. Chem Rev 2024; 124:248-317. [PMID: 38108629 DOI: 10.1021/acs.chemrev.3c00223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The unique physicochemical properties, flexible structural tunability, and giant chemical space of ionic liquids (ILs) provide them a great opportunity to match different target properties to work as advanced process media. The crux of the matter is how to efficiently and reliably tailor suitable ILs toward a specific application. In this regard, the computer-aided molecular design (CAMD) approach has been widely adapted to cover this family of high-profile chemicals, that is, to perform computer-aided IL design (CAILD). This review discusses the past developments that have contributed to the state-of-the-art of CAILD and provides a perspective about how future works could pursue the acceleration of the practical application of ILs. In a broad context of CAILD, key aspects related to the forward structure-property modeling and reverse molecular design of ILs are overviewed. For the former forward task, diverse IL molecular representations, modeling algorithms, as well as representative models on physical properties, thermodynamic properties, among others of ILs are introduced. For the latter reverse task, representative works formulating different molecular design scenarios are summarized. Beyond the substantial progress made, some future perspectives to move CAILD a step forward are finally provided.
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Affiliation(s)
- Zhen Song
- State Key laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Jiahui Chen
- State Key laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Jie Cheng
- State Key laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Guzhong Chen
- State Key laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Zhiwen Qi
- State Key laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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Abstract
Condensable gases are the sum of condensable and volatile steam or organic compounds, including water vapor, which are discharged into the atmosphere in gaseous form at atmospheric pressure and room temperature. Condensable toxic and harmful gases emitted from petrochemical, chemical, packaging and printing, industrial coatings, and mineral mining activities seriously pollute the atmospheric environment and endanger human health. Meanwhile, these gases are necessary chemical raw materials; therefore, developing green and efficient capture technology is significant for efficiently utilizing condensed gas resources. To overcome the problems of pollution and corrosion existing in traditional organic solvent and alkali absorption methods, ionic liquids (ILs), known as "liquid molecular sieves", have received unprecedented attention thanks to their excellent separation and regeneration performance and have gradually become green solvents used by scholars to replace traditional absorbents. This work reviews the research progress of ILs in separating condensate gas. As the basis of chemical engineering, this review first provides a detailed discussion of the origin of predictive molecular thermodynamics and its broad application in theory and industry. Afterward, this review focuses on the latest research results of ILs in the capture of several important typical condensable gases, including water vapor, aromatic VOCs (i.e., BTEX), chlorinated VOC, fluorinated refrigerant gas, low-carbon alcohols, ketones, ethers, ester vapors, etc. Using pure IL, mixed ILs, and IL + organic solvent mixtures as absorbents also briefly expanded the related reports of porous materials loaded with an IL as adsorbents. Finally, future development and research directions in this exciting field are remarked.
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Affiliation(s)
- Guoxuan Li
- State Key Laboratory of Chemical Resource Engineering, Beijing Key Laboratory of Energy Environmental Catalysis, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
| | - Kai Chen
- School of Chemistry and Chemical Engineering/State Key Laboratory Incubation Base for Green Processing of Chemical Engineering, Shihezi University, Shihezi 832003, China
| | - Zhigang Lei
- State Key Laboratory of Chemical Resource Engineering, Beijing Key Laboratory of Energy Environmental Catalysis, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
- School of Chemistry and Chemical Engineering/State Key Laboratory Incubation Base for Green Processing of Chemical Engineering, Shihezi University, Shihezi 832003, China
| | - Zhong Wei
- School of Chemistry and Chemical Engineering/State Key Laboratory Incubation Base for Green Processing of Chemical Engineering, Shihezi University, Shihezi 832003, China
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Zheng J, Hu Y, Wu L, Zhang W. New Model to Predict Infinite Dilution Activity Coefficients Based on (∂ p/∂ x) T,x → 0. ACS OMEGA 2023; 8:12439-12444. [PMID: 37033839 PMCID: PMC10077546 DOI: 10.1021/acsomega.3c00368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 03/08/2023] [Indexed: 06/19/2023]
Abstract
Accurate prediction of infinite dilution activity coefficient (γ∞) is essential for the calculation of phase equilibria, solubility, and related properties in molecular thermodynamics. Here, we propose a new model to accurately predict the value of γ∞. It is applicable to calculate γ∞ for compounds in aqueous solution at different temperatures. The model is based on the relationship of (∂p/∂x) T,x→0 with γ∞ and temperature at low pressure. First, we introduce the new idea of using the group contribution method to estimate (∂p/∂x) T,x→0 and then obtain the activity coefficient of a solute at infinite dilution in water based on the relationship between (∂p/∂x) T,x→0 and γ∞. The accuracy of this model is verified using experimental data from 46 systems and more than 450 data points. The result shows that the total average relative deviation of the predicted values from the experimental values for training data is 4.73%. Besides, we test the applicability of the model using solutes that are not part of the training data set. The result shows that the model is satisfactory for the prediction of testing data. Compared with other models, the results prove that the developed model outperforms the UNIFAC model, the modified UNIFAC model, and previous predictive models for aqueous systems. The final equation with only simple arithmetic is more easily applied in engineering practices.
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5
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Wang R, Chen J, Song Z, Qi Z. Bridging Machine Learning and Redlich–Kister Theory for Solid–Liquid Equilibria Prediction of Binary Eutectic Solvent Systems. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.3c00054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Affiliation(s)
- Ruizhuan Wang
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Jiahui Chen
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Zhen Song
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Zhiwen Qi
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
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6
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Gui C, Li G, Song M, Lei Z. Absorption of dichloromethane in deep eutectic solvents: Experimental and computational thermodynamics. Sep Purif Technol 2023. [DOI: 10.1016/j.seppur.2023.123281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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7
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Gui C, Li G, Lei Z, Wei Z, Dong Y. Experiment and Molecular Mechanism of Two Chlorinated Volatile Organic Compounds in Ionic Liquids. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.2c04163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Chengmin Gui
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
| | - Guoxuan Li
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
| | - Zhigang Lei
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
- School of Chemistry and Chemical Engineering, Shihezi University, Shihezi832003, China
| | - Zhong Wei
- School of Chemistry and Chemical Engineering, Shihezi University, Shihezi832003, China
| | - Yichun Dong
- School of Chemistry and Chemical Engineering, Hefei University of Technology, Hefei230009, China
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8
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Li G, Liu Q, Gui C, Zhang J, Lei Z. Molecular Refining: A Simulation Comparison between Real Fuel Oil and Model Oil. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c03664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Guoxuan Li
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
| | - Qinghua Liu
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
| | - Chengmin Gui
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
| | - Jie Zhang
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
| | - Zhigang Lei
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing100029, China
- School of Chemistry and Chemical Engineering, Shihezi University, Shihezi832003, China
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9
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De Visscher A. Extended Specific Ion Theory (ESIT): Theoretical development and application to Harned’s rule. J SOLUTION CHEM 2022. [DOI: 10.1007/s10953-022-01152-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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10
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Zhu R, Huang S, Gui C, Li G, Lei Z. Capturing low-carbon alcohols from CO2 gas with ionic liquids. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.117745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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11
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Wang K, Xu W, Wang Q, Zhao C, Huang Z, Yang C, Ye C, Qiu T. Rational Design and Screening of Ionic Liquid Absorbents for Simultaneous and Stepwise Separations of SO2 and CO2 from Flue Gas. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.1c04240] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Kai Wang
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
| | - Weijie Xu
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
| | - Qinglian Wang
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
| | - Chuncheng Zhao
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
| | - Zhixian Huang
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
| | - Chen Yang
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
| | - Changshen Ye
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
| | - Ting Qiu
- Engineering Research Center of Reactive Distillation, Fujian Province Higher Education Institutes, College of Chemical Engineering, Fuzhou University, Fuzhou 350116 Fujian, China
- Qingyuan Innovation Laboratory, Quanzhou 362801, China
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12
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Yu G, Wei Z, Chen K, Guo R, Lei Z. Predictive molecular thermodynamic models for ionic liquids. AIChE J 2022. [DOI: 10.1002/aic.17575] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Gangqiang Yu
- Faculty of Environment and Life Beijing University of Technology Beijing China
| | - Zhong Wei
- School of Chemistry and Chemical Engineering Shihezi University Shihezi China
| | - Kai Chen
- School of Chemistry and Chemical Engineering Shihezi University Shihezi China
| | - Ruili Guo
- School of Chemistry and Chemical Engineering Shihezi University Shihezi China
| | - Zhigang Lei
- School of Chemistry and Chemical Engineering Shihezi University Shihezi China
- State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Beijing China
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13
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Li G, Gui C, Zhu R, Lei Z. Deep eutectic solvents for efficient capture of cyclohexane in volatile organic compound
s
: Thermodynamic and molecular mechanism. AIChE J 2021. [DOI: 10.1002/aic.17535] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Affiliation(s)
- Guoxuan Li
- State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Beijing China
| | - Chengmin Gui
- State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Beijing China
| | - Ruisong Zhu
- State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Beijing China
| | - Zhigang Lei
- State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Beijing China
- School of Chemistry and Chemical Engineering Shihezi University Shihezi China
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14
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Solvent pre-selection for extractive distillation using infinite dilution activity coefficients and the three-component Margules equation. Sep Purif Technol 2021. [DOI: 10.1016/j.seppur.2021.119230] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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15
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Zhu R, Li G, Lei Z, Gui C. Mechanistic insight into absorption performance assessment for SO2 by mixed ionic liquids. J Mol Liq 2021. [DOI: 10.1016/j.molliq.2021.117927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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16
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Chen G, Song Z, Qi Z. Transformer-convolutional neural network for surface charge density profile prediction: Enabling high-throughput solvent screening with COSMO-SAC. Chem Eng Sci 2021. [DOI: 10.1016/j.ces.2021.117002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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17
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Systematic screening of bifunctional ionic liquid for intensifying esterification of methyl heptanoate in the reactive extraction process. Chem Eng Sci 2021. [DOI: 10.1016/j.ces.2021.116888] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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18
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Hekayati J, Raeissi S. Determination of the Solute Content and Volumetric Properties of Binary Ionic Liquid Mixtures Using a Global Regularity of Molar Volume Expansion. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c02176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Javad Hekayati
- School of Chemical and Petroleum Engineering, Shiraz University, Mollasadra Avenue, Shiraz 71348-51154, Iran
| | - Sona Raeissi
- School of Chemical and Petroleum Engineering, Shiraz University, Mollasadra Avenue, Shiraz 71348-51154, Iran
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19
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Zhang X, Wang J, Song Z, Zhou T. Data-Driven Ionic Liquid Design for CO 2 Capture: Molecular Structure Optimization and DFT Verification. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c01384] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Xiang Zhang
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, Magdeburg D-39106, Germany
| | - Jingwen Wang
- Academy of Building Energy Efficiency, School of Civil Engineering, Guangzhou University, Guangzhou 510006, China
| | - Zhen Song
- Process Systems Engineering, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, Magdeburg D-39106, Germany
| | - Teng Zhou
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, Magdeburg D-39106, Germany
- Process Systems Engineering, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, Magdeburg D-39106, Germany
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20
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Chen Y, Garg N, Luo H, Kontogeorgis GM, Woodley JM. Ionic liquid-based in situ product removal design exemplified for an acetone-butanol-ethanol fermentation. Biotechnol Prog 2021; 37:e3183. [PMID: 34129284 DOI: 10.1002/btpr.3183] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 06/07/2021] [Accepted: 06/11/2021] [Indexed: 01/10/2023]
Abstract
Selecting an appropriate separation technique is essential for the application of in situ product removal (ISPR) technology in biological processes. In this work, a three-stage systematic design method is proposed as a guide to integrate ionic liquid (IL)-based separation techniques into ISPR. This design method combines the selection of a suitable ISPR processing scheme, the optimal design of an IL-based liquid-liquid extraction (LLE) system followed by process simulation and evaluation. As a proof of concept, results for a conventional acetone-butanol-ethanol fermentation are presented (40,000 ton/year butanol production). In this application, ILs tetradecyl(trihexyl)phosphonium tetracyanoborate ([TDPh][TCB]) and tetraoctylammonium 2-methyl-1-naphthoate ([TOA] [MNaph]) are identified as the optimal solvents from computer-aided IL design (CAILD) method and reported experimental data, respectively. The dynamic simulation results for the fermentation process show that, the productivity of IL-based in situ (fed-batch) process and in situ (batch) process is around 2.7 and 1.8fold that of base case. Additionally, the IL-based in situ (fed-batch) process and in situ (batch) process also have significant energy savings (79.6% and 77.6%) when compared to the base case.
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Affiliation(s)
- Yuqiu Chen
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - Nipun Garg
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - Hao Luo
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - Georgios M Kontogeorgis
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - John M Woodley
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
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21
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Zhang X, Ding X, Song Z, Zhou T, Sundmacher K. Integrated ionic liquid and
rate‐based
absorption process design for gas separation: Global optimization using hybrid models. AIChE J 2021. [DOI: 10.1002/aic.17340] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Xiang Zhang
- Process Systems Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany
| | - Xuechong Ding
- Process Systems Engineering Otto‐von‐Guericke University Magdeburg Magdeburg Germany
| | - Zhen Song
- Process Systems Engineering Otto‐von‐Guericke University Magdeburg Magdeburg Germany
| | - Teng Zhou
- Process Systems Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany
- Process Systems Engineering Otto‐von‐Guericke University Magdeburg Magdeburg Germany
| | - Kai Sundmacher
- Process Systems Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany
- Process Systems Engineering Otto‐von‐Guericke University Magdeburg Magdeburg Germany
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22
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Modeling of Technological Processes for a Rectification Plant in Second-Generation Bioethanol Production. Processes (Basel) 2021. [DOI: 10.3390/pr9060944] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The article deals with the recent developments in the fuel industry, considering the permanent increasing requirements for fuel quality and environmental safety. The work aims to study various technological modes at the rectification unit to produce fuel bioethanol from lignocellulosic biomass. The main goals are to solve applied scientific problems of rational designing and technological optimization to obtain boundaries of energy consumption to ensure the quality of bioethanol sufficient for a consumer. Recent approaches for numerical simulation of chemical technological processes were applied to study the operating processes and optimize technological parameters. The plant model was designed from various modules that allow us to simulate technological processes efficiently and accurately for all the primary units of the rectification equipment. The methodology based on the activity coefficient UNIFAC model of phase equilibrium was applied. As a result, a mixture with 74% of bioethanol 9% of impurities was obtained in the brew column. In the epuration column, a mixture of 46% bioethanol and 2.2% of impurities was obtained in bottoms. Finally, in the alcohol column, the mass fraction of distillate of 96.9% and impurities of 2.7% were reached. The numerical simulation results can be applied in recent fuel technologies and designing the corresponding biofuel plants.
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23
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Kang X, Lv Z, Zhao Y, Chen Z. A QSPR model for estimating Henry's law constant of H2S in ionic liquids by ELM algorithm. CHEMOSPHERE 2021; 269:128743. [PMID: 33139046 DOI: 10.1016/j.chemosphere.2020.128743] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 10/13/2020] [Accepted: 10/22/2020] [Indexed: 06/11/2023]
Abstract
Ionic liquids (ILs) as green solvents have been studied in the application of gas sweetening. However, it is a huge challenge to obtain all the experimental values because of the high costs and generated chemical wastes. This study pioneered a quantitative structure-property relationship (QSPR) model for estimating Henry's law constant (HLC) of H2S in ILs. A dataset consisting of the HLC data of H2S for 22 ILs within a wide range of temperature (298.15-363.15 K) were collected from published reports. The electrostatic potential surface area (SEP) and molecular volume of these ILs were calculated and used as input descriptors together with temperature. The extreme learning machine (ELM) algorithm was employed for nonlinear modelling. Results showed that the determination coefficient (R2) of the training set, test set and total set were 0.9996, 0.9989,0.9994, respectively, while the average absolute relative deviation (AARD%) of them were 1.3383, 2,4820 and 1.5820, respectively. The statistical parameters for the measurement of the model exhibited the great reliability, stability, and predictive power of the ELM model. The Applicability Domain (AD) of the ELM model is also investigated. It proves that the majority of ILs in the training and test sets are located in the model's AD and verifies the reliability of the model. The proposed model is potentially applicable to guide the application of ILs for gas sweetening.
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Affiliation(s)
- Xuejing Kang
- The Key Laboratory of Biotechnology for Medicinal Plants of Jiangsu Province, School of Life, Jiangsu Normal University, Shanghai Road 101, 221116, Xuzhou, China; Department of Applied Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, 16500, Prague 6, Czech Republic
| | - Zuopeng Lv
- The Key Laboratory of Biotechnology for Medicinal Plants of Jiangsu Province, School of Life, Jiangsu Normal University, Shanghai Road 101, 221116, Xuzhou, China
| | - Yongsheng Zhao
- Department of Chemical Engineering, University of California, Santa Barbara, CA, 93106-5080, United States.
| | - Zhongbing Chen
- Department of Applied Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, 16500, Prague 6, Czech Republic.
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Lei Y, Zhou Y, Wei Z, Chen Y, Guo F, Yan W. Optimal Design of an Ionic Liquid (IL)-Based Aromatic Extractive Distillation Process Involving Energy and Economic Evaluation. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.0c05183] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Yang Lei
- School of Chemistry and Chemical Engineering, Hubei Key Laboratory of Coal Conversion and New Carbon Materials, Wuhan University of Science and Technology, Wuhan 430081, Hubei, China
- Center for Energy Resources Engineering, Department of Chemistry, Technical University of Denmark, Lyngby 2800, Denmark
| | - Yuhang Zhou
- School of Chemistry and Chemical Engineering, Hubei Key Laboratory of Coal Conversion and New Carbon Materials, Wuhan University of Science and Technology, Wuhan 430081, Hubei, China
| | - Zhiqiang Wei
- SINOPEC Refining Department, Beijing 100728, China
| | - Yuqiu Chen
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby 2800, Denmark
| | - Fen Guo
- School of Chemistry and Chemical Engineering, Hubei Key Laboratory of Coal Conversion and New Carbon Materials, Wuhan University of Science and Technology, Wuhan 430081, Hubei, China
| | - Wei Yan
- Center for Energy Resources Engineering, Department of Chemistry, Technical University of Denmark, Lyngby 2800, Denmark
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25
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Chen G, Song Z, Qi Z, Sundmacher K. Neural recommender system for the activity coefficient prediction and
UNIFAC
model extension of ionic
liquid‐solute
systems. AIChE J 2021. [DOI: 10.1002/aic.17171] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Guzhong Chen
- State Key laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
| | - Zhen Song
- Process Systems Engineering Otto‐von‐Guericke University Magdeburg Magdeburg Germany
- Process Systems Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany
| | - Zhiwen Qi
- State Key laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
| | - Kai Sundmacher
- Process Systems Engineering Otto‐von‐Guericke University Magdeburg Magdeburg Germany
- Process Systems Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany
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26
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Zhou T, Shi H, Ding X, Zhou Y. Thermodynamic modeling and rational design of ionic liquids for pre-combustion carbon capture. Chem Eng Sci 2021. [DOI: 10.1016/j.ces.2020.116076] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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27
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Abstract
The extent to which cations and anions in ionic liquids (ILs) and ionic liquid solutions are dissociated is of both fundamental scientific interest and practical importance because ion dissociation has been shown to impact viscosity, density, surface tension, volatility, solubility, chemical reactivity, and many other important chemical and physical properties. When mixed with solvents, ionic liquids provide the unique opportunity to investigate ion dissociation from infinite dilution in the solvent to a completely solvent-free state, even at ambient conditions. The most common way to estimate ion dissociation in ILs and IL solutions is by comparing the molar conductivity determined from ionic conductivity measurements such as electrochemical impedance spectroscopy (EIS) (which measure the movement of only the charged, i.e., dissociated, ions) with the molar conductivity calculated from ion diffusivities measured by pulse field gradient nuclear magnetic resonance spectroscopy (PFG-NMR, which gives movement of all of the ions). Because the NMR measurements are time-consuming, the number of ILs and IL solutions investigated by this method is relatively limited. We have shown that use of the Stokes-Einstein equation with estimates of the effective ion Stokes radii allows ion dissociation to be calculated from easily measured density, viscosity, and ionic conductivity data (ρ, η, λ), which is readily available in the literature for a much larger number of pure ILs and IL solutions. Therefore, in this review, we present values of ion dissociation for ILs and IL solutions (aqueous and nonaqueous) determined by both the traditional molar conductivity/PFG-NMR method and the ρ, η, λ method. We explore the effect of cation and anion alkyl chain length, structure, and interaction motifs of the cation and anion, temperature, and the strength of the solvent in IL solutions.
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Affiliation(s)
- Oscar Nordness
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, United States
| | - Joan F Brennecke
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, United States
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28
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Kang X, Lv Z, Chen Z, Zhao Y. Prediction of ammonia absorption in ionic liquids based on extreme learning machine modelling and a novel molecular descriptor S EP. ENVIRONMENTAL RESEARCH 2020; 189:109951. [PMID: 32777637 DOI: 10.1016/j.envres.2020.109951] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/07/2020] [Accepted: 07/12/2020] [Indexed: 06/11/2023]
Abstract
The large amounts of ammonia emissions generated from industrial production have caused serious environmental pollution problems, such as soil acidification, eutrophication, the formation of fine particles and changes in the global greenhouse balance, and also greatly endanger human health. At present, effectively reducing ammonia emissions or recovering ammonia is still a huge challenge. Ionic liquids (ILs) as a new class of green solvent have been introduced for ammonia absorption with great potential, but a huge number on combination systems of ILs lead to the difficulty of measuring the ammonia solubility in all ILs by experiments (e.g., danger and cost). Hereby, this study proposed a novel approach for estimating the ammonia solubility in different ILs. A predictive model was developed based on the novel Algorithm - extreme learning machine (ELM) and the molecular descriptors of electrostatic potential surface areas (SEP) as input parameters. Besides, 502 data points of ammonia solubility in 17 ILs were gathered with a wide range of pressure and temperature. For the total set, the determination coefficient (R2) and the average absolute relative deviation (AARD) of the developed model were 0.9937 and 2.95%, respectively. The regression plots revealed good consistency between predictive and experimental data points. Results show the good performance and reliability of the developed model, indicating that the proposed approach can be potentially applied for screening reasonable ILs to absorb ammonia from chemical industry processes.
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Affiliation(s)
- Xuejing Kang
- The Key Laboratory of Biotechnology for Medicinal Plants of Jiangsu Province, Jiangsu Normal University, Shanghai Road 101, 221116, Xuzhou, China; Department of Applied Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, 16500, Prague 6, Czech Republic
| | - Zuopeng Lv
- The Key Laboratory of Biotechnology for Medicinal Plants of Jiangsu Province, Jiangsu Normal University, Shanghai Road 101, 221116, Xuzhou, China
| | - Zhongbing Chen
- Department of Applied Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, 16500, Prague 6, Czech Republic.
| | - Yongsheng Zhao
- Department of Chemical Engineering, University of California, Santa Barbara, CA, 93106-5080, USA.
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29
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Chen Y, Liu X, Woodley JM, Kontogeorgis GM. Gas Solubility in Ionic Liquids: UNIFAC-IL Model Extension. Ind Eng Chem Res 2020. [DOI: 10.1021/acs.iecr.0c02769] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Yuqiu Chen
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Xinyan Liu
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark
- Beijing Key Laboratory of Ionic Liquids Clean Process, CAS Key Laboratory of Green Process and Engineering, State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, 100190 Beijing, China
| | - John M. Woodley
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Georgios M. Kontogeorgis
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark
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