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Palomar J, Lemus J, Navarro P, Moya C, Santiago R, Hospital-Benito D, Hernández E. Process Simulation and Optimization on Ionic Liquids. Chem Rev 2024; 124:1649-1737. [PMID: 38320111 PMCID: PMC10906004 DOI: 10.1021/acs.chemrev.3c00512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/16/2023] [Accepted: 01/10/2024] [Indexed: 02/08/2024]
Abstract
Ionic liquids (ILs) are promising alternative compounds that enable the development of technologies based on their unique properties as solvents or catalysts. These technologies require integrated product and process designs to select ILs with optimal process performances at an industrial scale to promote cost-effective and sustainable technologies. The digital era and multiscale research methodologies have changed the paradigm from experiment-oriented to hybrid experimental-computational developments guided by process engineering. This Review summarizes the relevant contributions (>300 research papers) of process simulations to advance IL-based technology developments by guiding experimental research efforts and enhancing industrial transferability. Robust simulation methodologies, mostly based on predictive COSMO-SAC/RS and UNIFAC models in Aspen Plus software, were applied to analyze key IL applications: physical and chemical CO2 capture, CO2 conversion, gas separation, liquid-liquid extraction, extractive distillation, refrigeration cycles, and biorefinery. The contributions concern the IL selection criteria, operational unit design, equipment sizing, technoeconomic and environmental analyses, and process optimization to promote the competitiveness of the proposed IL-based technologies. Process simulation revealed that multiscale research strategies enable advancement in the technological development of IL applications by focusing research efforts to overcome the limitations and exploit the excellent properties of ILs.
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Affiliation(s)
- Jose Palomar
- Chemical
Engineering Department, Autonomous University
of Madrid, Calle Tomás y Valiente 7, 28049 Madrid, Spain
| | - Jesús Lemus
- Chemical
Engineering Department, Autonomous University
of Madrid, Calle Tomás y Valiente 7, 28049 Madrid, Spain
| | - Pablo Navarro
- Chemical
Engineering Department, Autonomous University
of Madrid, Calle Tomás y Valiente 7, 28049 Madrid, Spain
| | - Cristian Moya
- Departamento
de Tecnología Química, Energética y Mecánica, Universidad Rey Juan Carlos, 28933 Madrid, Spain
| | - Rubén Santiago
- Departamento
de Ingeniería Eléctrica, Electrónica, Control,
Telemática y Química aplicada a la Ingeniería,
ETS de Ingenieros Industriales, Universidad
Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain
| | - Daniel Hospital-Benito
- Chemical
Engineering Department, Autonomous University
of Madrid, Calle Tomás y Valiente 7, 28049 Madrid, Spain
| | - Elisa Hernández
- Chemical
Engineering Department, Autonomous University
of Madrid, Calle Tomás y Valiente 7, 28049 Madrid, Spain
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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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Zhou T, Gui C, Sun L, Hu Y, Lyu H, Wang Z, Song Z, Yu G. Energy Applications of Ionic Liquids: Recent Developments and Future Prospects. Chem Rev 2023; 123:12170-12253. [PMID: 37879045 DOI: 10.1021/acs.chemrev.3c00391] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
Ionic liquids (ILs) consisting entirely of ions exhibit many fascinating and tunable properties, making them promising functional materials for a large number of energy-related applications. For example, ILs have been employed as electrolytes for electrochemical energy storage and conversion, as heat transfer fluids and phase-change materials for thermal energy transfer and storage, as solvents and/or catalysts for CO2 capture, CO2 conversion, biomass treatment and biofuel extraction, and as high-energy propellants for aerospace applications. This paper provides an extensive overview on the various energy applications of ILs and offers some thinking and viewpoints on the current challenges and emerging opportunities in each area. The basic fundamentals (structures and properties) of ILs are first introduced. Then, motivations and successful applications of ILs in the energy field are concisely outlined. Later, a detailed review of recent representative works in each area is provided. For each application, the role of ILs and their associated benefits are elaborated. Research trends and insights into the selection of ILs to achieve improved performance are analyzed as well. Challenges and future opportunities are pointed out before the paper is concluded.
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Affiliation(s)
- Teng Zhou
- Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
- HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen 518048, China
| | - Chengmin Gui
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Longgang Sun
- Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
| | - Yongxin Hu
- Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
| | - Hao Lyu
- Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
| | - Zihao Wang
- Department for Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, D-39106 Magdeburg, Germany
| | - Zhen Song
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Gangqiang Yu
- Faculty of Environment and Life, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China
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Fleitmann L, Gertig C, Scheffczyk J, Schilling J, Leonhard K, Bardow A. From Molecules to Heat‐Integrated Processes: Computer‐Aided Design of Solvents and Processes Using Quantum Chemistry. CHEM-ING-TECH 2022. [DOI: 10.1002/cite.202200098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Affiliation(s)
- Lorenz Fleitmann
- ETH Zürich Department of Mechanical and Process Engineering, Energy and Process Systems Engineering Tannenstrasse 3 8092 Zürich Switzerland
- RWTH Aachen University Institute of Technical Thermodynamics Schinkelstraße 8 52062 Aachen Germany
| | - Christoph Gertig
- RWTH Aachen University Institute of Technical Thermodynamics Schinkelstraße 8 52062 Aachen Germany
| | - Jan Scheffczyk
- RWTH Aachen University Institute of Technical Thermodynamics Schinkelstraße 8 52062 Aachen Germany
| | - Johannes Schilling
- ETH Zürich Department of Mechanical and Process Engineering, Energy and Process Systems Engineering Tannenstrasse 3 8092 Zürich Switzerland
| | - Kai Leonhard
- RWTH Aachen University Institute of Technical Thermodynamics Schinkelstraße 8 52062 Aachen Germany
| | - André Bardow
- ETH Zürich Department of Mechanical and Process Engineering, Energy and Process Systems Engineering Tannenstrasse 3 8092 Zürich Switzerland
- RWTH Aachen University Institute of Technical Thermodynamics Schinkelstraße 8 52062 Aachen Germany
- Forschungszentrum Jülich GmbH Institute of Energy and Climate Research (IEK-10) Wilhelm-Johnen-Straße 52425 Jülich Germany
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Foorginezhad S, Yu G, Ji X. Reviewing and screening ionic liquids and deep eutectic solvents for effective CO2 capture. Front Chem 2022; 10:951951. [PMID: 36034653 PMCID: PMC9399623 DOI: 10.3389/fchem.2022.951951] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/05/2022] [Indexed: 11/13/2022] Open
Abstract
CO2 capture is essential for both mitigating CO2 emissions and purifying/conditioning gases for fuel and chemical production. To further improve the process performance with low environmental impacts, different strategies have been proposed, where developing liquid green absorbent for capturing CO2 is one of the effective options. Ionic liquids (IL)/deep eutectic solvents (DES) have recently emerged as green absorbents with unique properties, especially DESs also benefit from facile synthesis, low toxicity, and high biodegradability. To promote their development, this work summarized the recent research progress on ILs/DESs developed for CO2 capture from the aspects of those physical- and chemical-based, and COSMO-RS was combined to predict the properties that are unavailable from published articles in order to evaluate their performance based on the key properties for different IL/DES-based technologies. Finally, top 10 ILs/DESs were listed based on the corresponding criteria. The shared information will provide insight into screening and further developing IL/DES-based technologies for CO2 capture.
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Affiliation(s)
- Sahar Foorginezhad
- Energy Science/Energy Engineering, Department of Engineering Sciences and Mathematics, Luleå University of Technology, Luleå, Sweden
| | - Gangqiang Yu
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
- *Correspondence: Gangqiang Yu, ; Xiaoyan Ji,
| | - Xiaoyan Ji
- Energy Science/Energy Engineering, Department of Engineering Sciences and Mathematics, Luleå University of Technology, Luleå, Sweden
- *Correspondence: Gangqiang Yu, ; Xiaoyan Ji,
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7
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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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Chen M, Dai C, Yu G, Liu N, Xu R, Wang N, Chen B. Highly efficient absorption of methyl tert-butyl ether with ionic liquids. Sep Purif Technol 2022. [DOI: 10.1016/j.seppur.2021.120108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Gui C, Li G, Zhu R, Liu Q, Lei Z. Ionic Liquids for Capturing 1,2-Dimethoxyethane (DMET) in VOCs: Experiment and Mechanism Exploration. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.1c04554] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Chengmin Gui
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
| | - Guoxuan Li
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
| | - Ruisong Zhu
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
| | - Qinghua Liu
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
| | - Zhigang Lei
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China
- School of Chemistry and Chemical Engineering, Shihezi University, Shihezi 832003, China
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10
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High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation. Processes (Basel) 2022. [DOI: 10.3390/pr10010165] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/10/2022] Open
Abstract
The separation of 1,3-butadiene (1,3-C4H6) and 1-butene (n-C4H8) is quite challenging due to their close boiling points and similar molecular structures. Extractive distillation (ED) is widely regarded as a promising approach for such a separation task. For ED processes, the selection of suitable entrainer is of central importance. Traditional ED processes using organic solvents suffer from high energy consumption. To tackle this issue, the utilization of ionic liquids (ILs) can serve as a potential alternative. In this work, a high-throughput computational screening of ILs is performed to find proper entrainers, where 36,260 IL candidates comprising of 370 cations and 98 anions are involved. COSMO-RS is employed to calculate the infinite dilution extractive capacity and selectivity of the 36,260 ILs. In doing so, the ILs that satisfy the prespecified thermodynamic criteria and physical property constraints are identified. After the screening, the resulting IL candidates are sent for rigorous process simulation and design. 1,2,3,4,5-pentamethylimidazolium methylcarbonate is found to be the optimal IL solvent. Compared with the benchmark ED process where the organic solvent N-methyl-2-pyrrolidone is adopted, the energy consumption is reduced by 26%. As a result, this work offers a new IL-based ED process for efficient 1,3-C4H6 production.
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11
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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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12
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Silva-Beard A, Flores-Tlacuahuac A, Rivera-Toledo M. Optimal computer-aided molecular design of ionic liquid mixtures for post-combustion carbon dioxide capture. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2021.107622] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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13
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Chai S, Li E, Zhang L, Du J, Meng Q. Crystallization solvent design based on a new quantitative prediction model of crystal morphology. AIChE J 2021. [DOI: 10.1002/aic.17499] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Shiyang Chai
- Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology Dalian China
| | - Enhui Li
- Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology Dalian China
| | - Lei Zhang
- Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology Dalian China
| | - Jian Du
- Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology Dalian China
| | - Qingwei Meng
- Department of Pharmaceutical Science School of Chemical Engineering, Dalian University of Technology Dalian China
- Ningbo Institute of Dalian University of Technology Ningbo China
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Machine Learning in Chemical Product Engineering: The State of the Art and a Guide for Newcomers. Processes (Basel) 2021. [DOI: 10.3390/pr9081456] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Chemical Product Engineering (CPE) is marked by numerous challenges, such as the complexity of the properties–structure–ingredients–process relationship of the different products and the necessity to discover and develop constantly and quickly new molecules and materials with tailor-made properties. In recent years, artificial intelligence (AI) and machine learning (ML) methods have gained increasing attention due to their performance in tackling particularly complex problems in various areas, such as computer vision and natural language processing. As such, they present a specific interest in addressing the complex challenges of CPE. This article provides an updated review of the state of the art regarding the implementation of ML techniques in different types of CPE problems with a particular focus on four specific domains, namely the design and discovery of new molecules and materials, the modeling of processes, the prediction of chemical reactions/retrosynthesis and the support for sensorial analysis. This review is further completed by general guidelines for the selection of an appropriate ML technique given the characteristics of each problem and by a critical discussion of several key issues associated with the development of ML modeling approaches. Accordingly, this paper may serve both the experienced researcher in the field as well as the newcomer.
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