Integrated ionic liquid and rate‐based absorption process design for gas separation: Global optimization using hybrid models

Process Simulation and Optimization on Ionic Liquids

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.

Computer-Aided Molecular Design of Ionic Liquids as Advanced Process Media: A Review from Fundamentals to Applications

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.

Energy Applications of Ionic Liquids: Recent Developments and Future Prospects

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.

Reviewing and screening ionic liquids and deep eutectic solvents for effective CO2 capture

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.

High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation

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.

Machine Learning in Chemical Product Engineering: The State of the Art and a Guide for Newcomers

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.