Data-Driven Ionic Liquid Design for CO2 Capture: Molecular Structure Optimization and DFT Verification

Prediction of CO2 solubility in Ionic liquids for CO2 capture using deep learning models

Ionic liquids (ILs) are highly effective for capturing carbon dioxide (CO2). The prediction of CO2 solubility in ILs is crucial for optimizing CO2 capture processes. This study investigates the use of deep learning models for CO2 solubility prediction in ILs with a comprehensive dataset of 10,116 CO2 solubility data in 164 kinds of ILs under different temperature and pressure conditions. Deep neural network models, including Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM), were developed to predict CO2 solubility in ILs. The ANN and LSTM models demonstrated robust test accuracy in predicting CO2 solubility, with coefficient of determination (R2) values of 0.986 and 0.985, respectively. Both model's computational efficiency and cost were investigated, and the ANN model achieved reliable accuracy with a significantly lower computational time (approximately 30 times faster) than the LSTM model. A global sensitivity analysis (GSA) was performed to assess the influence of process parameters and associated functional groups on CO2 solubility. The sensitivity analysis results provided insights into the relative importance of input attributes on output variables (CO2 solubility) in ILs. The findings highlight the significant potential of deep learning models for streamlining the screening process of ILs for CO2 capture applications.

Hydrocarbon Extraction with Ionic Liquids

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.

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.

Understanding the role of imidazolium-based ionic liquids in the electrochemical CO2 reduction reaction

The development of efficient CO2 capture and utilization technologies driven by renewable energy sources is mandatory to reduce the impact of climate change. Herein, seven imidazolium-based ionic liquids (ILs) with different anions and cations were tested as catholytes for the CO2 electrocatalytic reduction to CO over Ag electrode. Relevant activity and stability, but different selectivities for CO2 reduction or the side H2 evolution were observed. Density functional theory results show that depending on the IL anions the CO2 is captured or converted. Acetate anions (being strong Lewis bases) enhance CO2 capture and H2 evolution, while fluorinated anions (being weaker Lewis bases) favour the CO2 electroreduction. Differently from the hydrolytically unstable 1-butyl-3-methylimidazolium tetrafluoroborate, 1-Butyl-3-Methylimidazolium Triflate was the most promising IL, showing the highest Faradaic efficiency to CO (>95%), and up to 8 h of stable operation at high current rates (-20 mA & -60 mA), which opens the way for a prospective process scale-up.

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.

Low-temperature Hg0 abatement by ionic liquid based on weak interaction

Low-temperature gaseous elemental mercury (Hg⁰) abatement is an objective demand in industrial flue gas treatment. In this work, we proposed a new approach for Hg⁰ capture via weak interaction of ionic liquids. Ionic liquids with varied anions (1-butyl-3-methylimidazolium thioacetate ([Bmim][ThAc]), 1-butyl-3-methylimidazolium diethyldithiocarbamate ([Bmim][DTCR]), and 1-butyl-3-methylimidazolium ethylxanthate ([Bmim][EX])) were designed and synthesized. The interaction energies between ionic liquids and elemental mercury were proved to be positively related to mercury removal efficiency, revealing that the electrostatic interaction derived physical adsorption from anions is the dominant factor affecting mercury removal performance. [Bmim][ThAc] with the largest anionic electrostatic interaction energy showed the best mercury abatement performance, achieving a Hg⁰ removal efficiency of over 98% and an adsorption capacity of 10.66 mg/g at 50 °C. The influence of temperature and the results of mercury temperature-programmed desorption (Hg-TPD), X-ray photoelectron spectroscopy (XPS) further confirmed that the ionic liquid combines with elemental mercury through physical adsorption. The work provides a new perspective on designing high-efficiency sorbents for mercury removal at low temperature.

The State-of-the-Art Functionalized Nanomaterials for Carbon Dioxide Separation Membrane

Nanocomposite membrane (NCM) is deemed as a practical and green separation solution which has found application in various fields, due to its potential to delivery excellent separation performance economically. NCM is enabled by nanofiller, which comes in a wide range of geometries and chemical features. Despite numerous advantages offered by nanofiller incorporation, fabrication of NCM often met processing issues arising from incompatibility between inorganic nanofiller and polymeric membrane. Contemporary, functionalization of nanofiller which modify the surface properties of inorganic material using chemical agents is a viable approach and vigorously pursued to refine NCM processing and improve the odds of obtaining a defect-free high-performance membrane. This review highlights the recent progress on nanofiller functionalization employed in the fabrication of gas-separative NCMs. Apart from the different approaches used to obtain functionalized nanofiller (FN) with good dispersion in solvent and polymer matrix, this review discusses the implication of functionalization in altering the structure and chemical properties of nanofiller which favor interaction with specific gas species. These changes eventually led to the enhancement in the gas separation efficiency of NCMs. The most frequently used chemical agents are identified for each type of gas. Finally, the future perspective of gas-separative NCMs are highlighted.

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.