Search

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Industrial and Engineering Chemistry Research, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/abs/10.1021/acs.iecr.9b04603, There are a large number of liquid-liquid extraction processes where ionic liquids (ILs) are proposed as solvents. However, the development of purification and IL regeneration units still represents a challenge. Several effective separation trains were proposed to regenerate ILs, but extreme vacuum is needed to achieve commercial standards, which demands extra energy and extra solvent consumptions due to recycling streams. In this proposal, the use of stripping columns stands as a promising IL regeneration technology to avoid vacuum conditions and to enhance the separation of the compounds that form the extract stream, explored in the aromatic-aliphatic separation. COSMO-based/Aspen Plus methodology is applied to extensively evaluate the role of the IL nature and easily evaluate the influence of the main operating variables, namely, temperature feed, column pressure, reboiler heat, and number of stages, in the separation efficiency. A critical comparison between the current proposal and the benchmark IL regeneration process is reported, analyzing the aromatic recovery, energy duty, and operating cost. The use of two stripping columns for the IL regeneration stage evidences the potential of this new configuration, drawing a new paradigm in which mild conditions are enough to conceptually design new separation processes involving ILs, The authors are grateful to Comunidad de Madrid (project P2018/EMT4348) and Ministerio de Economía y Competitividad of Spain (project CTQ2017-89441-R) for financial support and Centro de Computación Científica de la Universidad Autónoma de Madrid (CCC) for its computational resources

A COSMO-based/Aspen HYSYS methodology has been used to perform an extensive thermodynamic evaluation of potential application of ionic liquids (ILs) to absorption refrigeration cycles. By applying this a priori methodology, 7200 systems, formed by 900 ILs and 8 refrigerants, representative of available commercial/cation and refrigerant, were evaluated, which would be otherwise unviable due to the lack of experimental data. Firstly, COSMO-RS analysis was carried out for the preliminary selection of suitable ILs as absorbents for each refrigerant, by means of predicted values of Henry’s Law constants of refrigerants in ILs. Selected ILs were then introduced in Aspen HYSYS simulator database by using the molecular information by COSMO-RS method. The reliability of COSMO-based/Aspen HYSYS calculations was successfully validated by comparison to available experimental data (>2700 points) of pure and mixture properties of absorbent-refrigerant systems. Then, the performance of selected ILs (and other proposed in the bibliography) in absorption refrigeration cycles was evaluated by process simulations (>230 refrigerant/IL pairs studied at 60 different operating conditions) using COSMO-based/Aspen HYSYS methodology. Cycle efficiency was analyzed in terms of the coefficient of performance (COP), solution circulation ratio (f ratio) and the total mass flow pumped from the absorber to the generator, a new parameter proposed to compare the results obtained with different refrigerants. COSMO-based/Aspen HYSYS methodology allowed the selection of adequate refrigerant-absorbent pairs (refrigerant with high cooling capacities and IL with absorption capacity) competitive to conventional systems as H2O/LiBr or NH3/H2O. Furthermore, the analysis of operating condition effects by COSMO-based/Aspen HYSYS methodology allows selecting refrigerant/IL pairs with maximum efficiency in the cycle for a fixed cooling temperature, revealing additional advantage of the applications of IL in absorption refrigeration technologies., The authors are grateful to Comunidad Autónoma de Madrid for the Project S2013/MAE-2800 and to Ministerio de Economía y Competitividad (MINECO) of Spain for financial support of Project CTQ2017-89441-R. Marcos Larriba also thanks MINECO for awarding him a Juan de la Cierva-Formación Contract (Reference FJCI-2015-25343).

The ionic liquids (ILs) have been widely studied as potential replacements of conventional solvents in the extraction of aromatic hydrocarbons from alkanes. However, most of the literature is focused in obtaining liquid-liquid equilibria experimental data without studying the complete extraction and IL regeneration process. In this paper, a computer-aided methodology combining COSMO-based molecular simulations and Aspen Plus process simulations has been used to study the extraction process of aromatic hydrocarbons from pyrolysis gasoline employing a binary mixture of 1-ethyl-4-methylpyridinium bis(trifluoromethylsulfonyl)imide ([4empy][NTf2]) and the 1-ethyl-3-methylimidazolium dicyanamide ([emim][DCA]) ILs as solvent. An extensive comparison (more than 600 points) between experimental data and the predictions obtained by the COSMO-based thermodynamic model of liquid–liquid and vapor–liquid equilibria and ILs physical properties was made for validation purposes. Process simulations were performed in three system configurations: with one, two, or three flash distillations in the IL recovery section. The potential advantage of using binary IL-IL mixture as extracting solvent was studied in the whole range of composition. The configuration with three flash distillations and the binary IL-IL mixture with a 75% of [4empy][NTf2] were selected as the optimal conditions to increase aromatic recovery and purity, improving the separation performance respect to the neat ILs, The authors are grateful to Ministerio de Economía y Competitividad (MINECO) of Spain for financial support of Projects CTQ2014-52288-R and CTQ2014–53655-R and to Comunidad Autónoma de Madrid for the Project S2013/MAE-2800. Noemí Delgado-Mellado also thanks MINECO for awarding them an FPI grant (Reference BES–2015–072855) and Marcos Larriba also thanks MINECO for awarding him a Juan de la Cierva-Formación Contract (Reference FJCI-2015-25343). Pablo Navarro thanks Fundação para a Ciência e a Tecnologia for awarding him a postdoctoral grant (Reference SFRH/BPD/117084/2016).

Three different processes to separate aromatic hydrocarbons from a very low-aromatic-content (10 wt.%) naphtha with the 4-methyl-N-butylpyridinium tetrafluoroborate ionic liquid are analyzed. A computer-aid methodology recently developed in our group that integrates the molecular modeling and the process simulation via COSMO-based thermodynamic models in Aspen Plus is used. The most commonly drawn process scheme is proposed as Base Case Configuration and two alternative configurations, one adding water as a co-solvent (Configuration 1) and the other including a stripper between the extraction and the solvent regeneration (Configuration 2), are studied. The processes performance is evaluated through the aliphatic and aromatic product purities and recoveries, and the solvent and energy consumptions. The results show that the separation of aromatic hydrocarbons from this type of naphtha using ionic liquids is possible. The Base Case Configuration is not able to achieve the separation successfully. The addition of water as co-solvent guaranties this demand but increases the solvent and energy consumption. The intermediate stripper seems to be a promising alternative as it allows achieving high purity aliphatic and aromatic products without increasing the solvent or energy needs. The results demonstrate that the computational strategy used is capable to discriminate among complex and relatively similar process alternatives.

WILEY: "This is the peer reviewed version of the following article: ChemPhysChem 19.7 (2018): 801-815, which has been published in final form at http://doi.org/10.1002/cphc.201701093. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions." Este artículo apareció anteriormente con el siguiente título "Exploring molecular and thermodynamic properties of zwitterions vs ionic liquids: A comprehensive computational analysis to develop advanced separation processes", Zwitterion ionic liquids (ZIs) are compounds in which both counterions are covalently tethered, conferring them with unique characteristics; however, most of their properties are still unknown, representing a bottleneck to exploit their practical applications. Herein, the molecular and fluid properties of ZIs and their mixtures were explored by means of quantum chemical analysis based on the density functional theory (DFT) and COSMO-RS method, and compared against homologous ionic liquids (ILs) to provide a comprehensive overview of the effect of the distinct structures on their physicochemical and thermodynamic behavior. Overall, ZIs were revealed as compounds with higher polarity and stronger hydrogen-bonding capacity, implying higher density, viscosity, melting point, and even lower volatility than structurally similar ILs. The phase equilibrium of binary and ternary systems supports stronger attractive interactions between ZIs and polar compounds, whereas higher liquid–liquid immiscibility with nonpolar compounds may be expected. Ultimately, the performance of ZIs in the wider context of separation processes is illustrated, while providing molecular insights to allow their selection and design for relevant applications, The authors would like to acknowledge to Comunidad Autónoma de Madrid for the Project S2013/MAE-2800 and to Ministerio de Economía y Competitividad (MINECO) of Spain for financial support of Projects CTQ2014-52288-R. We are very grateful to Centro de Computación Científica de la Universidad Autónoma de Madrid for computational facilities. We all would like to acknowledge kind support in the framework of the COST Action EXIL-Exchange on Ionic Liquids (CM1206).

COSMO-based process simulations with Aspen Plus/Aspen HYSYS are used, for the first time, to a priori estimate the thermodynamic performance of ammonia absorption refrigeration cycles using ionic liquids as absorbents. This allows not only broadening the criteria set used to select/design ionic liquids with optimized properties to be used in that role, but also evaluating innovative strategies to improve the cycle’s performances. COSMO-RS method provides the information required for both creating the ionic liquid non-database components and specifying the COSMOSAC property model to perform Aspen Plus calculations. The computational procedure used here gives at the same time reasonable good property predictions of the vapor (refrigerant) and the condensed (ammonia + ionic liquid) phases as well as physically consistent estimations of the cycle’s performance under different conditions. Current results agree with those previously reported in the literature for several ionic liquid-based systems taken for comparison. In addition, task-specific ionic liquids, with improved properties for ammonia absorption, and also binary ionic liquid mixtures are considered in the analysis. It is obtained that ionic liquids showing higher ammonia absorption capacity among the considered absorbents simultaneously provide the best cycle’s performances. The cycle performances vary in relatively wide intervals depending on the ammonia concentration in the (refrigerant + absorbent) solutions. This behavior is strongly modulated by the ammonia absorption capacity of the selected absorbent. IL mixtures allow not only the tailoring of the working concentration interval of the cycle but also improving its performance.

Conductor-like-screening model for real solvents (COSMO-RS) method was used to analyze the solute-solvent interactions and to screen Henry's law constant of toluene over 272 ionic liquids (ILs), to select high-capacity absorbents. Thermogravimetric experiments were carried out to evaluate the toluene absorption by selected ILs at different temperatures and atmospheric pressure. Experimental equilibrium data were found in good agreement with COSMO-RS predictions. Complete desorption of toluene by N2 stripping was achieved, indicating an easy regeneration. The kinetic curves were described by a phenomenological diffusion model, obtaining effective diffusivities in reasonable concordance with those calculated by Wilke–Chang correlation. The separation process with selected ILs was modeled by Aspen Plus and a comparison with organic absorbents was carried out. Equilibrium- and rate-based simulations were used to analyze the importance of thermodynamics and kinetics in toluene absorption by ILs. Current computational-experimental research allowed selecting a set of suitable ILs for toluene absorption. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1648–1656, 2013

The integration of COSMO-RS methodology to Aspen Tech’s process simulators is used in this work to elaborate new criteria for the design/selection of ionic liquids to specific applications. These criteria are related to the operating conditions and energetic consumptions being the procedure capabilities demonstrated through the example of the IL regeneration in separation processes. Previously, the predictive capacity of the COSMO-RS method respect to VLE of mixtures (organic solvent + IL) is assessed and the correct transferability of the COSMO-RS results to Aspen Plus/Aspen HYSYS process simulators demonstrated.

In this work, the a priori computational tool for screening ILs, developed in previous part 1, is extended to the simultaneous prediction of a set of IL properties for 45 imidazolium-based ILs. In addition, current part 2 reports the development of a more useful design strategy, which introduces the target IL properties as input, resulting in the selections of counterions as output, that is directly designing ILs on the computer. For this purpose, inverse neural networks are used to estimate the Sσ-profile molecular descriptor of a potential IL solvent by the specification of its required properties, following a reverse quantitative structure−property relationship scheme. Subsequently, a statistical tool based on Euclidean distances is developed to select an adequate set of anion+cation combinations that fulfill the estimated Sσ-profile values, to obtain, in this case, the tailor-made ILs. Finally, the proposed computational tool for designing ILs is applied in liquid−liquid extraction of a system model (...

An innovative computational approach is proposed to design ionic liquids (ILs) based on a new a priori molecular descriptor of ILs, derived from quantum-chemical COSMO-RS methodology. In this work, the charge distribution on the polarity scale given by COSMO-RS is used to characterize the chemical nature of both the cations and anions of the IL structures, using simple molecular models in the calculations. As a result, a novel a priori quantum-chemical parameter, Sσ-profile, is defined for 45 imidazolium-based ILs, as a quantitative numerical indicator of their electronic structures and molecular sizes. Subsequently, neural networks (NNs) are successfully applied to establish a relationship between the electronic information given by the Sσ-profile molecular descriptor and the density properties of IL solvents. As a consequence, we develop here an a priori computational tool for screening ILs with required properties, using COSMO-RS predictions to NN design and optimization. Current methodology is validat...

The specific density and molar liquid volume of 40 imidazolium-based ionic liquids were predicted using the COSMO-RS method, a thermodynamic model based on quantum chemistry calculations. A molecular model of ion pairs was proposed to simulate the pure ionic liquid compounds. These ion-paired structures were generated at the B3LYP/6-31++G** computational level by combining the cations 1-methyl- (Mmim+), 1-ethyl- (Emim+), 1-butyl- (Bmim+), 1-hexyl- (Hxmim+), and 1-octyl-3-methylimidazolium (Omim+) with the anions chloride (Cl-), tetrafluoroborate (BF4-), tetrachloroferrate (FeCl4-), hexafluorophosphate (PF6-), bis(trifluoromethanesulfonyl)imide (Tf2N-), methylsulfate (MeSO4-), ethylsulfate (EtSO4-), and trifluoromethanesulfonate (CF3SO3-). Satisfactory agreement with the available experimental measurements was obtained, showing the capability of the current computational approach to describe the effect of the anion nature and cation substituent on the volumetric properties of this family of ionic liquids. ...

A COSMO-RS descriptor (S(sigma-profile)) has been used in quantitative structure-property relationship (QSPR) studies by a neural network (NN) for the prediction of empirical solvent polarity E(T)(N) scale of neat ionic liquids (ILs) and their mixtures with organic solvents. S(sigma-profile) is a two-dimensional quantum chemical parameter which quantifies the polar electronic charge of chemical structures on the polarity (sigma) scale. Firstly, a radial basis neural network exact fit (RBNN) is successfully optimized for the prediction of E(T)(N), the solvatochromic parameter of a wide variety of neat organic solvents and ILs, including imidazolium, pyridinium, ammonium, phosphonium and pyrrolidinium families, solely using the S(sigma-profile) of individual molecules and ions. Subsequently, a quantitative structure-activity map (QSAM), a new concept recently developed, is proposed as a valuable tool for the molecular understanding of IL polarity, by relating the E(T)(N) polarity parameter to the electronic structure of cations and anions given by quantum-chemical COSMO-RS calculations. Finally, based on the additive character of the S(sigma-profile) descriptor, we propose to simulate the mixture of IL-organic solvents by the estimation of the S(sigma-profile)(Mixture) descriptor, defined as the weighted mean of the S(sigma-profile) values of the components. Then, the E(T)(N) parameters for binary solvent mixtures, including ILs, are accurately predicted using the S(sigma-profile)(Mixture) values from the RBNN model previously developed for pure solvents. As result, we obtain a unique neural network tool to simulate, with similar reliability, the E(T)(N) polarity of a wide variety of pure ILs as well as their mixtures with organic solvents, which exhibit significant positive and negative deviations from ideality.

A new COSMO-RS descriptor (S(sigma-profile)) has been used in quantitative structure-property relationship (QSPR) studies based on neural networks (NN) for the prediction of polarity/polarizability scales of pure solvents and mixtures. S(sigma-profile) is a two-dimensional quantum chemical parameter which quantifies the polar electronic charge on the polarity (sigma) scale. Firstly, radial base neural networks (RBNN) are successfully optimized for the prediction of polarizability (SP) and polarity/polarizability (SPP) scales of pure solvents using the S(sigma-profile) of individual molecules. Subsequently, based on the additive character of the S(sigma-profile) parameter, we propose to simulate the solvents mixture by the estimation of S descriptor, defined as the weighted mean of S(sigma-profile) values of the components. Then, the SPP parameters for binary and ternary mixtures are accurately predicted using the S values into the RBNN model previously developed for pure solvents. As result, we obtain a unique neural network tool to simulate, with similar reliability, the polarity/polarizability of a wide variety of pure organic solvents as well as binary and ternary mixtures which exhibit significant deviations from ideality.