Maria Gonzalez-Miquel

Anion effects on kinetics and thermodynamics of CO2 absorption in ionic liquids

A thermogravimetric technique based on a magnetic suspension balance operating in dynamic mode was used to study the thermodynamics (in terms of solubility and Henrys law constants) and kinetics (i.e., diffusion coefficients) of CO2 in the ionic liquids [bmim][PF6], [bmim][NTf2], and [bmim][FAP] at temperatures of 298.15, 308.15, and 323.15 K and pressures up to 20 bar. The experimental technique employed was shown to be a fast, accurate, and low-solvent-consuming method to evaluate the suitability of the ionic liquids (ILs) to be used as CO2 absorbents. Thermodynamic results confirmed that the solubility of CO2 in the ILs followed the order [bmim][FAP] > [bmim][NTf2] > [bmim][PF6], increasing with decreasing temperatures and increasing pressures. Kinetic data showed that the diffusion coefficients of CO2 in the ILs followed a different order, [bmim][NTf2] > [bmim][FAP] > [bmim][PF6], increasing with increasing temperatures and pressures. These results evidenced the different influence of the IL structure and operating conditions on the solubility and absorption rate of CO2, illustrating the importance of considering both thermodynamic and kinetic aspects to select adequate ILs for CO2 absorption. On the other hand, the empirical Wilke-Chang correlation was successfully applied to estimate the diffusion coefficients of the systems, with results indicating the suitability of this approach to foresee the kinetic performance of ILs to absorb CO2. The research methodology proposed herein might be helpful in the selection of efficient absorption solvents based on ILs for postcombustion CO2 capture.

Selection of Ionic Liquids for Enhancing the Gas Solubility of Volatile Organic Compounds

A systematic thermodynamic analysis has been carried out for selecting cations and anions to enhance the absorption of volatile organic compounds (VOCs) at low concentration in gaseous streams by ionic liquids (ILs), using COSMO-RS methodology. The predictability of computational procedure was validated by comparing experimental and COSMO-RS calculated Henrys law constant data over a sample of 125 gaseous solute-IL systems. For more than 2400 solute-IL mixtures evaluated, including 9 solutes and 270 ILs, it was found that the lower the activity coefficient at infinite dilution (γ(∞)) of solutes in the ILs, the more the exothermic excess enthalpy (H(E)) of the equimolar IL-solute mixtures. Then, the solubility of a representative sample of VOC solutes, with very different chemical nature, was screened in a wide number of ILs using COSMO-RS methodology by means of γ(∞) and H(E) parameters, establishing criteria to select the IL structures that promote favorable solute-solvent intermolecular interactions. As a result of this analysis, an attempt of classification of VOCs respect to their potential solubility in ILs was proposed, providing insights to rationally select the cationic and anionic species for a possible development of absorption treatments of VOC pollutants based on IL systems.

Excess enthalpy of monoethanolamine + ionic liquid mixtures: how good are COSMO-RS predictions?

Mixtures of ionic liquids (ILs) and molecular amines have been suggested for CO2 capture applications. The basic idea is to replace water, which volatilizes in the amine regeneration step and increases the parasitic energy load, with a nonvolatile ionic liquid solvent. To fully understand the thermodynamics of these systems, here experimental excess enthalpies for binary mixtures of monoethanolamine (MEA) and two ILs: 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [hmim][NTf2], and 1-(2-hydroxyethyl)-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [OHemim][NTf2], were obtained by calorimetry, using a Setaram C80 calorimeter, over the whole range of compositions at 313.15 K. Since it is the temperature derivative of the Gibbs energy, enthalpy is a sensitive measure of intermolecular interactions. MEA + [hmim][NTf2] is endothermic and MEA + [OHemim][NTf2] is exothermic. The reliability of COSMO-RS to predict the excess enthalpy of the (MEA+IL) systems was tested based on the implementation of two different molecular models to define the structure of the IL: the IL as separate cation and anion [C+A] and the IL as a bonded single specie [CA]. Quantum-chemical calculations were performed to gain additional insight into the intermolecular interactions between the components of the mixture. For MEA + [hmim][NTf2] both the [C+A] and [CA] models predict endothermic behavior, but the [CA] model is in better agreement with the experimental results. For MEA + [OHemim][NTf2] the [C+A] model provides the best match to the experimental exothermic results. However, what is really surprising is that two different conformations of the cation-anion pair with nearly identical energies in the [CA] model result in completely different (exothermic vs endothermic) predictions of the excess enthalpy. Nonetheless, the results do show that the influence of the structure of the IL on the thermodynamic behavior of the mixture (endothermic vs exothermic) can be attributed to hydrogen bonding between the cation and the MEA molecule. However, this study highlights the importance of carefully selecting the molecular model and conformation in order to obtain even qualitatively correct predictions with COSMO-RS. The fact that even very slightly different conformations of the IL can drastically change the thermodynamic estimations using COSMO-RS is of significant concern. Overall, we believe the present work provides a better understanding of the behavior of mixtures involving amines and ILs, which is an important aspect to consider when evaluating the use of such solvent mixtures in CO2 capture technologies.

Multi-criteria screening of chemicals considering thermodynamic and life cycle assessment metrics via data envelopment analysis: application to CO2 capture

With the growing trend of incorporating sustainability principles in the chemical industry, there is a clear need to develop decision-making tools to quantify and optimise the sustainability level of chemical products and processes. In this study, we propose a systematic approach based on Data Envelopment Analysis (DEA) for the multi-criteria screening of molecules according to techno-economic and environmental aspects. The main advantage of our method is that it does not require any articulation of preferences via subjective weighting of the assessment criteria. Furthermore, our approach identifies the most efficient chemicals (according to some sustainability criteria) and for the ones found to be inefficient it establishes in turn improvement targets that can be used to guide research efforts in green chemistry. Our method was applied to the screening of 125 amine-based solvents for CO2 capture considering 10 different performance indicators, which are relevant to technical, health, safety and environmental aspects, including CO2 solubility, molar volume, surface tension, heat capacity, viscosity, vapour pressure, mobility, fire & explosion, acute toxicity and Eco-indicator 99. Our approach eliminates 36% of the solvents (as they are found to be inefficient), identifies the main sources of inefficiency (e.g., properties displaying poor values that should be improved) and ranks the best chemicals according to an objective criterion that does not rely on weights. Overall, our proposed DEA-based framework offers insightful guidance to make chemicals more sustainable.

Recovery of tyrosol from aqueous streams using hydrophobic ionic liquids: a first step towards developing sustainable processes for olive mill wastewater (OMW) management

Tyrosol is a high-value added polyphenolic compound with inherent antioxidant properties and increasing market demand for pharmaceutical, cosmetic and food industry applications. As a natural occurring antioxidant, the main source of tyrosol is olive mill wastewater (OMW), a by-product of olive oil processing that causes serious environmental issues due to its large volumes with high organic loads. Therefore, the valorization of OMW by recovering valuable antioxidants whilst reducing the overall toxicity of the aqueous stream is an attractive approach to promote sustainable OMW treatment and management. Herein we propose the utilization of hydrophobic ionic liquids (ILs) to replace conventional volatile organic compounds (VOCs) as extraction solvents to recover tyrosol from aqueous solutions. The operating temperature, the solvent to feed ratio, the effect of salt addition, the solvent physical properties and the solvent structure have been studied to optimize the extraction efficiency of tyrosol from water using [P4441][Tf2N], [N4441][Tf2N], and [N8881][Tf2N] ILs. Comprehensive experimental comparisons using ethyl acetate as a benchmark VOC solvent for tyrosol recovery have been performed. Moreover, the regeneration of the ILs and their subsequent recycling into the tyrosol extraction process have been addressed. Results show the capability of the aforementioned ILs to efficiently recover tyrosol under optimum operating conditions. Adding sodium salts, mainly NaCl, was proven to enhance the tyrosol selectivity towards the IL phase. Moreover, the solubility of ILs in the aqueous phase was found negligible, unlike ethyl acetate, and the water solubility in ethyl acetate was notably higher than in the hydrophobic ILs. Furthermore, back-extraction of tyrosol using inexpensive NaOH followed by IL recycling into the extraction process was successfully accomplished. Additional quantum chemical calculations were performed to provide insights into the behaviour of tyrosol–IL systems. Finally, [P4441][Tf2N] was revealed particularly promising for tyrosol recovery, providing similar extraction efficiency as conventional VOC solvents, proven capacity for regeneration and subsequent recycling, and adequate physical properties.

Sustainable joint solventless coproduction of glycerol carbonate and ethylene glycol via thermal transesterification of glycerol

This study focuses on the thermal reaction between glycerol and ethylene carbonate to obtain glycerol carbonate and ethylene glycol under solventless homogeneous operation, the process being a transcarbonation of glycerol or a glycerolysis of ethylene carbonate. As the two reagents constitute an immiscible system at 40 °C evolving into a single phase at 80 °C, the evolution of phases with temperature was studied by focused beam reflectance measurement. As the biphasic system was inert, runs were completed under a monophasic regime from 100 to 140 °C with molar ratios of ethylene carbonate to glycerol of 2 and 3, achieving quantitative conversion of glycerol, as corroborated by a thermodynamic study. Second order potential kinetic models were proposed and fitted to the data. Finally, a comparison with analogous catalytic approaches was made, showing that this process performs better material-wise.

Solubility of CO2 in [1-n-butylthiolanium][Tf2N]+ toluene mixtures: liquid–liquid phase split separation and modelling

Carbon dioxide has been shown to be an effective antisolvent gas for separating organic compounds from ionic liquids (ILs) by inducing a liquid–vapour to liquid–liquid–vapour transition. Using carbon dioxide, toluene can be separated from imidazolium, phosphonium and pyridinum cation-based ILs with the bis(trifluoromethylsulfonyl)imide anion, which is relatively hydrophobic and has a high toluene solubility. A new IL with relatively low viscosity is tested here for the same toluene separation process: 1-n-butylthiolanium bis(trifluoromethylsulfonyl)imide. Carbon dioxide solubility in binary and ternary systems containing toluene and 1-n-butylthiolanium bis(trifluoromethylsulfonyl)imide is measured at 298.15 and 313.15 K up to 7.4 MPa. Solubility behaviour in this IL is similar to imidazolium-based ILs with the same anion. However, phase split pressures are lower when 1-n-butylthiolanium bis (trifluoromethylsulfonyl)imide is used instead of 1- n-hexyl-3-methylimidazolium bis(trifluoromethylsu- lfonyl)imide at the same conditions of temperature and initial composition of toluene in the IL. Solubility data are modelled with the conductor-like screening model for real solvents combined with the Soave–Redlich–Kwong equation of state, which provides good qualitative results.

Enhanced microalgal lipid extraction using bio-based solvents for sustainable biofuel production

Global energy crisis and climate change urge to find alternative energy sources to help in transitioning from a petroleum-based to a more sustainable bio-based economy. In this context, microalgal biomass is regarded as a promising renewable energy feedstock for biodiesel production due to its high lipid accumulation and growth rate. Conventional extraction methods for lipid recovery from microalgae rely on hazardous petroleum-derived volatile organic compounds (VOCs), such as hexane, which is being strictly regulated in the chemical industry. Therefore, the goal of this work is to assess the feasibility of using renewable bio-based solvents for microalgal lipid extraction to develop environmentally-friendly biofuel production processes. In particular, lipid extraction studies were conducted on two microalgal strains, Chlorella vulgaris and Nannochloropsis sp., via the Soxhlet method using various bio-based solvents (i.e. ethyl acetate, ethyl lactate, cyclopentyl methyl ether (CPME) and 2-methyltetrahydrofuran (2-MeTHF)), compared to the benchmark VOC solvent (hexane). All bio-based solvents outperform the extraction capacity of hexane, with 2-MeTHF and ethyl lactate, respectively, providing two-fold and three-fold lipid extraction yields in comparison with the conventional solvent, hexane. Moreover, fatty acid methyl ester (FAME) profiles produced from both strains indicate the suitability of bio-based solvents to extract target lipids for biodiesel production. In addition, the overall biodiesel yield is significantly increased when using bio-based solvents for microalgal lipid extraction, with 2-MeTHF duplicating the overall biodiesel yield provided by hexane in both strains, Chlorella vulgaris and Nannochloropsis sp. Lipid extraction with ethyl lactate also duplicates the overall biodiesel yield produced from Chlorella vulgaris. Furthermore, bio-based solvents decrease the level of polyunsaturated fatty acids present in the extracts, hence increasing the biodiesel quality for practical applications. Overall, bio-based solvents exhibit the potential for replacing hexane in developing sustainable processes for biodiesel production. Thus, these findings support the role of renewable solvents in developing eco-efficient processes for biofuel production towards building a bio-economy based on renewable sources.

Predicting the cradle-to-gate environmental impact of chemicals from molecular descriptors and thermodynamic properties via mixed-integer programming

Life Cycle Assessment (LCA) has recently gained wide acceptance in the environmental impact evaluation of chemicals. Unfortunately, LCA studies require large amounts of data that are hard to gather in practice, a critical limitation when assessing the processes and value chains present in the chemical industry. We here develop an approach that predicts the cradle-to-gate life cycle production impact of organic chemicals from attributes related to their molecular structure and thermodynamic properties. This method is based on a mixed-integer programming (MIP) optimisation framework that systematically constructs short-cut predictive models of life cycle impact. On applying our approach to a data set containing 88 chemicals, 17 molecular descriptors and 15 thermodynamic properties, we estimate with enough accuracy (for the purposes of a standard LCA) several impact categories widely applied in LCA studies, including the cumulative energy demand, global warming potential and Eco-indicator 99. Our framework ultimately leads to linear models that can be easily integrated into existing modelling and optimisation software, thereby facilitating the design of more sustainable processes.

COSMO-derived descriptors applied in ionic liquids physical property modelling using machine learning algorithms

Abstract An application of machine learning algorithms for the prediction of physical properties of ionic liquids is presented herein. Molecular descriptors obtained from quantum-chemistry calculations (COSMO theory (Klamt, 2004)) containing both structural and energetic information are used as input parameters. In this sense, a set of COSMO-based descriptors is proposed by reduction of the original σ-profile (51 descriptors reduced to 9 bins). A critically evaluated set of viscosity data is used for a large number of ionic liquids (159). Artificial neural networks are then trained for the correlation of liquid viscosity and compared with available tools (QSPR).