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.

Experimental and Theoretical Investigation on the Extractive Mass Transfer of Eu3+ Ions Using Novel Amide Ligands in 1-Hexyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide

Novel amide ligands in the ionic liquid (1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide) were utilized for the liquid-liquid biphasic mass transfer of Eu3+ ions from aqueous acidic waste solution. The cation exchange mechanism was found to be operative with the formation of [Eu(NO3)2L3]+ species (L = 4-chloro-N-(1-methyl-1H-pyrazol-3-yl)picolinamide). However, the presence of an inner-sphere water molecule was revealed by density functional theory (DFT) calculations. The viscosity-induced slower kinetics was evidenced during mass transfer, which was improved by increasing temperature. The process was exothermic in nature. The improvement in the kinetics of extractive mass transfer at higher temperatures is evinced by a reduction in the distribution ratio value. The spontaneity of the reaction was evidenced through the negative Gibbs free energy value, whereas the process enhances the entropy of the system, probably by releasing water molecules at least partially during complexation. The structures of bare ligands and complexes have been optimized by using DFT calculations. A high value of complexation energy, solvation energy, and associated enthalpy and free energy change reveal the efficacy in binding Eu with O and N donor atoms. In addition, natural population analysis, atoms-in-molecules analysis, and energy decomposition analysis have been employed to explore the nature of bonding existing in Eu-O and Eu-N bonds.

Toward the Proactive Design of Sustainable Chemicals: Ionic Liquids as a Prime Example

The tailorable and often unique properties of ionic liquids (ILs) drive their implementation into a broad variety of seminal technologies. The modular design of ILs allows in this context a proactive selection of structures that favor environmental sustainability─ideally without compromising their technological performance. To achieve this objective, the whole life cycle must be taken into account and various aspects considered simultaneously. In this review, we discuss how the structural design of ILs affects their environmental impacts throughout all stages of their life cycles and scrutinize the available data in order to point out knowledge gaps that need further research activities. The design of more sustainable ILs starts with the selection of the most beneficial precursors and synthesis routes, takes their technical properties and application specific performance into due account, and considers its environmental fate particularly in terms of their (eco)toxicity, biotic and abiotic degradability, mobility, and bioaccumulation potential. Special emphasis is placed on reported structure-activity relationships and suggested mechanisms on a molecular level that might rationalize the empirically found design criteria.

Review of the toxic effects of ionic liquids

Interest in ionic liquids (ILs), called green or designer solvents, has been increasing because of their excellent properties such as thermal stability and low vapor pressure; thus, they can replace harmful organic chemicals and help several industrial fields e.g., energy-storage materials production and biomaterial pretreatment. However, the claim that ILs are green solvents should be carefully considered from an environmental perspective. ILs, given their minimal vapor pressure, may not directly cause atmospheric pollution. However, they have the potential to cause adverse effects if leaked into the environment, for instance if they are spilled due to human mistakes or technical errors. To estimate the risks of ILs, numerous ILs have had their toxicity assessed toward several micro- and macro-organisms over the past few decades. Since the toxic effects of ILs depend on the method of estimating toxicity, it is necessary to briefly summarize and comprehensively discuss the biological effects of ILs according to their structure and toxicity testing levels. This can help simplify our understanding of the toxicity of ILs. Therefore, in this review, we discuss the key findings of toxicological information of ILs, collect some toxicity data of ILs to different species, and explain the influence of IL structure on their toxic properties. In the discussion, we estimated two different sensitivity values of toxicity testing levels depending on the experiment condition, which are theoretical magnitudes of the inherent sensitivity of toxicity testing levels in various conditions and their changes in biological response according to the change in IL structure. Finally, some perspectives, future research directions, and limitations to toxicological research of ILs, presented so far, are discussed.

Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models

In recent times, machine learning has become increasingly prominent in predictive toxicology as it has shifted from in vivo studies toward in silico studies. Currently, in vitro methods together with other computational methods such as quantitative structure-activity relationship modeling and absorption, distribution, metabolism, and excretion calculations are being used. An overview of machine learning and its applications in predictive toxicology is presented here, including support vector machines (SVMs), random forest (RF) and decision trees (DTs), neural networks, regression models, naïve Bayes, k-nearest neighbors, and ensemble learning. The recent successes of these machine learning methods in predictive toxicology are summarized, and a comparison of some models used in predictive toxicology is presented. In predictive toxicology, SVMs, RF, and DTs are the dominant machine learning methods due to the characteristics of the data available. Lastly, this review describes the current challenges facing the use of machine learning in predictive toxicology and offers insights into the possible areas of improvement in the field.

Assessing the ecotoxicity of ionic liquids on Vibrio fischeri using electrostatic potential descriptors

Ionic liquids (ILs) have attracted increasing attention both in the scientific community and the industry in the past two decades. Their risk of being inevitable released to ecosystem lights up the urgent research on their toxicity to the environment. To reduce the time and capital consumption on testing tremendous ILs ecotoxicity experimentally, it is essential to construct predictive models for estimating their toxicity. The objective of this study is to provide a new approach for evaluating the ecotoxicity of ILs. A comprehensive ecotoxicity dataset for Vibrio fischeri involving 142 ILs, was collected and investigated. The electrostatic potential surface areas (S_EP) of separate cations and anions of ILs were firstly applied to develop predictive models for ecotoxicity on Vibrio fischeri. In addition, an intelligent algorithm named extreme learning machine (ELM) was employed to establish the predictive model. The squared correlation coefficients (R²), the average absolute error (AAE%) and the root-mean-square error (RMSE) of the developed model are 0.9272, 0.2101 and 0.3262 for the entire set, respectively. The proposed approach based on the high R² and low deviation has remarkable potential for predicting ILs ecotoxicity on Vibrio fischeri.

Application of general toxic effects of ionic liquids to predict toxicities of ionic liquids to Spodoptera frugiperda 9, Eisenia fetida, Caenorhabditis elegans, and Danio rerio

Modeling for the toxicity of ionic liquids (ILs) is necessary to fill data gaps for untested chemicals and to understand the relevant mechanisms at the molecular level. In order for many researchers to easily predict toxicity and/or develop some prediction model, simple method(s) based on a single parameter should be proposed. Therefore, previously our group developed a comprehensive toxicity prediction model with unified linear free-energy relationship descriptors to address the single parameter for predicting the toxicities, as follows (Cho et al., 2016b). Log 1/toxicity in the unit of mM= (2.254 E_c - 2.545 S_c + 0.646 A_c - 1.471 B_c + 1.650 V_c + 2.917 J⁺ - 0.201 E_a + 0.418 V_a + 0.131 J^-) - 0.709. It is considered that the model can calculate the general toxicological effect of ILs in parenthesis, as it was developed on the basis of numerous toxic effects i.e., 58 toxicity testing methods and about 1600 data points. In order to check the hypothesis, the values calculated by the model were correlated with four different datasets from insect cell line (Spodoptera frugiperda 9), earthworm (Eisenia fetida), nematode (Caenorhabditis elegans), and fish (Danio rerio). The results clearly showed that the calculated values are in good agreement with each dataset. In the case of S. frugiperda 9 cells, the calculated parameters were correlated with log1/LC₅₀ values, measured after 24 h and 48 h incubation, in R² of 0.67 and 0.88, respectively. The R² values for the earthworm, nematode, and fish were 0.88, 0.96, and 0.94-0.95, respectively. This study confirmed that the comprehensive model can be simply and accurately used to predict toxicity of ILs.

A simple method for assessing chemical toxicity of ionic liquids on Vibrio fischeri through the structure of cations with specific anions

Both water and non-water soluble ionic liquids (ILs) may be toxic where ILs soluble in water can be released into aquatic ecosystems. Toxicity of ILs can be determined as effective nominal concentration EC₅₀ because it is important to assess the toxicity of ILs by an inhibition assay, which can evaluate the toxicological danger of ILs. A novel model is introduced for desk calculations of chemical toxicity of ILs based on Vibrio fischeri with more reliance on their answers as one could attach to the more complex outputs. It requires only specific elemental compositions of cations and anions as well as the presence of some molecular fragments in cations with particular anions. The measured values of logEC₅₀(/μM) for 187 ILs corresponding to 250 experimental data were used to derive and test of the new model. For 153 ILs (203 datapoints), where the reported values of logEC₅₀(/μM) as training and test sets by one of the best quantitative structure-activity relationship (QSAR) were available, the new method gives more reliable predictions. The present simple method is also tested with further 34 (47 datapoints), which confirm good forecasting reliability of the new model.

Ionic liquids-a novel material for planar photonics

Electron beam patterning is an important technology in the fabrication of miniaturized photonic devices. The fabrication process conventionally involves the use of radiation sensitive polymer-based solutions (called resists). We propose to replace typical polymer resists with eco-friendly solvent-free room temperature ionic liquids (RTILs), which are polymerized in situ and solidified by an electron beam. It is demonstrated that the shapes of polymerized structures are different for high-viscous Cl-based RTILs and low-viscous NTf₂-based RTILs. Due to the the satisfactory quality of the polymerized spatial microstructures and their light transmission properties, the RTIL-derived microstructures are potentially attractive as photonic elements for near-infrared.

Evaluation of the antioxidant properties of curcumin derivatives by genetic function algorithm

The prevalence of degenerative diseases in recent time has triggered extensive research on their control. This condition could be prevented if the body has an efficient antioxidant mechanism to scavenge the free radicals which are their main causes. Curcumin and its derivatives are widely employed as antioxidants. The free radical scavenging activities of curcumin and its derivatives have been explored in this research by the application of quantitative structure activity relationship (QSAR). The entire data set was optimized at the density functional theory (DFT) level using the Becke's three-parameter Lee-Yang-Parr hybrid functional (B3LYP) in combination with the 6-311G^∗ basis set. The training set was subjected to QSAR studies by genetic function algorithm (GFA). Five predictive QSAR models were developed and statistically subjected to both internal and external validations. Also the applicability domain of the developed model was accessed by the leverage approach. Furthermore, the variation inflation factor, (VIF), mean effect (MF) and the degree of contribution (DC) of each descriptor in the resulting model were calculated. The developed models met all the standard requirements for acceptability upon validation with highly impressive results (R=0.965,R2=0.931,Q2(RCV2)=0.887,Rpred2=0.844,cRp2=0.842s=0.226,rmsep=0.362). Based on the results of this research, the most crucial descriptor that influence the free radical scavenge of the curcumins is the nsssN (count of atom-type E-state: >N-) descriptor with DC and MF values of 12.980 and 0.965 respectively.

Development of QSAR model to predict the ecotoxicity of Vibrio fischeri using COSMO-RS descriptors

Ionic liquids (ILs) are class of solvent whose properties can be modified and tuned to meet industrial requirements. However, a high number of potentially available cations and anions leads to an even increasing members of newly-synthesized ionic liquids, adding to the complexity of understanding on their impact on aquatic organisms. Quantitative structure activity∖property relationship (QSAR∖QSPR) technique has been proven to be a useful method for toxicity prediction. In this work,σ-profile descriptors were used to build linear and non-linear QSAR models to predict the ecotoxicities of a wide variety of ILs towards bioluminescent bacterium Vibrio fischeri. Linear model was constructed using five descriptors resulting in high accuracy prediction of 0.906. The model performance and stability were ascertained using k-fold cross validation method. The selected descriptors set from the linear model was then used in multilayer perceptron (MLP) technique to develop the non-linear model, the accuracy of the model was further enhanced achieving high correlation coefficient with the lowest value being 0.961 with the highest mean square error of 0.157.

How the structure of ionic liquid affects its toxicity to Vibrio fischeri?

In the present work, we have proposed a statistical model predicting the toxicity of ionic liquids (ILs) to Vibrio fischeri bacteria using the Quantitative Structure-Activity Relationships (QSAR) method. The model was developed with Multiple Linear Regression (MLR) technique, using the Gutman molecular topological index (GMTI), the lopping centric information index (LOC) and the number of oxygen atoms. Presented model is characterized by the good fit to the experimental data (R(2) = 0.78), high robustness (Q(2)CV = 0.72) and good predictive ability (Q(2)EXT = 0.75). This approach, with using very simple descriptors, helps to initially evaluate the toxicity of newly designed ionic liquids. The studied toxicity of ionic liquids depends mainly on their cations' structure: larger, more branched cations with long alkyl chains are more toxic than the smaller, linear ones. The presence of polar functional groups in the cation's structure reduces the toxic properties of ionic liquids. The structure of the anion has little effect on the toxicity of the studied ionic liquids. Obtained results will provide insight into the toxicity mechanisms and useful information for assessing the potential ecological risk of ionic liquids.

Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests

Despite possessing an interesting chemical nature and tuneable physicochemical properties, ionic liquids (ILs) must have their ecotoxicity tested in order to be commercialized. The water solubility of ILs allows their easy access to the aquatic compartment of the ecosystem creating a potential hazard to aquatic organisms. Hence, it is relevant to design ionic liquids with lower toxicity while keeping the desired properties of interest. Considering the possibility of an enormous number of combinations of different cations and anions, a rational guidance for the structural design of ionic liquids is essential in order to prioritize the synthesis as well as testing of selected molecules only. Predictive in silico models, such as quantitative structure-activity relationship (QSAR) models, can play a pivotal role in exploring the important chemical attributes contributing to the response activity. These models may then lead to the design of novel ionic liquids. The present study aims at developing predictive QSAR models for the ecotoxicity of ionic liquids using the bacteria Vibrio fischeri as an indicator response species. Instead of a single model, here we have used multiple models to capture more complete structural information of ionic liquids for toxicity towards Vibrio fischeri. The derived chemical attributes have been implemented in designing new analogues, some of which have been synthesized and had their ecotoxicity tested for the same model organism. The predictive QSAR models reported here can be used for ecotoxicity prediction of new IL chemicals and for data-gap filling. Moreover, the synthesized low-toxic ILs could be considered for evaluation as well as for application in suitable processes serving the purpose of industry and academia.

A QSPR approach to the ecotoxicity of ionic liquids (Vibrio fischeri) using VolSurf principal properties

Recently derived in silico structural descriptors for both IL cations and anions allowed the development of a QSPR model correlating ionic liquid structures to Vibrio fischeri toxicity using the partial least squares (PLS) approach. Interpretation of the PLS model confirmed the effect of IL cationic structural features such as the influence of cation side chain length, presence of heteroatoms, and non-aromaticity of the heterocyclic scaffold on toxicity. The PLS model also provided a quantitative evaluation of anion effects, previously not evidenced due to the structural similarity of the anions considered. A simple equation in which three descriptors (two for the cations and one for the anions) allow the prediction of Vibrio fischeri toxicity for over 8000 ILs is reported.

Modelling the aquatic toxicity of ionic liquids by means of VolSurf in silico descriptors

VolSurf+ in silico physicochemical descriptors for both the cationic and the anionic counterparts of ionic liquids (ILs) have been derived. These descriptors, suitable for molecular modelling of IL structures which, due to their amphiphilic nature, interact strongly with biological matrices, can be related to aquatic toxicity by means of a partial least squares statistical model. This model gives an insight into the relationships between structural physicochemical properties and aquatic toxicity as well as a satisfactory quantitative structure-property correlation, allowing prediction of aquatic toxicity scores of ILs.

Stability studies of ionic liquid [EMIm][NTf2] under short-term thermal exposure

Mass spectrometer coupled TG analysis was used to identify decomposition products of thermally highly stressed ionic liquids.

Nonlinear QSAR modeling for predicting cytotoxicity of ionic liquids in leukemia rat cell line: an aid to green chemicals designing

Safety assessment and designing of safer ionic liquids (ILs) are among the priorities of the chemists and toxicologists today. Computational approaches have been considered as appropriate methods for prior safety assessment of chemicals and tools to aid in structural designing. The present study is an attempt to investigate the chemical attributes of a wide variety of ILs towards their cytotoxicity in leukemia rat cell line IPC-81 through the development of nonlinear quantitative structure-activity relationship (QSAR) models in the light of the OECD principles for QSAR development. Here, the cascade correlation network (CCN), probabilistic neural network (PNN), and generalized regression neural networks (GRNN) QSAR models were established for the discrimination of ILs in four categories of cytotoxicity and their end-point prediction using few simple descriptors. The diversity and nonlinearity of the considered dataset were evaluated through computing the Euclidean distance and Brock-Dechert-Scheinkman statistics. The constructed QSAR models were validated with external test data. The predictive power of these models was established through a variety of stringent parameters recommended in QSAR literature. The classification QSARs rendered the accuracy of >86%, and the regression models yielded correlation (R(2)) of >0.90 in test data. The developed QSAR models exhibited high statistical confidence and identified the structural elements of the ILs responsible for their cytotoxicity and, hence, could be useful tools in structural designing of safer and green ILs.

Predictive QSAR modelling of algal toxicity of ionic liquids and its interspecies correlation with Daphnia toxicity

Predictive toxicology using chemometric tools can be very useful in order to fill the data gaps for ionic liquids (ILs) with limited available experimental toxicity information, in view of their growing industrial uses. Though originally promoted as green chemicals, ILs have now been shown to possess considerable toxicity against different ecological endpoints. Against this background, quantitative structure-activity relationship (QSAR) models have been developed here for the toxicity of ILs against the green algae Scenedesmus vacuolatus using computed descriptors with definite physicochemical meaning. The final models emerged from E-state indices, extended topochemical atom (ETA) indices and quantum topological molecular similarity (QTMS) indices. The developed partial least squares models support the established mechanism of toxicity of ionic liquids in terms of a surfactant action of cations and chaotropic action of anions. The models have been developed within the guidelines of the Organization of Economic Co-operation and Development (OECD) for regulatory QSAR models, and they have been validated both internally and externally using multiple strategies and also tested for applicability domain. A preliminary attempt has also been made, for the first time, to develop interspecies quantitative toxicity-toxicity relationship (QTTR) models for the algal toxicity of ILs with Daphnia toxicity, which should be interesting while predicting toxicity of ILs for an endpoint when the data for the other are available.

Topological study on the toxicity of ionic liquids on Vibrio fischeri by the quantitative structure-activity relationship method

As environmentally friendly solvents, ionic liquids (ILs) are unlikely to act as air contaminants or inhalation toxins resulting from their negligible vapor pressure and excellent thermal stability. However, they can be potential water contaminants because of their considerable solubility in water; therefore, a proper toxicological assessment of ILs is essential. The environmental fate of ILs is studied by quantitative structure-activity relationship (QSAR) method. A multiple linear regression (MLR) model is obtained by topological method using toxicity data of 157 ILs on Vibrio fischeri, which are composed of 74 cations and 22 anions. The topological index developed in our research group is used for predicting the V. fischeri toxicity for the first time. The MLR model is precise for estimating LogEC50 of ILs on V. fischeri with square of correlation coefficient (R(2)) = 0.908 and the average absolute error (AAE) = 0.278.

Predicting the ecotoxicity of ionic liquids towards Vibrio fischeri using genetic function approximation and least squares support vector machine

Ionic liquids (ILs) are widely used in industrial production for their unique physicochemical properties, and they are even regarded as green solvents. However, the recent study showed ILs might pose a potential risk to aquatic ecosystems. In the present work, the quantitative structure-activity relationship (QSAR) models, including genetic function approximation (GFA) and least squares support vector machine (LSSVM) were developed for predicting the ecotoxicity of ILs towards the marine bacterium Vibrio fischeri based on the descriptors calculated from cations and anions. Five descriptors were selected by GFA and used to develop the linear model. From the discussion of descriptors, the cation structure was the main factor to the toxicity, which mainly depended on the size, lipophilic, and 3D molecular structure of cations. In order to capture the nonlinear nature, the LSSVM model was also built for more accurately predicting the ecotoxicity. The GFA and LSSVM models were performed the rigorous internal and external validation, further verifying these models with excellent robustness and predictive ability. Therefore, both of models can be used for the prediction of the ecotoxicity of newly synthesized and untested ILs, and can provide reference information and theoretical guidance for designing and synthesizing safer and more eco-friendly ILs.

Quantitative structure-activity relationship for toxicity of ionic liquids to Daphnia magna: aromaticity vs. lipophilicity

Water solubility of ionic liquids (ILs) allows their dispersion into aquatic systems and raises concerns on their pollutant potential. Again, lipophilicity can contribute to the toxicity of ILs due to increased ability of the compounds to cross lipoidal bio-membranes. In the present work, we have performed statistical model development for toxicity of a set of ionic liquids to Daphnia magna, a widely accepted model organism for toxicity testing, using computed lipophilicity, atom-type fragment, quantum topological molecular similarity (QTMS) and extended topochemical atom (ETA) descriptors. The models have been developed and validated in accordance with the Organization for Economic Co-operation and Development (OECD) guidelines for quantitative structure-activity relationships (QSARs). The best partial least squares (PLS) model outperforms the previously reported multiple linear regression (MLR) model in statistical quality and predictive ability (R(2)=0.955, Q(2)=0.917, Rpred(2)=0.848). In this work, the ETA descriptors show importance of branching and aromaticity while the QTMS descriptor ellipticity efficiently shows which compounds are influential in the data set, with reference to the model. While obvious importance of lipophilicity is evident from the models, the best model clearly shows the importance of aromaticity suggesting that more lipophilic ILs with less toxicity may be designed by avoiding aromaticity, nitrogen atoms and increasing branching in the cationic structure. The developed quantitative models are in consonance with the recent hypothesis of importance of aromaticity for toxicity of ILs.

Applications and mechanisms of ionic liquids in whole-cell biotransformation

Ionic liquids (ILs), entirely composed of cations and anions, are liquid solvents at room temperature. They are interesting due to their low vapor pressure, high polarity and thermostability, and also for the possibility to fine-tune their physicochemical properties through modification of the chemical structures of their cations or anions. In recent years, ILs have been widely used in biotechnological fields involving whole-cell biotransformations of biodiesel or biomass, and organic compound synthesis with cells. Research studies in these fields have increased from the past decades and compared to the typical solvents, ILs are the most promising alternative solvents for cell biotransformations. However, there are increasing limitations and new challenges in whole-cell biotransformations with ILs. There is little understanding of the mechanisms of ILs' interactions with cells, and much remains to be clarified. Further investigations are required to overcome the drawbacks of their applications and to broaden their application spectrum. This work mainly reviews the applications of ILs in whole-cell biotransformations, and the possible mechanisms of ILs in microbial cell biotransformation are proposed and discussed.

Predictive modeling studies for the ecotoxicity of ionic liquids towards the green algae Scenedesmus vacuolatus

Hazardous potential of ionic liquids is becoming an issue of high concern with increasing application of these compounds in various industrial processes. Predictive toxicological modeling on ionic liquids provides a rational assessment strategy and aids in developing suitable guidance for designing novel analogues. The present study attempts to explore the chemical features of ionic liquids responsible for their ecotoxicity towards the green algae Scenedesmus vacuolatus by developing mathematical models using extended topochemical atom (ETA) indices along with other categories of chemical descriptors. The entire study has been conducted with reference to the OECD guidelines for QSAR model development using predictive classification and regression modeling strategies. The best models from both the analyses showed that ecotoxicity of ionic liquids can be decreased by reducing chain length of cationic substituents and increasing hydrogen bond donor feature in cations, and replacing bulky unsaturated anions with simple saturated moiety having less lipophilic heteroatoms.

Novel organic–inorganic hybrid soft xerogels with lanthanide complexes through an ionic liquid linkage

Functional hybrid soft materials [Ln(L)₄]⁻IM⁺–Al/Ti are prepared by sol–gel derived hosts based on Ti–O or Al–O groups, with an exchange reaction of the ionic liquid 3-(5-carboxy-propyl)-1-methyl-imidazolium bromide and lanthanide complexes.