The Monte Carlo approach to model and predict the melting point of imidazolium ionic liquids using hybrid optimal descriptors (original) (raw)
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Journal of Chemical Information and Modeling, 2005
The melting points of several imidazolium-based ionic liquids or ionic liquid analogues were correlated using the CODESSA program in order to develop predictive tools for determination of suitable ionic liquid salts. The data set consisted of melting point data (°C) for 104 substituted imidazolium bromides divided on the basis of the N-substituents into three subsets: A-57 compounds, B-29 compounds, and C-18 compounds. The 45 benzimidazolium bromides form set D. Five-parameter correlations were obtained for (i) set A with R 2 ) 0.7442, (ii) set B with R 2 ) 0.7517, and (iii) set D with R 2 ) 0.6899, while set C was correlated with a three parameter equation with R 2 ) 0.9432. These descriptors for predicting the melting points of the imidazolium and benzimidazolium bromides were based on the size and electrostatic interactions in the cations.
Melting-Point Estimation of Ionic Liquids by a Group Contribution Method
International Journal of Thermophysics, 2012
Based on experimental data collected from the literature, a group contribution method for estimating the melting points of imidazolium-, pyridinium-, pyrrolidinium-, ammonium-, phosphonium-, and piperidinium-based ionic liquids (ILs) with common anions is proposed. The method considers the contributions of ionic groups and methylene groups, as additive parameters, and two nonadditive characteristic geometric parameters of cations such as symmetry and flexibility. A total of 293 data points for 136 ILs were used in this study. The average relative deviation and the average absolute deviation of the proposed model are 7.8 % and 22.6 K, respectively. It is concluded that the proposal is useful for the prediction of the melting points for a wide range of ILs.
Journal of Chemical Information and Modeling, 2007
Several popular machine learning methodssAssociative Neural Networks (ANN), Support Vector Machines (SVM), k Nearest Neighbors (kNN), modified version of the partial least-squares analysis (PLSM), backpropagation neural network (BPNN), and Multiple Linear Regression Analysis (MLR)simplemented in ISIDA, NASAWIN, and VCCLAB software have been used to perform QSPR modeling of melting point of structurally diverse data set of 717 bromides of nitrogen-containing organic cations (FULL) including 126 pyridinium bromides (PYR), 384 imidazolium and benzoimidazolium bromides (IMZ), and 207 quaternary ammonium bromides (QUAT). Several types of descriptors were tested: E-state indices, counts of atoms determined for E-state atom types, molecular descriptors generated by the DRAGON program, and different types of substructural molecular fragments. Predictive ability of the models was analyzed using a 5-fold external cross-validation procedure in which every compound in the parent set was included in one of five test sets. Among the 16 types of developed structuremelting point models, nonlinear SVM, ASNN, and BPNN techniques demonstrate slightly better performance over other methods. For the full set, the accuracy of predictions does not significantly change as a function of the type of descriptors. For other sets, the performance of descriptors varies as a function of method and data set used. The root-mean squared error (RMSE) of prediction calculated on independent test sets is in the range of 37.5-46.4°C (FULL), 26.2-34.8°C (PYR), 38.8-45.9°C (IMZ), and 34.2-49.3°C (QUAT). The moderate accuracy of predictions can be related to the quality of the experimental data used for obtaining the models as well as to difficulties to take into account the structural features of ionic liquids in the solid state (polymorphic effects, eutectics, glass formation).
Predicting Melting point and Viscosity of Ionic Liquids Using New Quantum Chemistry Descriptors
Ionic liquids (ILs) are an emerging group of chemical compounds which possess promising properties such as having negligible vapor pressure. These so called designer solvents have the potential to replace volatile organic compounds in industrial applications. A large number of ILs, through the combination of different cations and anions, can potentially be synthesized. In this context, it will be useful to intelligently design customized ILs through computer-aided methods. Practical limitations dictate that any successful attempt to design new ILs for industrial applications requires the ability to accurately predict their melting point and viscosity as experimental data will not be available for designed structures. In this paper, we present two new correlation equations towards the more precise prediction of melting point and viscosity of ILs solely based on the inputs from quantum chemistry calculations (no experimental data or simulation results are needed). To develop these correlations we utilized data related to size, shape, and electrostatic properties of cations and anions that constitutes ILs. In this work, new descriptors such as dielectric energy of cations and anions as well as the values predicted by an 'ad-hoc' model for the radii of cations and anions (instead of their van der waals radii) were used. An enormous form of correlation equations constituent of all different combinations of descriptors (as the inputs to the model) were tested. The average relative errors were measured to be 3.16% and 6.45% for the melting point, Tm, and ln(vis), respectively.
Thermal properties of imidazolium ionic liquids
Thermochimica Acta, 2000
We investigated the thermal properties of several imidazolium salts using DSC and TGA/SDTA data. Many of these salts are liquids at sub-ambient temperatures. These ionic liquids form glasses at low temperatures and have minimal vapor pressure up to their thermal decomposition temperature (>4008C). Thermal decomposition is endothermic with the inorganic anions and exothermic with the organic anions investigated. Halide anions drastically reduce the thermal stability of these salts (<3008C). We have observed that aluminium catalyzes the decomposition of the salts containing the inorganic¯uoride anions. The imidazolium cations are thermally more stable than the tetraalkyl ammonium cations.
Low-melting organic salts, commonly known as ionic liquids (ILs), have been of considerable interest to both scientific and industrial communities. Reliable knowledge of their various thermophysical properties, such as liquid density, is of great importance for industrial design and operation. In this work, use has been made of three equations of state based on the statistical molecular-thermodynamic theory of lattice-hole; i.e. ε*-Modified Sanchez-Lacombe, Simha- Somcynsky and Park-Kim EOSs. Considering the experimental liquid density data of three imidazolium based ILs, namely 1-butyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide ([C4mim][NTf2]), 1-hexyl-3-methylimidazolium tetrafluoroborate ([C6mim][BF4]) and 1-butyl-3- methylimidazolium dicyanamide ([C4mim][dca]), the pure component characteristic parameters of the EOSs were optimized. Subsequently, their relative performance was investigated over broad pressure and temperature ranges and a comparison was made between the results obtained and the commonly used Peng-Robinson cubic equation of state.
Molecules
While several group contribution method (GCM) models have been developed in recent years for the prediction of ionic liquid (IL) properties, some challenges exist in their effective application. Firstly, the models have been developed and tested based on different datasets; therefore, direct comparison based on reported statistical measures is not reliable. Secondly, many of the existing models are limited in the range of ILs for which they can be used due to the lack of functional group parameters. In this paper, we examine two of the most diverse GCMs for the estimation of IL melting point; a key property in the selection and design of ILs for materials and energy applications. A comprehensive database consisting of over 1300 data points for 933 unique ILs, has been compiled and used to critically evaluate the two GCMs. One of the GCMs has been refined by introducing new functional groups and reparametrized to give improved performance for melting point estimation over a wider ran...