Ionic liquids (ILs) have shown remarkable
potential for applications
in separation, such as extractive distillation and liquid–liquid
extraction. Crucial to these applications is the estimation of a significant
property of the ILs which is the infinite dilution activity coefficient
(IDAC) of different solutes in ILs. In this context, the present paper
aims to model IDAC of 17 solutes in 44 imidazolium ILs using 2666
experimental data points gathered from the literature and based on
support vector machine for the regression (SVMr) learning algorithm.
Two models are developed, one based on SVMr and the other one based
on dragonfly algorithm (DA) associated with SVMr. Both models consider
the same set of predictive variables which are the temperature, the
molecular weight of solute and solvent, and five conductor-like screening
models for real solvents (COSMO-RS) σ-profile descriptors related
to the solute and IL. The DA is applied for optimization of SVMr hyper-parameters.
The results show the superiority of the DA-SVMr model demonstrated
by its correlation coefficient (R) and root mean
square error values of 0.996 and 0.170, respectively.
A comprehensive data set on experimental solubility of 210 solid solutes in supercritical CO 2 counting 5550 data points has been used for comparison of the correlation performance of 21 empirical models. On the basis of the comparison results a new eightparameter density-based model has been proposed. The comparison shows that the three-parameter models are the least accurate. The results also show that models that relate the logarithm of the solubility to the logarithm of solvent density and temperature are more accurate than models that include the pressure. When comparing the overall correlating performance in terms of average absolute relative deviation the proposed model is by far the best with an average absolute relative deviation lying in the range 0.17 e81.99% and an average value of 8.88%.
The study aims at modelling the drying kinetics of a pharmaceutical powder with active ingredient Candesartan Cilexetil. The kinetics was carried out in a vacuum dryer at different temperature levels, pressure, initial mass, and water content. The effect of some operating parameters on the drying time was studied. The modelling of drying times was based on the use of experimental design method. The data obtained were adjusted using 17 semi-empirical models, one proposed, a static ANN and DA_SVMR, regrouping all studied kinetics. The
proposed model and DA_SVMR model were chosen as the most appropriate to
describe the drying kinetics.
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