New molecular structure based models for estimation of the CO 2 solubility in different choline chloride-based deep eutectic solvents (DESs)

In this study, CO solubility in different choline chloride-based deep eutectic solvents (DESs) has been investigated using the Quantitative Structure-Property Relationship (QSPR). In this regard, the effect of different structures of the hydrogen bond donor (HBD) in choline chloride (ChCl) based dee...

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Veröffentlicht in:Scientific reports 2023-05, Vol.13 (1), p.8495
Hauptverfasser: Dehkordi, Farnoosh, Sobati, Mohammad Amin, Gorji, Ali Ebrahimpoor
Format: Artikel
Sprache:eng
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Zusammenfassung:In this study, CO solubility in different choline chloride-based deep eutectic solvents (DESs) has been investigated using the Quantitative Structure-Property Relationship (QSPR). In this regard, the effect of different structures of the hydrogen bond donor (HBD) in choline chloride (ChCl) based deep eutectic solvents (DESs) has been studied in different temperatures and different molar ratios of ChCl as hydrogen bond acceptor (HBA) to HBD. 12 different datasets with 390 data on the CO solubility were chosen from the literature for the model development. Eight predictive models, which contain the pressure and one structural descriptor, have been developed at the fixed temperature (i.e. 293, 303, 313, or 323 K), and the constant molar ratio of ChCl to HBD equal to 1:3 or 1:4. Moreover, two models were also introduced, which considered the effects of pressure, temperature, and HBD structures, simultaneously in the molar ratios equal to 1:3 or 1:4. Two additional datasets were used only for the further external validation of these two models at new temperatures, pressures, and HBD structures. It was identified that CO solubility depends on the "EEig02d" descriptor of HBD. "EEig02d" is a molecular descriptor derived from the edge adjacency matrix of a molecule that is weighted by dipole moments. This descriptor is also related to the molar volume of the structure. The statistical evaluation of the proposed models for the unfixed and fixed temperature datasets confirmed the validity of the developed models.
ISSN:2045-2322
DOI:10.1038/s41598-023-35747-8