Chromatographia

, Volume 81, Issue 4, pp 595–610 | Cite as

Prediction of Dispersive Liquid–Liquid Microextraction Enrichment Effect of Aromatic Organics by [OMIM] [PF6] Ionic Liquid Based on Atom-Type Electrotopological State Indices

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Abstract

In this work, a quantitative structure–property relationship (QSPR) model based on atom-type electrotopological state (E-state) indices has been developed for predicting the dispersive liquid–liquid microextraction (DLLME) enrichment effect for aromatic organics by using 1-octyl-3-methylimidazolium hexafluorophosphate ([OMIM][PF6]) ionic liquid as extractant. The enrichment factors of the aromatic organics obtained through DLLME-IL process were used as the dependent variable of the multiple linear regression (MLR) equation. The E-state indices of those organic compounds which combined together both electronic and topological characteristics of the analyzed molecules were used as molecular structure descriptors and the independent variable of the equation. The squared correlation coefficient R2 for the MLR was 0.992 for the training set of 33 compounds. For the test set of 8 compounds, the linear regression coefficient was R2 = 0.985. The results of this study showed that it can successfully predict enrichment factors of [OMIM][PF6] in DLLME by using atom-type E-state indices, which can provide one more way for predicting the ability of ionic liquid to extract organic compounds based on their molecular structures.

Keywords

Atom-type electrotopological state indices Dispersive liquid–liquid microextraction Ionic liquid Quantitative structure–property relationship 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 21277108, 71501149).

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Human/animal studies

This article does not contain any studies with human participants or animals performed by the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Resources and Environmental EngineeringWuhan University of TechnologyWuhanChina
  2. 2.School of ManagementWuhan University of TechnologyWuhanChina

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