| Publication Type |
Journal Article |
| Title |
The Solubility of Gases in Ionic Liquids: A Chemoinformatic Predictive and Interpretable Approach |
| Authors |
Goncalo V. S. M. Carrera Joao Ines Carlos E. S. Bernardes Kyrylo Klimenko Karina Shimizu Jose N. Canongia Lopes |
| Groups |
MET |
| Journal |
CHEMPHYSCHEM |
| Year |
2021 |
| Month |
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|
| Volume |
22 |
| Number |
21 |
| Pages |
2190-2200 |
| Abstract |
This work comprises the study of solubilities of gases in ionic liquids (ILs) using a chemoinformatic approach. It is based on the codification, of the atomic inter-component interactions, cation/gas and anion/gas, which are used to obtain a pattern of activation in a Kohonen Neural Network (MOLMAP descriptors). A robust predictive model has been obtained with the Random Forest algorithm and used the maximum proximity as a confidence measure of a given chemical system compared to the training set. The encoding method has been validated with molecular dynamics. This encoding approach is a valuable estimator of attractive/repulsive interactions of a generical chemical system IL+gas. This method has been used as a fast/visual form of identification of the reasons behind the differences observed between the solubility of CO2 and O-2 in 1-butyl-3-methylimidazolium hexafluorophosphate (BMIM PF6) at identical temperature and pressure (TP) conditions, The effect of variable cation and anion effect has been evaluated. |
| DOI |
http://dx.doi.org/10.1002/cphc.202100632 |
| ISBN |
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| Publisher |
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| Book Title |
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| ISSN |
1439-4235 |
| EISSN |
1439-7641 |
| Conference Name |
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| Bibtex ID |
WOS:000697216100001 |
| Observations |
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