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Beware of proper validation of models for ionic Liquids!
J. Mol. Liq. 344:117722 (2021)
The melting point (MP) of an ionic liquid (IL) is one of the key physical properties as it determines the lower limit of the IL working temperature range. In this work, we analysed the recently published studies to predict MP of ILs. While we were able to reproduce the statistical parameters reported by the authors, we found that the performance of the models with new test set data was much lower than the reported statistical values. The discrepancy was due to the validation protocol (random split of the initial set into training/test subsets) that did not allow correct estimation of how contributions of individual ions affect the model performance. Using a more rigorous validation protocol we reached good agreement between the training and test set statistical parameters. We strongly suggest using this protocol for proper validation of models for other properties of ILs to avoid reporting overoptimistic statistical parameters. We also showed that the Transformer Convolutional Neural Network, which was based on the representation of molecules as text (SMILES), proposed a model with significantly higher prediction accuracy as compared to those developed using descriptors that were used in the previous studies. The RMSE of this model is 44 °C and the model is applicable to any type of ILs. The data and developed models are publicly available online at http://ochem.eu/article/135195.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Ionic Liquids ; Melting Point ; Nlp ; Ochem ; Qspr ; Transformer-cnn; Triethanolamine-based Salts; Melting-points; Imidazolium Bromides; Thermal-properties; Temperature; Solvents; Predict; Mixtures; Acids; Qspr
ISSN (print) / ISBN
0167-7322
e-ISSN
1873-3166
Zeitschrift
Journal of Molecular Liquids
Quellenangaben
Band: 344,
Artikelnummer: 117722
Verlag
Elsevier
Verlagsort
Radarweg 29, 1043 Nx Amsterdam, Netherlands
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Structural Biology (STB)
Förderungen
Ministry of Science and Higher Education of The Russian Federation