Statistical models are able to predict ionic liquid viscosity across a wide range of chemical functionalities and experimental conditions

Herein we present a method of developing predictive models of viscosity for ionic liquids (ILs) using publicly available data in the ILThermo database and the open-source software toolkits PyChem, RDKit, and SciKit-Learn. The process consists of downloading ∼700 datapoints from ILThermo, generating...

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Veröffentlicht in:	Molecular systems design & engineering 2018-02, Vol.3 (1), p.253-263
Hauptverfasser:	Beckner, Wesley, Mao, Coco M, Pfaendtner, Jim
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Downloading Ionic liquids Linearity Neural networks Physiochemistry Shrinkage Source code Statistical models Toolkits Viscosity
Online-Zugang:	Volltext
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