New QSPR Models to Predict the Flammability of Binary Liquid Mixtures

New Quantitative Structure‐Property Relationships (QSPR) are presented to predict the flash point of binary liquid mixtures, based on more than 600 experimental flash points for 60 binary mixtures. Two models are proposed based on a GA‐MLR approach that uses a genetic algorithm (GA) variable selecti...

Full description

Saved in:
Bibliographic Details
Published in:Molecular informatics 2019-08, Vol.38 (8-9), p.e1800122-n/a
Main Authors: Fayet, Guillaume, Rotureau, Patricia
Format: Article
Language:English
Subjects:
Binary mixtures
Environmental Engineering
Environmental Sciences
Flammability
Flash point
genetic algorithm
Genetic algorithms
mixtures
Predictions
Quantitative Structure-Property Relationships
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:New Quantitative Structure‐Property Relationships (QSPR) are presented to predict the flash point of binary liquid mixtures, based on more than 600 experimental flash points for 60 binary mixtures. Two models are proposed based on a GA‐MLR approach that uses a genetic algorithm (GA) variable selection in multilinear regressions (MLR). In these models, mixtures were characterized by a series of mixture descriptors calculated from various mixture formula combining the molecular descriptors of the single compounds constituting the mixtures and their respective molar fractions in the mixture. The best model demonstrated good predictive capabilities with a mean absolute error of only 7.3 °C estimated for an external validation set. Moreover, this model is focused on mixture descriptors applicable to more complex mixtures, i. e. constituted of more than 2 components, and already demonstrated interesting predictions for a series of ternary mixtures.
ISSN:1868-1743
1868-1751
DOI:10.1002/minf.201800122