Prediction of clearing temperatures of bent-core liquid crystals using decision trees and multivariate adaptive regression splines

Accurate prediction of transition temperature is very helpful for the design of new liquid crystals (LCs) because even small changes in structure can dramatically alter the transition temperature, and therefore the synthesis of LCs should not be governed only by chemical intuition. A quantitative st...

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Bibliographic Details
Published in:Liquid crystals 2016-06, Vol.43 (8), p.1028-1037
Main Authors: Antanasijević, Jelena, Pocajt, Viktor, Antanasijević, Davor, Trišović, Nemanja, Fodor-Csorba, Katalin
Format: Article
Language:English
Subjects:
Clearing
Crystals
decision tree
Decision trees
Liquid crystals
MARS modelling
Mathematical models
QSPR
Regression
Splines
Temperature
Transition temperature
Two dimensional
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Summary:Accurate prediction of transition temperature is very helpful for the design of new liquid crystals (LCs) because even small changes in structure can dramatically alter the transition temperature, and therefore the synthesis of LCs should not be governed only by chemical intuition. A quantitative structure-property relationship (QSPR) study was performed on 243 five-ring bent-core LCs in order to predict their clearing temperatures using molecular descriptors. Decision tree and multivariate adaptive regression splines (MARS), techniques well suited for high-dimensional data analysis, were applied to select important descriptors (dimension reduction) and to generate nonlinear models. These techniques were applied both on two-dimensional (2D) descriptors only and on the pool of 2D and 3D descriptors (2&3D). The obtained QSPR models were tested using 15% of available data, and their performance and ability to generalise were analysed using multiple statistical metrics. The best results for the external test set were obtained using the MARS model created with 2&3D descriptors, with a high correlation coefficient of r = 0.95 and a root mean squared error of 7.41 K. All metrics suggest that the proposed QSPR model, generated by MARS, is a robust and satisfactorily accurate approach for the prediction of clearing temperatures of bent-core LCs.
ISSN:0267-8292
1366-5855
DOI:10.1080/02678292.2016.1155769