The system of self-consistent QSPR-models for refractive index of polymers

Andrey A Toropov,Valentin O Kudyshkin,Alla P Toropova

doi:10.1007/s11224-021-01875-y

Abstract

Quantitative structure–property/activity relationships (QSPRs/QSARs) are a component of modern natural science. The system of self-consistent models is a specific approach to build up QSPR/QSAR. A group of models of refractive index for different distributions in training and test sets is compared. This comparison is a basis to formulate the system of self-consistent models. The so-called index of ideality of correlation (IIC) has been used to improve the predictive potential of models of the refractive index of different polymers (n = 255). The predictive potential of the suggested models is high since the average value of the determination coefficient for the validation set is 0.885. In addition, the system of self-consistent models may be applied as a tool to assess the predictive potential of an arbitrary QSPR-approach. The statistical characteristics of the best model are the following: n = 57, R2 = 0.7764, RMSE = 0.039 (active training set) and n = 57, R2 = 0.9028, RMSE = 0.019 (validation set).

Highlights

Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool to assess various endpoints via analysis of available databases on experimental values of the endpoint of interest [1,2,3,4,5,6,7]
The present study aims to build up and validate of QSPR model for the refractive index of polymers
Applying the ideality of correlation (IIC) improves the statistical characteristics of a model for the validation set but to the detriment of the active/passive training sets

Summary

Introduction

Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool to assess various endpoints via analysis of available databases on experimental values of the endpoint of interest [1,2,3,4,5,6,7]. High refractive index polymers have captured considerable attention of the scientific community due to various applications, aimed to improve advanced opticelectronic devices [9]. The present study aims to build up and validate of QSPR model for the refractive index of polymers. The assessment of the predictive potential of these models carried out via so-called the system of self-consistent models of the refractive index of polymers. The index of ideality of correlation (IIC) can be serve as a criterion of the predictive potential. The IIC demonstrates significant ability to improve the predictive potential of QSPR model being applied as add component of the Monte Carlo optimization aimed to model an arbitrary endpoint

Methods

Results

Conclusion