Improved models for predicting viscosities at 20 C were generated using three different
methods for descriptor selection. Data set of 361 diverse organic molecules and their …

A QSPR (quantitative structure− property relationship) model for the estimation of the liquid
viscosity of a large variety of organic compounds was established using the CODESSA …

A predictive method, based on quantitative structure-activity relationship (QSAR) techniques,
has been developed for liquid viscosities of organic compounds. On the basis of the set of …

In this study, a new quantitative structure–property relationship (QSPR) is presented for
prediction of the liquid viscosity of pure organic compounds. The model implements eight …

Experimental values for the liquid viscosity (η) at 20° C ranging from 0.164 mPa⊙ s (trans-2-
pentene) to 1490 mPa⊙ s (glycerol) have been collected from literature for 361 organic …

The liquid viscosity of 361 organic compounds containing C, H, N, O, S and/or halogens was
investigated using a quantitative structure–property relationship (QSPR) approach. A five …

A quantitative structure− property relationship (QSPR) approach was used to develop a
predictive model for viscosities of pure organic liquids using a set of 403 compounds that …

The application of a commonly used computer algorithm based on the group-additivity
method for the calculation of the liquid viscosity coefficient at 293.15 K and the activity …

ABSTRACT A four-descriptor quantitative structure–property relationship model was
constructed to predict 65 intrinsic viscosities [η] of polymer solutions. Four quantum chemical …

Back-propagation neural network models for correlating and predicting the viscosity−
temperature behavior of a large variety of organic liquids were developed. Experimental …