Abstract
In this communication, a group contribution method (GC) for the representation/prediction of liquid thermal conductivity of pure chemical compounds, most of which are organic in nature, is presented. Nearly 19,000 liquid thermal conductivity data at different temperatures compiled for 1635 chemical compounds were extracted from the DIPPR 801 database and used to develop the proposed model, as well as to validate and optimize its parameters and evaluate its predictive capability. The parameters of the model comprise the occurrences/existence of 49 chemical substructures plus temperature. Nearly 80% of the data set (15,450 data points) is used to develop the model parameters, 10% of the data set (1931 data points) was employed to validate and optimize the model parameters, and the remaining data (1931 data points) were implemented to assess its predictive capability. The average absolute relative deviation of the model results with respect to the DIPPR 801 data is less than 7.1%. In terms of its simplicity and wide range of applicability, the model shows reasonable accuracy.
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