SVRC Model Predicting Thermal Conductivity of Gas of Pure Organic Compound

摘要

The present invention is hydrogen (H), carbon (C), nitrogen (N), oxygen (O) , sulfur (S) consists of elements, such as less than 5 kinds and provides mathematical models for predicting the number of atoms other than hydrogen, the gas thermal conductivity at a high accuracy (Thermal Conductivity of Gas) of the pure organic compound consisting of not more than 25 molecules . As the model is SVRC (scaled variable reduced coordinate) model, allows to know the value of the thermal conductivity of the gas at different temperatures through the SVRC formula. The same formula calculation requires the value of the various parameters, the values are based on the experimental value for the gas thermal conductivity of a number of compounds that satisfy the conditions mentioned in the present invention in order to obtain these values uniquely given to each compound, the were using multiple linear regression analysis and artificial neural network to establish the QSPR (quantitative structure-property relationship) prediction model for each parameter. Therefore, the above model is, if you know the specific values of the molecules presenters included in the model any molecular way, allows to predict the gas thermal conductivity of pure compounds consisting of these molecules. As such, the present invention can maintain the cost and time savings by giving the experiment to provide a way to predict the values of the gas thermal conductivity and reliable for the number of the compounds of the experimental conditions is unknown, facilitate the research and development of related industries lays effects such as that. ;