The study on thermal transport properties of polymers is very important because of the crucial role played by these properties in both processing stages and product uses. It provides an insight into the structure of the polymers and it helps to predict product performance during specific applications. The thermal conductivity of polymers is an important physical property, which describes the ability of those materials to conduct heat. For example, in certain polymer processing applications the polymer may experience very rapid and large temperature or pressure changes, and the degree and type of crystallinity, which strongly affects the engineering properties of the resulting film or fiber, depend upon the details of the thermal history. Therefore, it is desirable to determine the temperature and pressure dependence of the thermal conductivity.A total of three thermal conductivity models were developed in this work. The first one is a group contribution model for the prediction of the thermal conductivity of polymer melts. Based only on the information of the chemical structure of the polymers considered, the model requires only the existing group contribution methods for the estimation of specific heats, densities, and melting temperatures in the calculation of thermal conductivity for polymer melts. For 11 polymer melt systems tested, predictive accuracy of the model is normally better than 10%. As only group parameters are needed in the calculation, this model is predictive, and is very convenient for practical use.The second model proposed in this work is a group contribution model for the correlation and prediction of the thermal conductivity of glassy and liquid amorphouspolymers. The model requires only the existing group contribution methods for the estimation of glass temperature, molar Rao function, heat capacity at constant pressure, molar volume and Poisson's ratio at 298 K in the calculation of thermal conductivity for amorphous polymers. For 28 polymer systems with 700 data points tested, predictive accuracy of the model is normally better than 15%. Similarly to the previous model, as only group parameters are needed in the calculation, this model is also predictive, and is very convenient for engineering use.Although studies on the temperature dependence of the thermal conductivity of polymers have been carried out by many researchers theoretically and experimentally, the relevant studies on the pressure dependence of the thermal conductivity of polymers are still rare. A new model was proposed for the prediction of the pressure dependence of the thermal conductivity of polymer melts. The model requires only a known or predicted atmospheric pressure thermal conductivity datum and the Tait equation parameters in the calculation of the thermal conductivity for polymer melts at high pressures. For 8 polymer melt systems tested, predictive accuracy of the model is normally better than 10% for a wide pressure range. As the model can be used for polymer systems where no any thermal conductivity data exist, it is a predictive model with satisfactory accuracy, which makes the model have a broad engineering applying prospect.In summary, the three models proposed in this work provide very simple and convenient methods to predict the thermal conductivity of polymers with good accuracy, which makes them be of great practical use. |