## 2 Basic Analysis of Prediction Models and Model Verification
### Prediction Models of Viscosity and Thermal Conductivity
#### 3.4.1 Prediction Models of Viscosity and Thermal Conductivity
The ARD between the reference values and the predictive values was about 9% [117]:  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]7  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]8  
\[F^{*} =1-0.2756\omega+0.059035\mu_{\rm dim}^{4}+\kappa \tag{70}\]9  
4.2 Comparison and Discussion of Different Models of Viscosity and Thermal Conductivity Discussion of The PCS Model  
For the PCS model, the relative deviations between the predicted values and the reference values [64,70,74] of the viscosities of FC-72, Novec 649 and HFE-7100 and the relative deviations between the predicted values and the reference values [68,72] of the thermal conductivities of Novec 649 and HFE-7100 are shown in Figures 11 and 12, respectively. The data on the thermal conductivity of FC-72 were too few to be referred [65]. The combined expanded uncertainties in viscosity measurements (level of confidence = 0.95, coverage factor = 2) of FC-72, Novec 649 and HFE-7100 were 0.8% [64], 3.0% [70] and 2.0% [74], respectively. The combined expanded uncertainties in thermal conductivity measurements (level of confidence = 0.95, coverage factor = 2) of Novec 649 and HFE-7100 were 3.0% [78] and 2.0% [72], and 2.0% [72], respectively. The ideal gas specific heat required to calculate the thermal conductivity contributed by the internal motion of molecules was estimated by Aspen Plus v10. The residual viscosity and residual thermal conductivity of the reference fluid R134a were calculated by the formulas in literature [118,119]. From Figures 11 and 12, it can be found that when the viscosities and thermal conductivities of the electronic fluoride liquids were predicted, the relative deviations between the predicted values and the reference values were high under most conditions. Given these results, the empirical correction factor \(\psi\) for viscosity and \(\chi\) for thermal conductivity are introduced to further modify the conformal density [107], as shown in Equations (88) and (89), which will greatly improve the predictive accuracies of viscosity and thermal conductivity. However, these two new parameters were fitted by a great number of experimental data which may have made the work more difficult and contrary to the main goal of obtaining the properties by the prediction models directly. Therefore, for viscosity and thermal  
\[\mu_{\rm dim} =131.3\mu\;/\;(V_{c}\,T_{c})^{0.5} \tag{71}\]0 Relative deviations between the predicted and reference values [64,70,74] of the viscosities of FC-72, Novec 649 and HFE-7100 using the PCS model. conductivity, the PCS model is not an ideal prediction model, but its predictive values still have some reference significance. Comparison and Discussion of Different Models of Viscosity  
The prediction results obtained by four prediction models of viscosity (PCS, SVIS1, SVIS2 and NVIS) for the three electronic fluoride liquids were compared, as shown in Figures 13-15. For different electronic fluoride fluids, the best prediction models are also different. The best prediction models of viscosity for FC-72, Novvec 649 and HFE-7100 are the SVIS2 model, the NVIS model and the SVIS1 model, respectively. The PCS model is not the best prediction model for any of these liquids. The predicted viscosities for FC-72 and HFE-7100 were more accurate than those for Novvec 649 by using the SVIS1 and SVIS2 models. For FC-72 and HFE-7100, the relative deviations between the reference and predicted viscosities by the SVIS1 model were within 10%; when the SVIS2 model was used, the relative deviations between the reference and predicted viscosities were within 22%. However, for Novvec 649, when using the two models, the relative deviations between the reference and predicted viscosities were greater than 24%.