In this study, molecular dynamics simulations were carried out to study the coupling effect of electric field strength and surface wettability on the condensation process of water vapor. Our results show that an electric field can rotate water molecules upward and restrict condensation. Formed clusters are stretched to become columns above the threshold strength of the field, causing the condensation rate to drop quickly. The enhancement of surface attraction force boosts the rearrangement of water molecules adjacent to the surface and exaggerates the threshold value for shape transformation. In addition, the contact area between clusters and the surface increases with increasing amounts of surface attraction force, which raises the condensation efficiency. Thus, the condensation rate of water vapor on a surface under an electric field is determined by competition between intermolecular forces from the electric field and the surface.

In this work, molecular structures, combined with machine learning algorithms, were applied to predict the critical temperatures (Tc) of a group of organic refrigerants. Aiming at solving the problem that previous models cannot distinguish isomers, a topological index was introduced. The results indicate that the novel molecular descriptor ‘molecular fingerprint + topological index’ can effectively differentiate isomers. The average absolute average deviation between the predicted and experimental values is 3.99%, which proves a reasonable prediction ability of the present method. In addition, the performance of the proposed model was compared with that of other previously reported methods. The results show that the present model is superior to other approaches with respect to accuracy.

Exploring renewable energy is beneficial for ameliorating the energy crisis and reducing environmental emissions. The hybrid utilization of solar and geothermal energies is an effective way to improve the existing energy consumption structure dominated by fossil energy. This paper proposes a novel power generation system composed of a topping recompression supercritical carbon dioxide (sCO2) Brayton cycle and a bottom organic flash cycle (OFC) driven by the hybrid solar-geothermal energies. The sCO2 Brayton cycle is driven by the heat from the solar tower system, and the OFC is driven by a part of the heat from CO2 in the sCO2 Brayton cycle and another part of the heat from the geothermal water. The corresponding energy and exergy analyses of the proposed combined system are presented. The effects of the five main parameters on the system thermodynamic performance are carried out, which are direct radiation intensity, concentration ratio, sCO2 pressure ratio, preheater terminal temperature difference, and flash temperature. Results show that the OFC with R245ca has the highest exergy efficiency among the different four fluids. The energy efficiency and exergy efficiency of the total system are 26.03% and 33.38%, respectively, since the energy losses exist in the heliostat field and central receivers. There observes that through the parametric study the parameters of direct radiation intensity and concentration ratio are larger causing better system thermodynamic performance. Through the thermodynamic analysis, there observes the power cycle subsystem has the largest energy loss, while the central receiver possesses the highest among other subsystems.