We report phase separation in a mixture of "hot" and "cold" three-dimensional dumbbells which interact by Lennard-Jones potential. We also have studied the effect of asymmetry of dumbbells and the variation of ratio of "hot" and "cold" dumbbells on their phase separation. The ratio of the temperature difference between hot and cold dumbbells to the temperature of cold dumbbells is a measure of the activity χ of the system. From constant density simulations of symmetric dumbbells, we observe that the "hot" and "cold" dumbbells phase separate at higher activity ratio (χ > 5.80) compared to that of a mixture of hot and cold Lennard-Jones monomers (χ > 3.44). We find that, in the phase-separated system, the hot dumbbells have high effective volume and hence high entropy which is calculated by two-phase thermodynamic method. The high kinetic pressure of hot dumbbells forces the cold dumbbells to form dense clusters such that at the interface the high kinetic pressure of hot dumbbells is balanced by the virial pressure of cold dumbbells. We find that phase separation pushes the cluster of cold dumbbells to have solidlike ordering. Bond orientation order parameters reveal that the cold dumbbells form solidlike ordering consisting of predominantly face-centered cubic and hexagonal-close packing packing, but the individual dumbbells have random orientations. The simulation of the nonequilibrium system of symmetric dumbbells at different ratios of number of hot dumbbells to cold dumbbells reveals that the critical activity of phase separation decreases with increase in fraction of hot dumbbells. The simulation of equal mixture of hot and cold asymmetric dumbbells revealed that the critical activity of phase separation was independent of the asymmetry of dumbbells. We also observed that the clusters of cold asymmetric dumbbells showed both crystalline and noncrystalline order depending on the asymmetry of dumbbells.
No abstract
The existing charging infrastructure needs expansion and upgrade with the growing fleet of electric vehicles (EV). The electric grids are largely affected by the uncontrolled charging cycles. To overcome this drawback, the hybrid charging stations are incorporated with battery storage and renewable energy sources. The power necessary from the grid can be buffered using a battery and renewable source attached to the charging station thereby avoiding the grid constraints and peaks. It has been a challenge to trace the origin of the battery’s energy till date. The battery energy storage and a simple photovoltaic system is incorporated in a hybrid EV charging station. Uncontrolled EV charging and its adverse effects can be overcome by this technology by accurately calculating the share of renewable energy derived from the battery. Multi-attribute utility theory is used for optimizing the EV charging level and scheduling the battery charging and discharging. Minimizing battery degradation and charging cost while maximizing the renewable energy from the battery and PV sources are the major criteria of optimization. Multicriteria optimization function is used along with the genetic algorithm optimization scheme to address the optimization issues. Optimal capacity of the battery and optimization strategy is affected by the preferences in decision making.
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