Multilayered graphene films prepared at moderate temperatures using energetic physical vapour deposition

Carbon films were energetically deposited onto copper and nickel foil using a filtered cathodic vacuum arc deposition system. Raman spectroscopy, scanning electron microscopy, transmission electron microscopy and UV–visible spectroscopy showed that graphene films of uniform thickness with up to 10 layers can be deposited onto copper foil at moderate temperatures of 750 C. The resulting films, which can be prepared at high deposition rates, were comparable to graphene films grown at 1050 C using chemical vapour deposition (CVD). This difference in growth temperature is attributed to dynamic annealing which occurs as the film grows from the energetic carbon flux. In the case of nickel substrates, it was found that graphene films can also be prepared at moderate substrate temperatures. However much higher carbon doses were required, indicating that the growth mode differs between substrates as observed in CVD grown graphene. The films deposited onto nickel were also highly non uniform in thickness, indicating that the grain structure of the nickel substrate influenced the growth of graphene layers. 

Optimal day-ahead scheduling of integrated urban energy systems

An optimal day-ahead scheduling method (ODSM) for the integrated urban energy system (IUES) is introduced, which considers the reconfigurable capability of an electric distribution network. The hourly topology of a distribution network, a natural gas network, the energy centers including the combined heat and power (CHP) units, different energy conversion devices and demand responsive loads (DRLs), are optimized to minimize the day-ahead operation cost of the IUES. The hourly reconfigurable capability of the electric distribution network utilizing remotely controlled switches (RCSs) is explored and discussed. The operational constraints from the unbalanced three-phase electric distribution network, the natural gas network, and the energy centers are considered. The interactions between the electric distribution network and the natural gas network take place through conversion of energy among different energy vectors in the energy centers. An energy conversion analysis model for the energy center was developed based on the energy hub model. A hybrid optimization method based on genetic algorithm (GA) and a nonlinear interior point method (IPM) is utilized to solve the ODSM model. Numerical studies demonstrate that the proposed ODSM is able to provide the IUES with an effective and economical day-ahead scheduling scheme and reduce the operational cost of the IUES.