Melting properties of mixed Ni13-xAlx(x=0 to 13) clusters

Starting from the configuration full optimized by Genetic Algorithm (GA), the melting behaviors of Binary Ni13-xAlx(x=0 to 13) clusters have been investigated by Monte Carlo (MC) simulations with Metropolis algorithm with a n-body Gupta potential. In contrast to bulk, these clusters have smeared first order transitions occurring over a range of temperature. The melting temperature Tm calculated from Lindemanns criterion vary drastically with concentrations x. For most clusters studied, the average energy per atom E, the relative root-mean-square (rms) bond length fluchuation δ and the heat capacity C per atom related to the energy fluctuation of the system change with temperature in the transition region in manners differing from LJ and alkali metal clusters. For Ni12Al, Ni7Al6, Ni6Al7, Ni5Al8 clusters, there are behaviors characteristic of magic number in C, which do not exist in the pure TM clusters.

Melting properties of mixed Ni13-xAlx(x=0 to 13) clusters

Starting from the configuration full optimized by Genetic Algorithm (GA), the melting behaviors of Binary Ni13-xAlx(x=0 to 13) clusters have been investigated by Monte Carlo (MC) simulations with Metropolis algorithm with a n-body Gupta potential. In contrast to bulk, these clusters have smeared first order transitions occurring over a range of temperature. The melting temperature Tm calculated from Lindemanns criterion vary drastically with concentrations x. For most clusters studied, the average energy per atom E, the relative root-mean-square (rms) bond length fluchuation δ and the heat capacity C per atom related to the energy fluctuation of the system change with temperature in the transition region in manners differing from LJ and alkali metal clusters. For Ni12Al, Ni7Al6, Ni6Al7, Ni5Al8 clusters, there are behaviors characteristic of magic number in C, which do not exist in the pure TM clusters.