A Survey on Nanoscale Atomic Clusters Structural Optimization Using Computational Intelligence Algorithms

Atomic clusters are nanoscale aggregates of atom particles whose properties range from those of their fundamental constituents to those of bulk limit as the number of particles increases. For years, researchers have shown great interests on chemical physical properties of nanoscale atomic clusters. With the rapid development of computer technology, a variety of theoretical simulation research clusters have become a focus in this research area. The emerging computational intelligent algorithms are more suitable for this optimization, including Simulated Annealing (SA), Monte Carlo (MC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Nonetheless, most of them lack the combination with Computational Geometry to optimize the precise optimum structure. Accordingly, another current tendency in study large cluster systems is using computational intelligence algorithms in conjunction with standard quantum chemical procedures, especially Density Functional Theory (DFT), which is often used to verify and/or local optimize the results.