MINIMIZATION OF SMALL SILICON CLUSTERS USING THE SPACE-FIXED MODIFIEDGENETIC ALGORITHM METHOD

A space-fixed modified genetic algorithm (SFMGA) approach was used to obtain global minima for the silicon clusters (Si)(n) using a semiempi rical potential. One modification to the usual GA is the use of gradie nt-driven minimization of each geometry. A novel feature of the method is the use of space-fixed atomic coordinates. The advantages of these coordinates are discussed. The method found all minima previously rep orted fern = 3-10, and improved on those for n = 5-8. That the commonl y-used method of seeding a cluster can actually detract from minimizat ion efficiency, is also shown.