Topology Optimization in Nano-Scale for Generation of New Graphene-Like Materials

Abstract eng:
The paper describes an application of a hybrid algorithm to optimal searching for new, stable atomic arrangements of two- dimensional graphene-like carbon lattices. The proposed approach combines the parallel evolutionary algorithm and the conjugated- gradient optimization technique. The main goal of the topology optimization is to find stable arrangements of carbon atoms under certain imposed conditions such as density, shape and size of the unit cell. The objective function is formulated as the total potential energy of an atomic carbon system. The optimized structure is considered as a discrete atomic model and interactions between atoms are modeled using the AIREBO potential, especially developed for carbon and hydrocarbon materials. The parallel approach used in computations allows significant reduction of computation time. Validation of the obtained results and examples of the models of the new grapheme-like materials are presented.

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