In this paper we present a method for optimizing of metal nanoparticle structures. The core of the method is a lattice Monte-Carlo method with different lattices combined with an approach from molecular dynamics. Interaction between atoms is calculated using multi-particle tight-binding potential of Gupta – Cleri&Rosato. The method allows solving of problems with periodic boundary conditions. It can be used for modeling of one-dimensional (nanowire, tube) and two-dimensional (nano-film) structures. If periodic boundary conditions are not given, we assume finite dimensions of the model lattice. In addition, automatic relaxation of the crystal lattice can be performed in order to minimize further the potential energy of the system. Both stretching and compressing of the lattice is permitted. A computer implementation of the method is developed. It allows easy and efficient operation. It uses the commonly accepted XYZ format for describing metal nanoparticles. The parameters of the method, such as number and type of metal atoms, temperature of the system, etc. are entered on a separate command line. The method is tested extensively on a large set of examples.
CITATION STYLE
Myasnichenko, V., Sdobnyakov, N., Kirilov, L., Mikhov, R., & Fidanova, S. (2019). Monte carlo approach for modeling and optimization of one-dimensional bimetallic nanostructures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11189 LNCS, pp. 133–141). Springer Verlag. https://doi.org/10.1007/978-3-030-10692-8_15
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