Genetic algorithm-Monte Carlo hybrid geometry optimization method for atomic clusters

Dugan, Nazim
Erkoç, Şakir
In this work, an evolutionary type global optimization method for identifying the stable geometries of atomic clusters is developed and applied to carbon clusters for testing purpose. Monte Carlo (MC) type local optimization is used between genetic algorithm (GA) steps together with a special Mutation operation designed for the Cluster geometry optimization problem. Cluster geometries and the corresponding potential energies for carbon obtained with this GA-MC hybrid method are compared with available results in the literature and reliability of the method is justified for moderate sized carbon clusters.


Thermodynamics of small platinum clusters
Sebetci, A; Guvenc, ZB; Kökten, Hatice (Elsevier BV, 2006-03-01)
Using the Voter and Chen version of an embedded atom model, derived by fitting simultaneously to experimental data of both the diatomic molecule and bulk platinum, we have studied the melting behavior of free, small platinum clusters in the size range of N = 15-19 in the molecular dynamics simulation technique. We present an atom-resolved analysis method that includes physical quantities such as the root-mean-square bond-length fluctuation and coordination number for individual atoms as functions of tempera...
Application of non-convex rate dependent gradient plasticity to the modeling and simulation of inelastic microstructure development and inhomogeneous material behavior
Klusemann, Benjamin; Yalçınkaya, Tuncay; Geers, M. G. D.; Svendsen, Bob (Elsevier BV, 2013-12-01)
In this study, a two-dimensional rate-dependent gradient crystal plasticity model for non-convex energetic hardening is formulated and applied to the simulation of inelastic microstructure formation. In particular, non-convex hardening is modeled via a Landau-Devonshire potential for self-hardening and two interaction-matrix-based forms for latent hardening. The algorithmic formulation and the numerical implementation treats the displacement and the glide-system slips as the primary field variables. The num...
Structural properties of boron carbide nanoparticles: Application of a new set of Stillinger-Weber parameters
Dugan, Nazim; Erkoç, Şakir (Elsevier BV, 2011-08-01)
A suitable Stillinger-Weber (SW) potential energy function parameter set is developed for finite boron structures by genetic algorithm and trial error techniques. Boron structure geometries in 7-24 atoms range, calculated by ab initio methods, are taken as the fitting criteria in the parameter set development. This parameter set is used together with another SW parameter set developed for carbon-carbon interactions in order to investigate boron carbide nanoparticles in the form of BxCx where 8 <= x <= 14. I...
Three dimensional computational analysis of fatigue crack propagation in functionally graded materials
Sabuncuoglu, Baris; Dağ, Serkan; YILDIRIM, BORA (Elsevier BV, 2012-02-01)
This article proposes a new finite elements based three dimensional method developed to study the phenomenon of fatigue crack propagation in functionally graded materials (FGMs). The particular problem examined in detail is that of an initially-elliptical crack located in a functionally graded medium, subjected to mode I cyclic loading. The crack is modelled by employing three dimensional finite elements; and the stress intensity factors (SIFs) around the crack front are computed by the application of the d...
Genetic algorithms applied to Li+ ions contained in carbon nanotubes: An investigation using particle swarm optimization and differential evolution along with molecular dynamics
Chakraborti, N.; Das, S.; Jayakanth, R.; Pekoz, R.; Erkoç, Şakir (Informa UK Limited, 2007-01-01)
Empirical potentials based upon two and three body interactions were applied to the Li+ -C system, assuming the Li+ ions to be distributed inside high-symmetry, single walled carbon nanotubes of different chirality. Structural optimizations for various assemblages were conducted using evolutionary and genetic algorithms, where differential evolution and particle swarm optimization techniques worked satisfactorily. The results were compared with the outcome of some rigorous molecular dynamics simulations. Th...
Citation Formats
N. Dugan and Ş. Erkoç, “Genetic algorithm-Monte Carlo hybrid geometry optimization method for atomic clusters,” COMPUTATIONAL MATERIALS SCIENCE, pp. 127–132, 2009, Accessed: 00, 2020. [Online]. Available: