2014
DOI: 10.1063/1.4886337
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A genetic algorithm for first principles global structure optimization of supported nano structures

Abstract: We present a newly developed publicly available genetic algorithm (GA) for global structure optimisation within atomic scale modeling. The GA is focused on optimizations using first principles calculations, but it works equally well with empirical potentials. The implementation is described and benchmarked through a detailed statistical analysis employing averages across many independent runs of the GA. This analysis focuses on the practical use of GA's with a description of optimal parameters to use. New resu… Show more

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Cited by 195 publications
(211 citation statements)
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“…A relevant challenge when dealing with clusters is their very rich polymorphism, both in the gas phase and on the surface. The problem to identify the global minimum requires, for instance, the use of genetic algorithms, as recently done for Au 10 on rutile TiO 2 [61]. This technique, however, is not only computationally extremely demanding, but accounts for the most stable isomer at a temperature of 0 K, while at finite temperatures small clusters may not be in their global minimum structure most of the time.…”
mentioning
confidence: 98%
“…A relevant challenge when dealing with clusters is their very rich polymorphism, both in the gas phase and on the surface. The problem to identify the global minimum requires, for instance, the use of genetic algorithms, as recently done for Au 10 on rutile TiO 2 [61]. This technique, however, is not only computationally extremely demanding, but accounts for the most stable isomer at a temperature of 0 K, while at finite temperatures small clusters may not be in their global minimum structure most of the time.…”
mentioning
confidence: 98%
“…The ReaxFF parameters for P/H systems were optimized using a modified version of the evolutionary algorithms (EA) software suite OGOLEM, 52,53 which is able to globally optimize ReaxFF parameter sets with high parallel efficiency. Based on DFT calculations for bulk black phosphorus, pristine and defected black phosphorene, blue phosphorene, phosphorus hydride molecules and phosphorus clusters, ReaxFF parameters were generated for P-P and P-H bond energies, P-P-P, H-P-P and H-P-H valence angle energies and for H-P-P-P and H-P-P-H torsion energies.…”
Section: Dft Training Of Force Fieldmentioning
confidence: 99%
“…1 were selected (starting with , , , , ). The parameters were fitted to the training set using OGOELM 52,53 .…”
Section: Dft Training Of Force Fieldmentioning
confidence: 99%
“…We note that the equilibrium Bi-G distance (0.33 nm) is typical of physisorbed graphene, which is dominated by vdW interactions. In turn, the Bi-G distances resulting from a 0.07 nm displacement are more characteristic of chemisorbed graphene, which is expected to hybridize more with the substrate, significantly altering the electronic structure of graphene and even leading to band gap fomation 39,40,45 . The optB88-vdW functional used in this study is able to properly describe these two bonding regimes in graphene-metal contacts 46 and remarkably, such a distortion has a relatively small energy cost (~80 meV per graphene unit cell).…”
mentioning
confidence: 99%