Model potential for silicon clusters and surfaces

Mistriotis, Α.; Froudakis, Georgios; Vendras, P. J.; Flytzanis, N.

doi:10.1103/physrevb.47.10648

Cited by 14 publications

(12 citation statements)

References 26 publications

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“…In contrast, Si 7 is again a simple case: A pentagonal bipyramid is proposed by Raghavachari and Rohlfing's ab-initio calculations, 7 and various empirical potential studies agree on this, e.g. Mistriotis et al, 8,9 Li, Jonston and Murrell, 2 and Bolding and Andersen; 4 in fact, it is quite hard not to favor this geometry. Also, for Si n (n ¼ 3,4,6,7) clusters, Raman spectra 10,11 and IR spectra 12 are in good agreement with the results of theoretical studies.…”

Section: Introductionmentioning

confidence: 98%

Global geometry optimization of small silicon clusters with empirical potentials and at the DFT level

Tekin

Hartke

2004

Phys. Chem. Chem. Phys.

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Section: Introductionmentioning

confidence: 98%

Global geometry optimization of small silicon clusters with empirical potentials and at the DFT level

Tekin

Hartke

2004

Phys. Chem. Chem. Phys.

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“…Many of these potentials can be divided into three main categories, namely Stillinger & Weber (SW)-type, Tersoff-type, and potentials derived directly from ab initio data. The SW, 32 Gong, 33 Mistriotis, 34,35 and Modified Mistriotis 28 potentials belong to the first class. In these potentials, the total potential energy is expanded into manybody terms.…”

Section: Empirical Potentialsmentioning

confidence: 99%

GLOBAL GEOMETRY OPTIMIZATION OF SILICON CLUSTERS EMPLOYING EMPIRICAL POTENTIALS, DENSITY FUNCTIONALS, AND AB INITIO CALCULATIONS

Tekin

Hartke

2005

J. Theor. Comput. Chem.

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Sin clusters in the size range n = 4-30 have been investigated using a combination of global structure optimization methods with DFT and ab initio calculations. One of the central aims is to provide explanations for the structural transition from prolate to spherical outer shapes at about n = 25, as observed in ion mobility measurements. Firstly, several existing empirical potentials for silicon and a newly generated variant of one of them were better adapted to small silicon clusters, by global optimization of their parameters. The best resulting empirical potentials were then employed in global cluster structure optimizations. The most promising structures from this stage were relaxed further at the DFT level with the hybrid B3LYP functional. For the resulting structures, single point energies have been calculated at the LMP2 level with a reasonable medium-sized basis set, cc-pVTZ. These DFT and LMP2 calculations were also carried out for the best structures proposed in the literature, including the most recent ones, to obtain the currently best and most complete overall picture of the structural preferences of silicon clusters. In agreement with recent findings, results obtained at the DFT level do support the shape transition from prolate to spherical structures, beginning with Si 26 (albeit not completely without problems). In stark contrast, at the LMP2 level, the dominance of spherical structures after the transition region could not be confirmed. Instead, just as below the transition region, prolate isomers are obtained as the lowestenergy structures for n ≤ 29. We conclude that higher (probably multireference) levels of theoretical treatments are needed before the puzzle of the silicon cluster shape transition at n = 25 can safely be considered as explained.

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“…However they did not correlate the size and shape of individual clusters, and they were also unable to resolve the atomic structure of the Si magic clusters. Several Si magic cluster structures have been predicted theoretically, [23][24][25][26][27][28][29][30][31][32][33][34][35] with varying geometries such as ring, prism, and octahedron structures, for different numbers of Si n ͑4 Յ n Յ 20͒ where n is number of Si atoms per cluster. These theoretical calculations have also showed that clusters with different numbers of Si atoms display different bonding structures and hence do not share similar electronic or physical properties.…”

Section: Introductionmentioning

confidence: 99%

“…These theoretical calculations have also showed that clusters with different numbers of Si atoms display different bonding structures and hence do not share similar electronic or physical properties. [23][24][25][26][27][28][29][30][31][32][33][34][35] However, these atomic models only account for freestanding clusters in idealized minimum energy structures and do not accurately represent magic clusters existing on reconstructed surfaces. It is anticipated that the bonding characteristics of these proposed Si clusters may be altered with the introduction of an underlying substrate surface potential.…”

Section: Introductionmentioning

confidence: 99%

Self-assembly, dynamics, and structure of Si magic clusters

et al. 2009

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We demonstrate the preferential formation and self-assembly of monodisperse Si magic clusters ͑X 4 ͒ of size ϳ13.5Ϯ 0.5 Å on Si͑111͒-͑7 ϫ 7͒ surface using scanning tunneling microscope. The growth process is observed to occur via a stepwise assembly of planarized Si tetramers ͑X 1 ͒ formed from Si adatoms deposited at room temperature, leading to Si tetraclusters ͑X 2 ͒ ͑size ϳ4.6Ϯ 0.5 Å͒ and culminating in tetracluster dimer ͑X 3 ͒ and trimer ͑X 4 ͒ formations as the surface is being annealed progressively to 150°C. The respective cluster species density distribution at each annealing temperature also shows the preferential formation of X 1 → X 2 → X 3 → X 4 at higher temperatures, which we describe using surface reaction schemes; X 1 → X 2 , X 2 + X 2 → X 3 , and X 2 + X 3 → X 4 . We determine the activation and formation energies for respective cluster species and elucidate the formation energetics and dynamics of tetraclusters which function unequivocally as fundamental building blocks in the self-assembly of stable Si magic clusters. Finally, we resolve the structure of the Si magic cluster to comprise three tetraclusters or n = 12 Si atoms taking into consideration ͑i͒ cluster symmetry and alignment, ͑ii͒ close packing, and ͑iii͒ minimization of dangling bonds.

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Model potential for silicon clusters and surfaces

Cited by 14 publications

References 26 publications

Global geometry optimization of small silicon clusters with empirical potentials and at the DFT level

Global geometry optimization of small silicon clusters with empirical potentials and at the DFT level

GLOBAL GEOMETRY OPTIMIZATION OF SILICON CLUSTERS EMPLOYING EMPIRICAL POTENTIALS, DENSITY FUNCTIONALS, AND AB INITIO CALCULATIONS

Self-assembly, dynamics, and structure of Si magic clusters

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