Density-functional theory study of Aln and Aln−1Mg (n=2–17) clusters

Ouyang, Yifang; Wang, Peng; Xiang, Peng; Chen, Hongmei; Du, Yong

doi:10.1016/j.comptc.2012.01.012

Cited by 33 publications

(23 citation statements)

References 49 publications

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“…The Cu atom prefers to stay on the surface of Al N clusters. The same phenomenon is observed in Al n Mg [16] and Al n N [24] clusters. clusters.…”

Section: Structuressupporting

confidence: 65%

“…[8] are not the lowest energy structures. From Fig.1 it can be seen that the small Al n Cu clusters usually inherit the configurations of the host Al N clusters [16]. The differences arise as the cluster size n increased.…”

Section: Structuresmentioning

confidence: 93%

“…It indicates that the chemical reactivity of the above clusters is better than their neighbors. In general, the clusters with odd number of atoms tend to have relatively larger gaps than their adjacent clusters with even number atoms [16]. A large HOMO-LUMO gap generally corresponds to a closed-shell electronic configuration with high stability [24].…”

Section: Structuresmentioning

confidence: 99%

“…The double numerical polarization (DNP) basis set [11] was chosen. To avoid trapping in the local minima of the potential energy surface, all the geometries with unconstrained symmetry and various 2nd Annual International Conference on Advanced Material Engineering (AME 2016) possible spin multiplicities were considered [16]. Harmonic vibrational frequency analysis was performed to verify that the obtained geometries and the stable structures with no imaginary frequencies [16].…”

Section: Computational Detailsmentioning

confidence: 99%

“…To avoid trapping in the local minima of the potential energy surface, all the geometries with unconstrained symmetry and various 2nd Annual International Conference on Advanced Material Engineering (AME 2016) possible spin multiplicities were considered [16]. Harmonic vibrational frequency analysis was performed to verify that the obtained geometries and the stable structures with no imaginary frequencies [16]. In the geometry optimization processes, the energy gradient and atomic displacement converged to within 1×10 -5 Hartree/Bohr and 5×10 -3 Å, respectively.…”

Section: Computational Detailsmentioning

confidence: 99%

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Geometries, Stability and Growth Strategies of Small AlnCu (n=1-9) Clusters

Li¹,

Zhou²,

Wang³

et al. 2016

Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)

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Abstract. To improve the anti-crack performance of Al-Cu alloys, the geometries, relative stability as well as growth strategies of Al n Cu (n=1-9) clusters were investigated with spin polarized density functional theory: BLYP. The results reveal that the Cu atom tends to convergence aluminum clusters to close-packed structures. The average binding energies of Al n Cu are slightly higher than that of Al N clusters. Local peaks of the HOMO-LUMO gaps are found at n=1, 4, 6, and 9. The reaction energies of Al n Cu (n=1-2) are higher which means that Al n Cu clusters are easier to react with Al clusters. Cu atom prior reacts with Al atom.

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“…The Cu atom prefers to stay on the surface of Al N clusters. The same phenomenon is observed in Al n Mg [16] and Al n N [24] clusters. clusters.…”

Section: Structuressupporting

confidence: 65%

Section: Structuresmentioning

confidence: 93%

Section: Structuresmentioning

confidence: 99%

Section: Computational Detailsmentioning

confidence: 99%

Section: Computational Detailsmentioning

confidence: 99%

See 3 more Smart Citations

Geometries, Stability and Growth Strategies of Small AlnCu (n=1-9) Clusters

Li¹,

Zhou²,

Wang³

et al. 2016

Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)

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Structural evolution and electronic properties of pure and semiconductor atom doped in clusters: In_n⁻, In_nSi⁻, and In_nGe⁻ (n = 3–16)

et al. 2022

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The bonding and electronic properties of Inn−, InnSi−, and InnGe− (n = 3–16) clusters have been computationally investigated. An intensive global search for the ground‐state structures of these clusters were conducted using the genetic algorithm coupled with density functional theory (DFT). The ground‐state structures of these clusters have been identified through the comparison between simulated photoelectron spectra (PES) of the found lowest‐energy isomers and the experimentally measured ones. Doping semiconductor atom (Si or Ge) can significantly change the structures of the In clusters in most sizes, and the dopant prefers to be surrounded by In atoms. There are three structural motifs for InnX− (X = Si, Ge, n = 3–16), and the transition occurs at sizes n = 5 and 13. All InnSi− and InnGe− share the same configurations and similar electronic properties except for n = 8. Among all above studied clusters, In13− stands out with the largest vertical detachment energy (VDE), HOMO–LUMO gap, (Eb) and second order energy difference Δ2E due to its closed electronic shell of (1S)2(1P)6(1D)10(2S)2(1F)14(2P)6. Similarly, the neutral In12X (X = Si, Ge) clusters are also identified as superatoms but with electronic configuration of (1S)2(1P)6(2S)2(1D)10(1F)14(2P)6.

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Molecule‐adapted basis sets optimized with a quantum Monte Carlo method

Arruda

Neto

Campos

et al. 2014

Int J of Quantum Chemistry

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The Monte Carlo simulated annealing method is adapted to optimize correlated Gaussian‐type functions in nonrelativistic molecular environments. Starting from an atom‐centered atomic Gaussian basis set, the uncontracted functions are reoptimized in the molecular environments corresponding to the H2O, CN−, N2, CO, BF, NO+, CO2, and CS systems. These new molecular adapted basis sets are used to calculate total energies, harmonic vibrational frequencies, and equilibrium geometries at a correlated level of theory. The present methodology is a simple and effective way to improve molecular correlated wave functions, without the need to enlarge the molecular basis set. Additionally, this methodology can be used to generate hierarchical sequences of molecular basis sets with increasing size, which are relevant to establish complete basis set limits. © 2014 Wiley Periodicals, Inc.

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Density-functional theory study of Aln and Aln−1Mg (n=2–17) clusters

Cited by 33 publications

References 49 publications

Geometries, Stability and Growth Strategies of Small AlnCu (n=1-9) Clusters

Geometries, Stability and Growth Strategies of Small AlnCu (n=1-9) Clusters

Structural evolution and electronic properties of pure and semiconductor atom doped in clusters: In_n⁻, In_nSi⁻, and In_nGe⁻ (n = 3–16)

Molecule‐adapted basis sets optimized with a quantum Monte Carlo method

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Density-functional theory study of Aln and Aln−1Mg (n=2–17) clusters

Cited by 33 publications

References 49 publications

Geometries, Stability and Growth Strategies of Small AlnCu (n=1-9) Clusters

Geometries, Stability and Growth Strategies of Small AlnCu (n=1-9) Clusters

Structural evolution and electronic properties of pure and semiconductor atom doped in clusters: Inn−, InnSi−, and InnGe− (n = 3–16)

Molecule‐adapted basis sets optimized with a quantum Monte Carlo method

Contact Info

Product

Resources

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Structural evolution and electronic properties of pure and semiconductor atom doped in clusters: In_n⁻, In_nSi⁻, and In_nGe⁻ (n = 3–16)