Stable structures and potential energy surface of the metallic clusters: Ni, Cu, Ag, Au, Pd, and Pt

Wu, Xia; Sun, Yan

doi:10.1007/s11051-017-3907-6

Cited by 31 publications

(28 citation statements)

References 51 publications

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“…In figure 2, structures of Ag n Au n clusters can be categorized into 18 Dh at n = 30, 32–40, 42, 44, 46–48, 52–54, one distorted Ih at Ag 31 Au 31 , one twinned Dh at n = 41, three stacking-fault fcc (sf-fcc) at n = 43, 45 and 51, and two LT at Ag 49 Au 49 and Ag 50 Au 50 . LT motifs were discovered as the global minima of LJ 98 [45], Ni 98 [46] and partial 98-atom Pd–Pt clusters [47], exhibiting T d point group. Apparently, the dominant motif of the studied Ag n Au n clusters is Dh.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, n lib initial configurations are randomly selected from random generation of atomic coordinates and different core structures. The developed AIOA-IC method has been applied for locating the stable structures of trimetallic Cu-Au-Pt clusters [43] [45], Ni 98 [46] and partial 98-atom Pd-Pt clusters [47], exhibiting T d point group. Apparently, the dominant motif of the studied Ag n Au n clusters is Dh.…”

Section: Optimization Algorithmmentioning

confidence: 99%

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Theoretical study of the structures of bimetallic Ag–Au and Cu–Au clusters up to 108 atoms

Tang

et al. 2019

R. Soc. open sci.

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The stable structures of Ag–Au and Cu–Au clusters with 1 : 1, 1 : 3 and 3 : 1 compositions with up to 108 atoms are obtained using a modified adaptive immune optimization algorithm with Gupta potential. The dominant motifs of Ag–Au and Cu–Au clusters are decahedron and icosahedron, respectively. However, in Ag-rich Ag–Au clusters, more icosahedra are found, and in Cu-rich Cu–Au clusters, there exist several decahedral motifs. Four Leary tetrahedral motifs are predicted. Cu core Au shell configurations are predicted in Cu–Au clusters. In Ag–Au clusters, most Ag atoms are on the surface, but partial ones are located in the inner shell, while Au atoms are interconnected in the middle shell.

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Section: Resultsmentioning

confidence: 99%

Section: Optimization Algorithmmentioning

confidence: 99%

Theoretical study of the structures of bimetallic Ag–Au and Cu–Au clusters up to 108 atoms

Tang

et al. 2019

R. Soc. open sci.

Self Cite

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show abstract

“…A common approach to evaluating Gibbs free energy with continually improving DFT approximations [60,61,62,63,64,65,66] is to determine the enthalpy at T = 0 K and then include the temperature-dependent vibrational/configurational entropy terms for viable candidates. Explorations of configurational spaces can be done with a variety of advanced structure prediction methods introduced in the past two decades [7,8,67,68,69,70,71,72,73,74,75,76,77,78,79]. The search strategy employed in our predictive work has involved (i) high-throughput (HT) screening of known relevant prototypes to establish a baseline for compound stability; (ii) unconstrained evolutionary search (ES) to identify new stable motifs; and (iii) stability analysis to explain or improve the stability of identified materials.…”

Section: Confirmed Predictionsmentioning

confidence: 99%

MAISE: Construction of neural network interatomic models and evolutionary structure optimization

Hajinazar,

Thorn,

Sandoval

et al. 2020

Preprint

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MAISE is an open-source package for materials modeling and prediction. The code's main feature is an automated generation of neural network (NN) interatomic potentials for use in global structure searches. The systematic construction of Behler-Parrinello-type NN models approximating ab initio energy and forces relies on two approaches introduced in our recent studies. An evolutionary sampling scheme for generating reference structures improves the NNs' mapping of regions visited in unconstrained searches, while a stratified training approach enables the creation of standardized NN models for multiple elements. A more flexible NN architecture proposed here expands the applicability of the stratified scheme for an arbitrary number of elements. The full workflow in the NN development is managed with a customizable 'MAISE-NET' wrapper written in Python. The global structure optimization capability in MAISE is based on an evolutionary algorithm applicable for nanoparticles, films, and bulk crystals. A multitribe extension of the algorithm allows for an efficient simultaneous optimization of nanoparticles in a given size range. Implemented structure analysis functions include fingerprinting with radial distribution functions and finding space groups with the SPGLIB tool. This work overviews MAISE's available features, constructed models, and confirmed predictions.

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“…Assembly of atoms constitutes nanoclusters, and the structure, thermodynamics, and growth process have been extensively investigated for many elemental systems such as Pb [1][2][3], Ni [4], Au [5,6], and transition metals [7,8] (see also Ref. [9] for a review).…”

Section: Introductionmentioning

confidence: 99%

Mapping the metastability of Lennard-Jones clusters by the maximum vibrational frequency

Ono

2021

Preprint

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We study the structure-stability relationship of the Lennard-Jones (LJ) clusters from a point of view of vibrations. By assuming the size up to N = 1610, we demonstrate that the N -dependence of the maximum vibrational frequency reflects the geometry of the core (the interior of cluster) that will determine the overall geometry of the cluster. This allows us to identify the formation of non-icosahedral structures for N ≤ 150, the vacancy formation at the core for N ≥ 752, and the transition from icosahedral to decahedral structures at N = 1034. We apply the maximum frequency analysis to classify metastable clusters for 19 ≤ N ≤ 39, where transformation pathways between different structures are visualized, and the energy barrier height is estimated simultaneously.

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Stable structures and potential energy surface of the metallic clusters: Ni, Cu, Ag, Au, Pd, and Pt

Cited by 31 publications

References 51 publications

Theoretical study of the structures of bimetallic Ag–Au and Cu–Au clusters up to 108 atoms

Theoretical study of the structures of bimetallic Ag–Au and Cu–Au clusters up to 108 atoms

MAISE: Construction of neural network interatomic models and evolutionary structure optimization

Mapping the metastability of Lennard-Jones clusters by the maximum vibrational frequency

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