Molecular dynamics simulation of shell-symmetric Pd nanoclusters

Pan, Yuhui; Huang, Shiping; Liu, Zhi Ping; Wang, W.

doi:10.1080/08927020500449401

Cited by 5 publications

(26 citation statements)

References 10 publications

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“…5 depicts the G(r) variation with temperature for 8-cub using both potentials. In both cases, the G(r) shows the same pattern for solid and liquid-like states in agreement with previously reported patterns (Pan et al, 2005). The solid-like state at the bottom of each figure can be interpreted from 4 main peaks indicated by dashed line corresponding to 4 shells (not to be confused with 4th NNs).…”

Section: Radial Distribution Functionsupporting

confidence: 90%

“…Fig. 7 compares normalized T mp obtained from caloric curves in comparison with previous MD (Pan et al, 2005;Miao et al, 2005) and MC (Lee et al, 2001) simulations. The figure also contains values calculated from Eq.…”

Section: Common Neighbor Analysismentioning

confidence: 95%

“…Finally, snapshot L shows a complete liquid state. It is worth noting that the minor C p peak, is sometimes misinterpreted as surface melting (Pan et al, 2005). However, as mentioned in the introduction, the improper use of G(r) was the real reason for the misinterpretation.…”

Section: Melting Criteriamentioning

confidence: 99%

“…Alternatively, atomistic Monte Carlo (MC) (Westergren and Nordholm, 2003) and molecular dynamics (MD) (Baletto et al, 2002;Pan et al, 2005;Miao et al, 2005;Schebarchov and Hendy, 2006) simulations have proven to be an excellent tool for probing the nanoparticles stability and melting behavior. For instance, Baletto et al (2002) have shown that for small Pd cluster icosahedron (ico) structure is more stable while decahedron (dec) and cuboctahedron (cub) are more stable at the moderate and large clusters, respectively.…”

mentioning

confidence: 99%

“…the diffusion of the surface atoms, those have more degree of freedom, into inner shells causes a broadening of the G(r) peak for the outer shell which can be misinterpreted as surface melting (Bertoldi et al, 2017). They regretted this drawback by reporting quasi-solid core at the melting point (T mp ) of clusters while their G(r) patterns indicated broad peaks for all shells (Pan et al, 2005). They also observed a minor peak prior to the main melting peak in the specific heat capacity C p of the ico cluster which they attributed to the surface melting.…”

mentioning

confidence: 99%

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Size and shape-dependent melting mechanism of Pd nanoparticles

et al. 2018

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Molecular dynamics simulation is employed to understand the thermodynamic behavior of cuboctahedron (cub) and icosahedron (ico) nanoparticles with 2 − 20 number of full shells. The original embedded atom method (EAM) was compared to the more recent highly optimized version as interatomic potential. The thermal stability of clusters were probed using potential energy and specific heat capacity as well as structure analysis by radial distribution function (G(r)) and common neighbor analysis (CNA), simultaneously, to make a comprehensive picture of the solid state and melting transitions. The result shows ico is the only stable shape of small clusters (Pd 55 -Pd 309 using original EAM and Pd 55 using optimized version) those are melting uniformly due to their small diameter. An exception is cub Pd 309 modeled via optimized EAM that transforms to ico at elevated temperatures. A similar cub to ico transition was predicted by original EAM for Pd 923 -Pd 2075 clusters while for the larger clusters both cub and ico are stable up to the melting point. As detected by G(r) and CNA, moderate and large cub clusters were showing surface melting by nucleation of the liquid phase at (100) planes and growth of liquid phase at the surface before inward growth. While diagonal (one corner to another) melting was dominating over ico clusters owing to their partitioned

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Section: Radial Distribution Functionsupporting

confidence: 90%

Section: Common Neighbor Analysismentioning

confidence: 95%

Section: Melting Criteriamentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Size and shape-dependent melting mechanism of Pd nanoparticles

et al. 2018

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Determining phase transition using potential energy distribution and surface energy of Pd nanoparticles

Azadeh

Kateb

Marashi

2019

Computational Materials Science

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Molecular dynamics simulation is employed to understand the thermodynamic behavior of cuboctahedron (cub) and icosahedron (ico) nanoparticles with 2 -20 number of shells (55 -28741 atoms). The embedded atom method was used to describe the interatomic potential. Conventional melting criteria such as potential energy and specific heat capacity (C p ) caloric curves as well as structure analysis by radial distribution function (G(r)) and common neighbor analysis (CNA) were utilized simultaneously to provide a comprehensive picture of the melting process. It is shown that the potential energy distribution and surface energy (γ p ) proposed here are holding several advantages over previous criteria. In particular, potential energy distribution can distinguish between interior and surface atoms and even corner, edge and plane atoms at the surface. While G(r) and CNA are not surface sensitive methods and cannot distinguish between surface melting and an allotropic transition. It is also shown that allotropic change appears more clearly in C p and γ p rather than potential energy. However, determining accurate C p requires enough sampling to be averaged. Finally, a few issues in the current methods for determining γ p were discussed and a simple method based on available models was proposed which, independent of estimation of the surface area, predicts the correct temperature and size-dependent trend in agreement with Guggenheim-Katayama and Tolman's models, respectively.

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Structural evolution of Pd-79 cluster before melting

Qi¹,

Wang²

2007

Materials Letters

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Molecular dynamics simulation of shell-symmetric Pd nanoclusters

Cited by 5 publications

References 10 publications

Size and shape-dependent melting mechanism of Pd nanoparticles

Size and shape-dependent melting mechanism of Pd nanoparticles

Determining phase transition using potential energy distribution and surface energy of Pd nanoparticles

Structural evolution of Pd-79 cluster before melting

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