Alloy Clusters: Structural Classes, Mixing, and Phase Changes

Jellinek, Julius; Krissinel, E.B.

doi:10.1007/978-3-642-58389-6_12

Cited by 66 publications

(75 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At first we remark that, although the melting point is depressed, its reduction is smaller than that of LJ clusters, and is strongly material dependent Jellinek et al, 1986;Jellinek and Garzón, 1991). Usually melting is accompanied by a peak in the specific heat, and by a substantial rearrangement of the cluster.…”

Section: Noble and Transition Metal Clustersmentioning

confidence: 82%

“…As a result, simulated annealing is less efficient than genetic and basin-hopping algorithms (Hartke, 1993;Zeiri, 1995). To avoid trapping in a single basin, one can make long high-T MC or MD runs, collecting a large quantity of different snapshots and quenching them down Sebetci and Güvenc, 2003), monitoring the short-term average of kinetic energy (Garzón and Posada-Amarillas, 1996;Jellinek and Garzón, 1991). T must be chosen carefully.…”

Section: Global Optimization Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Structural properties of nanoclusters: Energetic, thermodynamic, and kinetic effects

Baletto¹,

Ferrando²

2005

Rev. Mod. Phys.

1,673

1,498

View full text Add to dashboard Cite

The structural properties of free nanoclusters are reviewed. Special attention is paid to the interplay of energetic, thermodynamic and kinetic factors in the explanation of the clusters structures which are actually observed in the experiments. The review starts with a brief summary of the experimental methods for the production of free nanoclusters, and then proceeds with a guideline given by theoretical and simulation issues, always discussed in close connection with the experimental results. The energetic properties are treated first, evidencing general trends, describing the methods for modelling the interactions between the elementary cluster constituents, and for the global optimization on the cluster potential energy surface. After that, a chapter on cluster thermodynamics follows. The discussion includes the analysis of solid-solid structural transitions, and of melting with its size dependence. The last part is devoted to the growth kinetics of free nanoclusters, and treats the growth of isolated clusters and their coalescence. Several specific systems are analyzed.

show abstract

Section: Noble and Transition Metal Clustersmentioning

confidence: 82%

Section: Global Optimization Methodsmentioning

confidence: 99%

Structural properties of nanoclusters: Energetic, thermodynamic, and kinetic effects

Baletto¹,

Ferrando²

2005

Rev. Mod. Phys.

1,673

1,498

View full text Add to dashboard Cite

show abstract

“…Thus most of the theoretical studies done on bimetallic alloy clusters take resort to some empirical manybody potential to reduce the computational expense. 1,21,22,23,24,25,26 Our study is one of the very few which uses an ab-initio methodology for transition metal nanoalloy clusters. Here we study bimetallic Mn x Co y clusters in the size ranging from 2 to 5 for all possible stoichiometry.…”

Section: Introductionmentioning

confidence: 99%

Magnetism in small bimetallic Mn-Co clusters

et al. 2008

View full text Add to dashboard Cite

Effects of alloying on the electronic and magnetic properties of MnxCoy (x + y=n=2-5; x=0-n) and Mn2Co11 nanoalloy clusters are investigated using the density functional theory (DFT). Unlike the bulk alloy, the Co-rich clusters are found to be ferromagnetic and the magnetic moment increases with Mn-concentration, and is larger than the moment of pure Con clusters of same size. For a particular sized cluster the magnetic moment increases by 2 µB/Mn-substitution, which is found to be independent of the size and composition. All these results are in good agreement with recent Stern-Gerlach (SG) experiments [Phys. Rev. B 75, 014401 (2007) and Phys. Rev. Lett. 98, 113401 (2007)]. Likewise in bulk MnxCo1−x alloy, the local Co-moment decreases with increasing Mn-concentration.

show abstract

“…One stage is focused on global geometry optimisation, and it involves the use of appropriate displacement movesoperations that alter the coordinates of at least one constituent particle without affecting the associated labels. Here we focus on the other stage, intended to find an optimal permutational isomer (homotop 3 ) for a particular geometrical motif. The search typically relies on exchange moves-operations that interchange the labels of two particles without immediately affecting the coordinates, thus performing a function that is complementary to that of displacement moves.…”

mentioning

confidence: 99%

Communication: A new paradigm for structure prediction in multicomponent systems

Schebarchov¹,

Wales²

2013

The Journal of Chemical Physics

View full text Add to dashboard Cite

We analyse the combinatorial aspect of global optimisation for multicomponent systems, which involves searching for the optimal chemical ordering by permuting particles corresponding to different species. The overall composition is presumed fixed, and the geometry is relaxed after each permutation in order to relieve local strain. From ideas used to solve graph partitioning problems we devise a deterministic search scheme that outperforms (by orders of magnitude) conventional and self-guided basin-hopping global optimisation. The search is guided by the energy gain from either swapping particles i and j (ΔEij) or changing the identity of particles i (ΔEi). These quantities are derived from the underlying (arbitrary) energy function, hence not constituting external bias, and for site-separable force fields each ΔEi can be approximated simply and efficiently. In our self-guided variant of basin-hopping, particles are weighted by an approximate ΔEi when randomly selected for an exchange, yielding a significant improvement for segregated multicomponent systems with modest particle size mismatch.

show abstract

Alloy Clusters: Structural Classes, Mixing, and Phase Changes

Cited by 66 publications

References 62 publications

Structural properties of nanoclusters: Energetic, thermodynamic, and kinetic effects

Structural properties of nanoclusters: Energetic, thermodynamic, and kinetic effects

Magnetism in small bimetallic Mn-Co clusters

Communication: A new paradigm for structure prediction in multicomponent systems

Contact Info

Product

Resources

About