Monte Carlo simulations of strain-driven elemental depletion or enrichment in Cu95Al5 and Cu90Al10 alloys

Deng, Lei; Deng, Hang; Tang, Jianfeng; Zhang, Xingming; Xiao, Shifang; Hu, Wangyu

doi:10.1016/j.commatsci.2015.04.039

Cited by 1 publication

(8 citation statements)

References 53 publications

(112 reference statements)

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“…For pure elements, the equilibrium physical properties fitted were the cohesive energy, unrelaxed vacancy formation energy, second-order elastic constants, and the lattice constants. The potential functions of pure elements can be found in ref 69 For binary alloys, the unlike-atom pair potential was determined by assuming a geometric mean between the likeatom potentials. The cross-pair potential functions of alloys also can be found in ref 69 alloying parameters and thus to better reproduce the experimental ordered phases.…”

Section: Model and Methodsmentioning

confidence: 99%

“…The potential functions of pure elements can be found in ref 69 For binary alloys, the unlike-atom pair potential was determined by assuming a geometric mean between the likeatom potentials. The cross-pair potential functions of alloys also can be found in ref 69 alloying parameters and thus to better reproduce the experimental ordered phases. For Cu−Pt alloys, the alloying parameters r c and μ were taken as 1.26 and 2.75.…”

Section: Model and Methodsmentioning

confidence: 99%

“…In the present work, MAEAM potential was adopted to describe atomic bonding in Cu–Pt NAs because of their underpinnings in quantum mechanics, mathematic simplicity, and extendibility to alloy materials. The original EAM potential, , the modified one (MEAM), ,, and our MAEAM one − have already been successfully applied for the study of bulk, surface, and nanoparticles of metals and alloys through incorporating many-body interactions. In short, for a monometallic system, the original EAM represents the energy per atom as a sum of the pair interaction energy and the embedding energy .…”

Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

“…The potential functions of pure elements can be found in ref . The final optimized parameters for Cu and Pt was given in ref and ref , respectively.…”

Section: Model and Methodsmentioning

confidence: 99%

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Chemical Ordering and Surface Segregation in Cu–Pt Nanoalloys: The Synergetic Roles in the Formation of Multishell Structures

Tang

Deng

Xiao³

et al. 2015

J. Phys. Chem. C

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We performed Monte Carlo simulations coupled with MAEAM potentials to study the surface segregation and chemical ordering patterns in Cu−Pt nanoalloy particles for a broad range of sizes, shapes, composition, and temperature. It was found that both the Cu segregation on the surface and the chemical ordering in the core are the general rules and usually compete with each other. Surface segregation of Cu is enhanced with increasing particle size or surface openness or global Cu composition. Despite their different morphologies, most of the types of ordered phases in the core region are the same as bulk alloys. Due to the modification or suppression effects of surface segregation, the degrees of chemical ordering shift to the Ptricher side and are more apparent in a large-sized particle. Particularly, at a narrow composition range, the multishell structures (onion-ring or multishell/maze-like core) form in (truncated) octahedrons, illustrating a subtle synergy between the segregated Cu {111} facets and the L1 1 ordering. The possibility and advantage of transformation from these multishell structures to Pt multilayer shell/single Cu-rich core ORR catalysts by selective etching of Cu were also discussed.

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Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

“…The potential functions of pure elements can be found in ref . The final optimized parameters for Cu and Pt was given in ref and ref , respectively.…”

Section: Model and Methodsmentioning

confidence: 99%

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