Atomistic modeling of the directed-assembly of bimetallic Pt-Ru nanoclusters on Ru(0001)-supported monolayer graphene

Abstract

The formation of Pt-Ru nanoclusters (NCs) by sequential deposition of Pt and Ru on a periodically rumpled graphene sheet supported on Ru(0001) is analyzed by atomistic-level modeling and kinetic Monte Carlo simulations. The "coarse-scale" periodic variation of the adsorption energy of metal adatoms across the graphene sheet directs the assembly of NCs to a periodic array of thermodynamically preferred locations. The modeling describes not only just the NC densities and size distributions, but also the composition distribution for mixed NCs. A strong dependence of these quantities on the deposition order is primarily related to different effective mobilities of Pt and Ru on the supported graphene. Disciplines Biological and Chemical Physics CommentsThe following article appeared in Journal of Chemical Physics 138,13 (2013) The formation of Pt-Ru nanoclusters (NCs) by sequential deposition of Pt and Ru on a periodically rumpled graphene sheet supported on Ru(0001) is analyzed by atomistic-level modeling and kinetic Monte Carlo simulations. The "coarse-scale" periodic variation of the adsorption energy of metal adatoms across the graphene sheet directs the assembly of NCs to a periodic array of thermodynamically preferred locations. The modeling describes not only just the NC densities and size distributions, but also the composition distribution for mixed NCs. A strong dependence of these quantities on the deposition order is primarily related to different effective mobilities of Pt and Ru on the supported graphene.

Point island models for nucleation and growth of supported nanoclusters during surface deposition

“…However, PIM can be applied directly to elucidate and interpret behavior in a host of specific systems, some of which are indicated above. An expanded list of examples includes: (a) homogenous nucleation and growth of metal NCs during deposition on metal, semiconductor, oxide substrates [8,9], with particular utility for Volmer-Weber growth of 3D islands on weakly binding substrates; (b) nucleation inhibited by attachment barriers as observed in metal (111) homoepitaxial systems which exhibit enhanced long-range adatom interactions with a "repulsive ring" due to surface states [38,49]; inhibited attachment was also recently suggested for Fe deposition on graphene [50]; (c) nucleation and growth with strongly anisotropic diffusion as observed for homoepitaxy on dimer-row reconstructed Si(100) surfaces [51]; (d) significant effects on nucleation of small mobile clusters as anticipated for homoepitaxy on metal (100) and (111) surfaces [52]; (e) growth inhibition in strained-layer heteroepitaxy with large mismatch [53]; (f) codeposition to form bimetallic NCs, e.g., of Pt and Au on TiO 2(110) [43], and Pt and Ru on graphene [44]; (g) exchange-mediated nucleation in Fe on Cu(100) [41], and Ni on Ag(111) [42] systems; (h) nucleation of metal NCs on graphite is often facilitated by sputtering to create surface damage and heterogeneous nucleation centers, but even a small fraction of Cu ions from an e-beam evaporator can create sufficient damage that heterogeneous nucleation dominates for Cu deposition on HOPG [46]; (i) deposition of metals on metal-supported graphene, with periodically rumpled morié structure due to lattice mismatch, often results in directed-assembly of 3D NCs [54], and the PIM framework is ideally suited to modeling of this complex process [48].…”

“…For sequential codeposition of species with strongly differing surface mobilities, the nucleation and growth process depends strongly on the order of deposition [43,44]. If the less mobile species is deposited first, a higher density of NCs of that species is formed which provide nucleation centers during the second stage of deposition.…”

“…In addition, NCs formed in the first stage of deposition are mainly converted to two-component NCs. PIM have been implemented for these processes, also incorporating additional features described in (ix) below [44]. PIM can also readily treat the case of simultaneous codeposition.…”

Adsorption and diffusion of Ru adatoms on Ru(0001)-supported graphene: Large-scale first-principles calculations

“…Also, a "ridge" (dashed red line) is defined as separating fcc and hcp regions, and thus, the ridge joins two neighboring mound regions. Here, the "mound" region is also often described as the "atop" region, 5,3,7,13,14 while the "ridge" was previously described as the "fcc-hcp boundary" 7,13,14 or "bridge." 35 Table I lists our results for c G , c Ru , and d C-Ru from PBE GGA and PBE GGA+D2 methods with different k meshes.…”

“…7,12,13 The basic point is that definitive analysis of NC formation and its relationship to the underlying energetics requires kinetic Monte Carlo (KMC) simulation of a suitable stochastic atomistic-level model for the overall deposition, diffusion, and aggregation processes where the model must incorporate the local and coarse variation in binding and diffusion properties with at least a reasonable model PES. 7,14 Simplified modeling may however be viable in some regimes.…”