Models alloy surface composition

In the field of alloy surface composition, both theory and experimental determination achieved much progress in recent years. The present state of the art does not, unfortunately, allow one to predict quantitatively the surface composition from the bulk concentrations, but calculations on models allow one to estimate various effects and to make interesting conclusions and sometimes even semiquantitative predictions. 

Various pc electrode models have been tested.827 Using the independent diffuse layer electrode model74,262 the value of E n = -0.88 V (SCE) can be simulated for Cd + Pb alloys with 63% Pb if bulk and surface compositions coincide. However, large deviations of calculated and experimental C,E curves are observed at a 0. Better correspondence between experimental and calculated C,E curves was obtained with the common diffuse-layer electrode model,262 if the Pb percentage in the solid phase is taken as 20%. However, the calculated C, at a Ois noticeably lower than the experimental one. It has been concluded that Pb is the surface-active component in Cd + Pb alloys, but there are noticeable deviations from electrical double-layer models for composite electrodes.827... 

The study of model Ff alloy surfaces has been pioneered by the work of Ross and Markovic in fhe Unifed Sfafes, firsf af fhe Lawrence Berkeley National Laboratory and more recently at Argorme National Laboratory. A series of bulk FfgM (M = V, Ti, Fe, Co, Ni) alloy polycrysfalline maferials were prepared and fheir surfaces characferized by surface science fechniques. The composition of fhe surface was found to be dependenf on posftieatment. Surfaces sputtered with Ar ions showed compositions similar to the bulk, while surfaces fhaf had been annealed in vacuum showed stiong segregation of Ft to give Ft skins. 

Statistical thermodynamic descriptions of these transitions in substitutional alloys have been developed for the cases of both binary and ternary alloys , using a simple nearest neighbor bond model of the surface segregation phenomenon (including strain energy effects). Results of the model have been evaluated here using model parameters appropriate for a Pb-5at%Bi-0.04at%Ni alloy for which experimental results will be provided below. However, the model can be applied in principle to the computation of equilibrium surface composition of any ternary solution. 

What is dear from this introduction is that the journey into the area of metal deposition from ionic liquids has tantalizing benefits. It is also dear that we have only just begun to scratch the surface of this topic. Our models for the physical properties of these novel fluids are only in an early state of devdopment and considerably more work is required to understand issues such as mass transport, spedation and double layer structure. Nudeation and growth mechanisms in ionic liquids will be considerably more complex than in their aqueous counterparts but the potential to adjust mass transport, composition and spedation independently for numerous metal ions opens the opportunity to deposit new metals, alloys and composite materials which have hitherto been outside the grasp of electroplaters. 

The composition of an alloy surface is often very different than the alloy s bulk composition due to segregation effects. The overall activity of a catalyst is determined by the distribution of active sites. This distribution may be very heterogeneous both in terms of the local environments that define each site and their chemical reactivities. The reactivity of any specific active site can be affected by contributions from strain, ligand and ensemble effects. Computational methods are well suited to exploring these effects because one can simulate model systems where only one effect dominates as well as model systems where multiple effects are important. 

In Fig. 4 are reported the values of Pd surface composition as a function of the nominal bulk composition for (111) faces of fee Pd-X alloys (X = Ni, Pt, Cu, Ag and Au). These values have been calculated with the Equivalent Medium Approximation (EMA) model [7]. 

In deriving the above equation, the metallic alloy was treated as an ideal solution. In general, however, an alloy has a finite heat of mixing. Once this parameter is introduced into the model, it becomes clear that the surface composition is strongly dependent on the heat of mixing, its sign and its magnitude [40]. 

Fig. 3.1 UHV characterization of Pt Fe alloy (a) LEIS spectra during UHV treatment annealed and sputtered surfaces, (b) LEIS spectra red) after electrochemical treatment reveals dissolution of Fe atoms from the surface and formation of Pt-skeleton surface (c) UPS spectra (d) The d-band center position relative to the Fermi level from the valence band spectra measurements on PtjM alloy surfaces (red) and calculated values of d-band center position (blue), Schematic ball models for the sputtered surface and Pt-skin are included to help visuahze the structure and composition of Pt and M atoms in the near-surface regions. Reprinted with permission from [29], copyright 2007 Nature Pubhshing Group...

A model P4-18-SPM scanning tunneling microscope (NT-MDT, Russia) was employed to investigate the structure, in atmosphere, of nanometer-scale thin film materials and also to measure the thickness of the film. A setup [28] combining electrochemical studies and X-ray photoelectron spectroscopic (XPS) analysis served to characterize the surface composition of alloy films. 

At higher temperatures the contribution of the enthalpy term diminishes, leaving the entropy term, which yields a strong Pt enrichment as is shown in fig.8 with several literature data (10,22,24,26). The model by van Langeveld and Niemantsverdriet is qualitatively in good agreement with the experimental results for the temperature dependence of the surface composition. In a forthcoming publication we will further quantify the temperature dependence of the surface composition of Pt-Rh alloys (27). 

Surface Composition of Alloys from Model Calculations... 

The intrinsic exchange current density,/ , is not a mere materials constant, but it depends on size distributions of catalyst nanoparticles, their surface structure, as well as surface composition in the case of alloy catalysts like PtRu. In this section, we discuss modeling approaches that highlight particle size effects and the role of surface heterogeneity in fuel cell electrocatalysis. 

---