(307h) Global Optimization and Hydrogen Adsorption on Pt-Cu Clusters By Using Genetic Algorithm and Density Functional Theory

Bimetallic transition-metal (TM) nanoparticles (NPs) can provide enhanced high activity, selectivity and good long-term stability compared to their pure counterparts in a wide range of technological applications especially for the the development of low-cost and high-performance industrial polymer electrolyte fuel-cell (PEMFC) catalysts. Platinum (Pt) has been used as a superior catalyst for hydrogen oxidation (HOR) and oxygen reduction (ORR) reactions which are the most in a fuel cell. Since the limited amount of Pt reserves and its high cost for fuel cell aplications have led to a strong demand for reducing the use of Pt. For this purpose, Pt alloyed catalysts such as Pt-Co, Pt-Ni, Pt-Cu have been studied to effectively improve both the kinetics of the catalytic reactions and utilization of Pt while reducing the expense of catalyst. In our case, copper (Cu) has been used as a second metal to improve catalytic behaviour due to the one of the most active Pt alloyed catalysts that has been developed over the past decade is the PtCu for use as electrocatalysts in PEMFC [1,2]. Previous studies showed that the particle morphology and elemental compositions of these nanoparticles plays a very important role in how a particular catalytic cycle proceeds. Moreover, the determination of the most stable structure of these nanoparticles is a crucial step for understanding their catalytic properties and designing as a catalyst for a possible industrial application. In the first part of the study, we investigated the morphology of Pt-Cu clusters with the diameter less than 1 nm (about 2-50 atoms) then we analyzed their geometries and; finally, we characterized the electronic structures by advanced computational chemistry methods with the aim to obtain atomistic understanding of the physical and chemical properties of bimetallic TM clusters. The prediction of energetically stable structures is regarded as a highly complex problem of global optimization. One of the most effective global optimization approach for finding the structure of a cluster with the minimum energy level is Density Functional Theory (DFT) which allows a close connection between theory and experiment and often leads to important clues about the geometric, electronic and spectroscopic properties of the systems being studied. Essential part of working under DFT environment is the identifying initial structure of cluster qualitatively because of feeding locally optimized structures rather than randomly arranged structures to DFT, reduces processing time and provides energetically stable clusters at global minima. For this purpose, Genetic Algorithm (GA) coupled with Gupta potential which is based on second moment approximation to tight binding theory were conducted to obtain a set of locally optimized structures for the equally weighted Pt-Cu bimetallic clusters in the range of between 2-50 atoms, all possible compositions of Pt-Cu of 10 atoms, and monometallic Pt and Cu optimized structures of 20 atoms. GA was used to solve a series of attractive and repulsive potential energy equations and find which morphology gives a minimum potential. The energy scaling parameters for Gupta potential which are A, ð??, p and q describing heteronuclear Pt-Cu interactions, were obtained by taking weighted averages of these parameters for pure bulk Pt and Cu metals [3]. The performance of GA prediction was tested for Cu-Au TM clusters which have optimized structures and exact potential energy values are available in literature [4]. Several GA runs agreed well with previous reports and the performance of GA prediction generally was better than the previous studies for different TM systems. Very interestingly and for the first time, the optimized structures and exact potential energy values for PtCu clusters was represented by using semi-empricial Gupta potential in GA environment more quantitatively. Then, the lowest energy structures which were found empirically were reoptimised bu using quantum-mechanical calculations at the ab-initio DFT level (first principles). DFT calculations were carried out using Gaussian 09 quantum chemistry simulation package within a LANL2DZ basis, and B3PW91 exchange correlational functional (Becke Three Parameters Hybrid Function). The structural motifs calculated by Gupta potential, as a function of composition and weighted parameters, were similar with structures obtained by DFT but the distances and places of certain atoms were slightly different. To further the understanding of the structural and energetic properties of the bimetallic Pt-Cu clusters which were optimized in both GA and DFT, we calculated a large number of properties, namely, excess and binding energy, effective coordination number, average weighted bond lengths, chemical order, detachment energy and ionization potential. To obtain a better understanding of the electronic and magnetic properties of PtCu clusters radial distribution functions, energy separation between the lowest unoccupied molecular orbitals (LUMO) and the highest occupied molecular orbitals (HOMO) and their magnetic moment properties have been still studying in details. The excess energy presents negative values while binding energy is positive for all PtCu compositions and these result provide a strong evidence that the optimized structures of binary PtCu is an energetically favourable. The most stable configuration of a binary cluster was found as a Pt₃Cu₇. The structures predicted by combination of GA and DFT are randomly chemically disordered structures as minimum energy states with no apparent segregation of a particular species either to the core or to the surface. In the second part of the study, hydrogen adsorption properties in a particular 10-atom bimetallic PtCu models have been studied to investigate how hydrogen interacts with Ptâ??Cu clusters for improving our understanding of the factors determining the HOR activity. Firstly, initial bimetallic Pt-Cu clusters which was globally optimized was obtained from DFT results. Then, all possible adsorption sites which are bridge, top and hollow for both Pt and Cu atoms in the optimized clusters was investigated before doing any hydrogen adsorption analysis on a well defined surface. Hydrogen adsorption was carried out in Gaussian 09 program package by using the same procedure which was represented in the optimization part. We investigated the hydrogen adsorption energies on pure Pt₁₀ and Cu₁₀ clusters in different sites and also for a Pt₃Cu₇ cluster which was most stable composition of 10 atoms. We obtained that adsorption energies takes negative values for all optimized cluster models. More negative adsorption energy indicates the stronger the adsorption since the adsorption energy measures the magnitude of the binding energy of the species to the cluster. Our preliminary results indicates that Pt₃Cu₇ cluster have more negative adsorption energy when it was compared with pure Pt₁₀ and Cu₁₀ clusters. Based on our calculations, the most favorable adsorption site for Pt₁₀ is located at the top site and for Cu₁₀ is located at the bridge site. For the case of bimetallic Pt₃Cu₇, the hollow site are more favorable for both Pt and Cu atoms but Pt-hollow site is more energetically favorable according to its adsorption energy calculations. This result indicates that H atoms show a preference for Pt atoms in bimetallic clusters.

References

[1] Mani P, Srivastava R and Strasser P. J. Phys Chem C 2008;112:2770-8

[2] Oezaslan M and Strasser P, J. Power Sources 2011;196;5240-9

[3] L. O. Paz-Borbo´n, , A. Gupta and R. L. Johnston, J. Mater. Chem., 2008, 18, 4154â??4164

[4] S. Darby, T. V. Mortimer-Jones, R. L. Johnston, and Christopher Roberts, J. Chem. Phys., Vol. 116, No. 4, 22 January 2002