432401 Structure–Function Relationships for Graphene-Supported Pt Nanoclusters

Wednesday, November 11, 2015: 10:30 AM
355E (Salt Palace Convention Center)
Hongbo Shi, Chemical Engineering, Univeristy of Massachusetts, Amherst, Amherst, MA, Ashwin Ramasubramaniam, Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA and Scott M. Auerbach, Chemistry, University of Massachusetts, Amherst, MA

Platinum-based catalysts play an important role in energy conversion technologies, particularly, in hydrogen-based or methanol-based proton exchange membrane fuel cells (PAFC). Graphene-supported Pt nanoclusters were recently found to be promising catalysts due to their enhanced catalytic activity and tolerance to CO poisoning, as well as their long-term stability toward sintering. However, structure–function relationships that govern the improved electrocatalytic activity in these materials are still not well understood. . Here, we employ a combination of empirical potential simulations and density functional theory (DFT) calculations to investigate the structure–function relationships of small Ptn (n=2-80) clusters on model carbon (graphene) supports.. A Tersoff-Brenner style empirical potential, was employed within a Genetic Algorithm to investigate the global-minimum structures of Pt clusters in the size range of N=2-80 on pristine as well as defective graphene supports. Point defects in graphene strongly anchor Pt clusters and also appreciably affect geometries of small clusters, which we characterize via various structural metrics such as the gyration radius, average bond length, and average coordination number. Through selected ab initio studies, we find a consistent trend for charge transfer from Pt clusters to defective graphene supports resulting in the lowering of the cluster d-band center. This lowering of the cluster d-band center has been shown previously to result in weaker CO adsorption as well as reduced barriers for CO oxidation. By varying the cluster size, we also identify an optimal range of cluster sizes over which the support effect can play a role in modulating the activity of the cluster, thereby providing guidance for practical applications of graphene-supported Pt nanoclusters in electrocatalysis.

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See more of this Session: Fundamentals of Supported Catalysis I
See more of this Group/Topical: Catalysis and Reaction Engineering Division