Some interpretations of surface vibrational spectroscopy pertinent to fuel-cell electrocatalysis

Abstract

Some applications of vibrational spectroscopy for characterizing chemisorbates of relevance to fuel-cell technology are examined, with particular reference to the fundamental interpretation in terms of interfacial structure and bonding. The central role of the surface potential in controlling vibrational properties is illustrated by examining chemisorbed CO in corresponding electrochemical and ultrahigh vacuum-based interfaces. Some new-found opportunities for the quantum-chemical understanding of potential-dependent chemisorbate bonding by using density functional theory (DFT) are briefly discussed, specifically the connections between vibrational frequencies, binding energetics, and surface charge polarization, and the insight into specific orbital and other interactions that can be furnished by finite-cluster calculations. Related adsorptive and electrocatalytic properties of carbon-supported Pt nanoparticle films are described, prompted by the applicability of such materials in fuel cells. The infrared characterization of size-dependent nanoparticles by using chemisorbed CO as a structural probe indicates a sharply increasing proportion of edge versus terrace Pt sites for particle diameters below 4 nm, in accordance with simple atom-packing considerations. The qualitatively different dependence of the electrocatalytic properties of such films on the nanoparticle diameter for methanol and formic acid oxidation is interpreted in terms of an ‘ensemble effect’, whereas the availability of contiguous terrace sites (apparently required for the former but not the latter process) is curtailed for small particle diameters. Finally, the value of DFT as a means of predicting infrared absorbances and Raman scattering intensities by evaluating the dynamic dipole moment and its field dependence (i.e. the dynamic polarizability), respectively, is illustrated for adsorbates of interest in fuel-cell electrocatalysis, and compared with experimental data.