Catalyst-support interactions are essential in the design of materials for a variety of applications related to renewable energy technologies. In the fuel cell field, improved understanding of these interactions enables controlled improvement in the catalytic activity and durability of carbon-supported fuel cell electrocatalysts. Carbon surface chemistry and structure can be altered to achieve a desired coverage, morphology and composition of the metal nanophase. For example, doping a model HOPG surface with argon or nitrogen results in structural and chemical modification of its surface that leads to improved dispersion, decreased nanoparticle phase and, at certain conditions, enhanced stability. In this work, the role of surface defects, oxygen and nitrogen groups introduced during doping and their effect on electrocatalyst deposition and performance is evaluated through a combination of spectroscopic (XPS, Raman, EELS) and microscopic (SEM, TEM) methods. The same methods are used to evaluate the effect of various surface modifications (via Ar plasma, O₂ plasma and their mixture, HNO₃, TMA functionalization, etc.) on high surface area carbon materials (CNTs, for instance) and their effect on nucleation and growth of Pt in a controlled nanoparticle or continuous coating phase.

Understanding the chemical structure and morphology of Pt electrocatalysts and their supports, and linking these parameters to electrocatalytic activity, corrosion stability and overall performance of the fuel cell is essential for elucidation of failure mechanisms and optimization of support properties. The strategy presented in this work can be viewed as universal methodology that allows correlation between multiple variables relevant to fuel cell technology.

In this work we have investigated the performance and corrosion stability of Pt electrocatalysts supported on different carbon supports in order to understand the effect of the carbon support on catalyst degradation. Low surface area (LSA), mid-range surface area (MSA), high surface area (HSA) and heat treated (to induce graphitization) high surface area carbons were extensively studied and characterized.

X-ray Photoelectron Spectroscopy (XPS) has been chosen to obtain information on graphiticity and amount of surface oxides on carbon supports. The ability to discriminate between different carbon chemical environments, not just elemental compositions, is one of the primary advantages of XPS in the characterization of carbon corrosion.

Morphological properties such as size of particles, size of particles agglomerates, surface area, roughness and porosity are equally contributive to corrosion process. Digital Image Processing (DIP) can be applied to SEM and TEM images to extract statistical parameters, such as roughness, particle size distributions, shape parameters, texture parameters, which all are related to morphology of carbon blacks.

Performance and durability of Pt electrocatalysts supported on various carbon blacks were evaluated extensively electrochemically to provide activity from rotating disk electrode measurements, capacitance and photon resistance from Electrode Impedance Spectroscopy, voltage degradation rates, effective platinum surface area and kinetic losses.

This multi-analytical approach provides a large set of variables (structural, physical and microscopic properties) which must be related to corrosion and performance behaviour of carbon blacks. Multivariate statistical methods of data analysis (MVA) become, thus, of critical importance in structure-to-property relationship modeling. Principal Component Analysis (PCA) is used as a visualization tool to find samples which are globally correlated or anti-correlated, and to facilitate visualization of the variables responsible for the correlations. Through this methodology, we have determined which set of structural and morphological parameters are responsible for durable and active electrocatalyst.

In order to meet the challenges of more economical and environmentally benign energy production, a new generation of complex materials and devices is being developed, these include thin film solar cells, fuel cells, and batteries. In all stages of development there is a requirement for materials characterization and analysis; from the initial development stages, through to testing of the finished article. Most materials need to be analyzed for compositional homogeneity across the sample surface and also for layer chemistry, interface chemistry and thickness through the sample. It is rare that a single technique can achieve all of these testing requirements, and therefore a complementary approach involving several techniques is demanded.

In this presentation we will discuss how a multi-technique approach can address a variety of technical problems, illustrated by examples from real applications case studies. We will mainly concentrate on the information supplied from two techniques, XPS and EDS, but we will also consider the additional data that can be obtained from other sources such as Raman spectroscopy.

X-ray photoelectron spectroscopy (XPS) is ideally suited to the quantitative determination of the surface chemistry and the way in which that chemistry changes in the surface, near-surface and interface region of the materials.

Energy Dispersive Spectroscopy (EDS) collects characteristic X-rays generated by rastering an electron beam over a solid sample to generate a full elemental X-ray spectrum at each pixel of the electron image. The latest generation silicon drift detectors for EDS are capable of collecting and storing hundreds of thousands of X-ray counts per second. This large volume of X-ray data, collected across the sample, allows for rapid identification and characterization of surface defects and lateral compositional variations. Software advances now allow rapid, multivariate statistical analysis processing of very limited amounts of X-ray data to determine not only the elemental distribution across the sample but also the chemical phase distribution.