(324d) Investigating the Dissolution of Platinum-Based Alloy Catalysts for Fuel Cells Using Kinetic Monte Carlo and Density Functional Theory Simulations

One of the most important challenges in low-temperature fuel cell technology is improving the catalytic efficiency, especially at the electrode-catalyst where the oxygen reduction reaction takes place. Platinum is the most popular catalyst for this reaction; however, it is expensive and scarce. Pt-based alloys are being studied to substitute platinum while maintaining the efficiency and life-time of the pure catalyst. Since the oxygen reduction reaction takes place in acid medium, both activity and durability of the catalyst are affected continuously while being exposed to such harsh environment. This work focuses on characterizing the dynamic evolution of the surface composition of platinum-based alloys under reaction conditions; specifically, we investigate the complex surface dynamics occurring in the near-surface layers influenced by adsorbates and alloy atoms which yields to the dissolution of the catalyst. The catalytic surface is characterized applying simulation methods that allow us to follow changes on its composition at the atomistic level, and at the same time to identify how those changes impact its activity and stability. During the fuel cell operation, oxygen is adsorbed on the cathode-catalyst surface. We have recently shown that its presence has a strong influence on the stability of the catalytic surface. The mechanisms of oxygen adsorption on catalytic alloy surfaces are complex and the presence of adsorbed oxygen affects the local composition of the surface, through the segregation phenomenon, as well as the stability of the catalyst with respect to metal dissolution in the electrolyte. Experiments and molecular simulations provide information about the possible microscopic states of the adsorbates involved in the reaction mechanism. Nevertheless, the connection between such microscopic states and the time evolution of the reaction rates and the changes in the local composition of the catalytic surface remains unexplained. Molecular dynamics simulations can provide the dynamic evolution of a real system if the potential gives a correct description of the atomic forces present in the modeled material. However, a serious limitation is that accurate integration of the equations of motion requires short enough time steps (~10^{- 15}s) to resolve the atomic vibrations. Thus, the total simulated time is usually limited to less than one microsecond whereas the steps involved in the complete surface reaction, including surface reconstruction and side reactions such as metal dissolution, may take place on much longer time scales. In order to overcome this problem, we implemented a coarse-grained 3-D Kinetic Monte Carlo method which utilizes the thermodynamic and kinetic information obtained from density functional theory (DFT) simulations. Hence, we are able to study the dynamic evolution of the surface composition of the catalytic alloy in long time scales, and under electrochemical conditions. This approach provides useful insight of the behavior of the alloy surface under reaction conditions and may contribute to the elucidation of the dissolution mechanisms giving firm guidelines for the design of improved catalysts.