Hydrogen storage on LaNi5−xSnx. Experimental and phenomenological Model-based analysis

Abstract

Three hydride-forming metals (LaNi5, LaNi4.73Sn0.27, and LaNi4.55Sn0.45) have been studied as solid phase hydrogen storage material in batch experiments using pure hydrogen and temperatures ranging from 300 K to 340 K. This process mainly involves: physisorption of hydrogen gas molecules; chemisorption and dissociation of hydrogen molecules; surface penetration of hydrogen atoms; hydride formation; and diffusion of hydrogen atoms through hydride-forming metal. In case the material is fully hydrided, hydride formation ceases and diffusion proceeds on the fully hydrided material. A phenomenological model was developed by aggregating the first four mechanisms in a single sorption kinetic term involving a first-order driving force, the remaining mechanism being the atomic diffusion in the hydride-forming material. The driving force is computed between external partial pressure and equilibrium pressure according to the Pressure-Composition-Temperature model (PCT). The corresponding parameters for an empirical PCT were estimated from equilibrium data. This equation is more suitable for process engineering optimization due to the smoothness in its concentration domain. Specific sorption rate and diffusion coefficients of the process were also estimated from dynamic data. From a sensitivity analysis, productivity proved to be related to particle diameter. In the frame of batch processes, the global rate is dominated by the sorption kinetic term at the beginning of the experiments with the material being free from hydride, whereas with more than 5?10% of the material being hydrided, diffusion dominates the process. LaNi5 shows higher hydrogen storage capacity than LaNi4.73Sn0.27 and LaNi4.55Sn0.45 within the investigated temperature and pressure ranges. Diffusion and sorption kinetic limited regions were identified from a sensitivity analysis of process productivity and normalized marginal values. The present work is oriented to modeling, designing, and optimizing storage and purification devices.