Investigating Influence of Palladium Metal Surface as a Component of Fuel Cells
12 Pages Posted: 30 May 2019
Date Written: May 1, 2019
Adsorptive studies focusing on palladium metal can model a situation in which some parts of platinum are replaced with palladium in a fuel cell, or some kind of PdPt alloy is used. Correspondingly thus, adsorptions of small molecules such as carbon monoxide and hydrogen are studied using density functional theory and the neural network method of generating higher dimensional potential energy surfaces. Various lower index surfaces of palladium metal are considered, and the adsorption energies appear to increase according to: Pd(110) Pd(211) > Pd(100) > Pd(111) with the adsorption of both molecules. The adsorption energies are in the range 0.79 eV to 1.86 eV with the adsorption of carbon monoxide while the values are between 0.93 eV to 1.76 eV with the adsorption of hydrogen. The large adsorption energies mean only energetic interactions with the ions from air such as oxygen ion can detach the adsorbates from the surface thereby forming water and carbon monoxide as by-products. Exploring possible adsorption sites gives insight on better ways in which charge exchanges are maximized while at the same time forming of the by-products becomes efficient. Charge transfers give some insight into the study of electrification process in the system. These values are computed to be about 1.06e with the adsorption of hydrogen and upto 0.90e with the adsorption of carbon monoxide. Training of the system potential energies using the neural network method shows promising opportunity to study further complex problems in such systems.
Keywords: neural networks, machine learning, density functional theory calculations, hydrogen, carbon monoxide, palladium, fuel cells
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