Influence of Scattering Dynamics on Efficiency of Proton Exchange Membrane Fuel Cell

Abstract

The global demand for proton exchange membrane fuel cells (PEMFCs) is rapidly increasing due to their high efficiency, zero carbon emissions, and potential for sustainable energy conversion in transportation and power systems. Compared to internal combustion engines, gas engines, and turbine systems, PEMFCs demonstrate superior energy efficiency. However, achieving consistent and sustainable efficiency remains a key research challenge, driving numerous ongoing investigations. One crucial factor affecting PEMFC performance is heat management, as it significantly influences microscopic and macroscopic particle behavior near and surface of electrode. The present study focuses on analyzing the scattering dynamics of charge particle on the electrode surface (thermal electron) due to surrounding particles (thermal hydrogen) and their impact on PEMFC performance. The research comprises both theoretical and experimental approaches. Theoretically, a relationship was developed between the differential cross-section (DCS) and various PEMFC parameters, whereas the experimental work aimed to verify the proposed model. The results indicate that DCS decreases with increasing current density, whereas temperature rises with increasing output current. DCS also decreases with the scattering angle, reaches a minimum, and then increases again at different output voltages and efficiencies. Similarly, DCS increases with incident electron energy, attains a maximum, and then decreases as the energy continues to rise. In regions of smaller separation, DCS increases with separation at different voltages and efficiencies. Experimental results confirm that rising temperature reduces the cell's output voltage, verifying the theoretical inverse relationship between DCS and voltage. These findings contribute to enhancing PEMFC performance, supporting the application of advanced technologies such as scanning tunneling microscopy, laser-induced fluorescence, quantum computing, and nanophotonic sensors for improved efficiency and control.