3D multi-physics modeling of a gas diffusion electrode for oxygen reduction reaction for electrochemical energy conversion in PEM fuel cells. (1st August 2016)

• Record Type: Journal Article
• Authors: Vasile, Nicolò S.; Doherty, Ronan; Monteverde Videla, Alessandro H.A.; Specchia, Stefania
• Is Part Of: Applied energy. Volume 175(2016)
• Page Start: 435
• Page End: 450
• Publication Date: 2016-08-01
• Subjects: 3D multi-physics modeling -- Gas diffusion electrode -- Oxygen reduction reaction -- Pt catalyst -- Fe–N–C catalyst -- Electrochemical energy conversion; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.04.030
• Languages: English
• ISSNs: 0306-2619

Abstract

Graphical abstract: Highlights: 3D multi-physics model of GDE for ORR computed by Comsol® v4.4a platform. Kinetic values obtained from experimental data by a semi-empirical model. Stokes–Brinkman and Maxwell–Stefan equations for gas transport in porous media. Porosity of GDL and CL included to account for oxygen diffusivity. Model validated against experimental data of Pt/C and Fe–N–C catalysts. Abstract: A 3D multi-physics, multi-component and not isothermal model is developed to analyze the effects of catalyst structures on the performance of a gas diffusion electrode (GDE) cell toward the oxygen reduction reaction using dry oxygen as a reactant. The model includes Stokes–Brinkman, Maxwell–Stefan, and modified Butler–Volmer equations for simulating the performance of the GDE cell, solved by Comsol® Multiphysics v4.4a platform. The model is validated against experimental data, showing congruent and convergent responses for different electrodes based on noble and non-noble metals catalysts, confirming the accuracy of the model and the equations applied. The use of a 3D model incorporating porous materials can be used for evaluating mass transport and diffusivity parameters of the electrocatalyst, identifying the controlling variable in the process. The model can be used as an optimization tool for further improvement of catalyst synthesis, suggesting which properties can be tuned to improve the overall performance in the catalyst design phase.