Computational Modelling of Surface Modified Carbon Nanotube for Low Temperature Fuel Cell

Abstract

For the advancement in performance of a PEMFC (Polymer Electrolyte Membrane Fuel Cell) it is seen that computational modelling plays a key role. It is observed that the fuel cell catalyst layer gives many challenges from a modelling standpoint. It comprises of a complex, multiphase nanostructured porous material which is difficult to characterize. Carbon nanotubes (CNTs) are excellent support structures for the anode catalyst layer because of their electrical, mechanical and thermal properties, as well as their huge application potential. Among different functionalization methods, ion irradiation has proven to be an exceptionally effective method for modifying and adapting the properties of CNTs, especially Multi-Walled Carbon Nanotubes (MWCNTs), by creating defects and adjusting the structure in a controlled manner. As functionalization by the irradiation technique is still undergoing intense development, the combination of new and optimized materials with high electrocatalytic activity and optimization of the conditions for this method is expected to lead to a significant increase in performance, efficiency and cost-effectiveness. Computational modelling makes it possible to systematically simulate and optimize functionalization conditions, which would facilitate the preparation of a new electrocatalytic material. Moreover, modelling of CNT functionalization gives in-depth understanding of the structure and transformation of CNTs upon ion irradiation. This model can be used to predict the electrocatalytic activity of an electrode like a function of physical characteristics as intrinsic activity of catalyst. This work exhibits computational modelling of a modified catalyst layer for a PEM fuel cell system by using MATLAB and PYTHON as programming languages.