The Impact of Platinum Reduction on Oxygen Transport in Proton Exchange Membrane Fuel Cells

2014 ◽  
Vol 117 ◽  
pp. 367-378 ◽  
Author(s):  
Yosuke Fukuyama ◽  
Takeshi Shiomi ◽  
Toshikazu Kotaka ◽  
Yuichiro Tabuchi
2011 ◽  
Vol 158 (4) ◽  
pp. B416 ◽  
Author(s):  
Nobuaki Nonoyama ◽  
Shinobu Okazaki ◽  
Adam Z. Weber ◽  
Yoshihiro Ikogi ◽  
Toshihiko Yoshida

2018 ◽  
Vol 379 ◽  
pp. 338-343 ◽  
Author(s):  
Shunzhong Wang ◽  
Xiaohui Li ◽  
Zhaohui Wan ◽  
Yanan Chen ◽  
Jinting Tan ◽  
...  

2009 ◽  
Vol 21 (5) ◽  
pp. 673-692 ◽  
Author(s):  
Cristina Iojoiu ◽  
Jean-Yves Sanchez

This paper is a review that is focused on ionomers based on aromatic polysulfone backbone and intended to be used in proton exchange membrane fuel cells or in direct methanol fuel cells. Emphasis is placed on the different chemical routes to prepare the ionomers. Special attention is given to the impact of the ionomer structure on the conductivity performance and on the dimensional stability of the membranes at high temperatures.


2021 ◽  
Author(s):  
Mina Safe

Proton exchange membrane (PEM) fuel cells' main components are the anode, cathode and the membrane. A conventional membrane used in today's PEM fuel cells is the Nafion 117 membrane. In this project, the Nafion 177 membrane is discussed in detail to demonstrate its ability to absorb water and the capability to operate in a specific range of temperatures. In addition, an extensive simulation using CATIA V5 is used to determine the highest stress distribution on the membrane for various boundary conditions. Other membranes materials were also considered in this report. They include the Dias membrane, the bacterial cellulose membrane to expand the selection of candidate membranes that can be used im PEM fuel cells for future research. Optimization methods were utilized to maximize the performance of the PEM fuel cells. The Genetic Algorithm is used to solve optimization problems by implementing powerful search techniques to find an optimal solution within a large set of solutions. In this project, the Genetic Algorithm is used to show the impact of the stack positions in order to optimize voltage output. In addition, the Nafion content and platinum loading are adjusted to optimize the performance of the current density within PEM fuel cells.


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