Autor: |
Andrew M. Herring, Arne Thaler, Chuloong (Christoph) Kim, Mei-Chen Kuo, Craig S Gittleman, Matthew Lindell, Michael A. Yandrasits, Ruichun Jiang |
Rok vydání: |
2020 |
Předmět: |
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Zdroj: |
ECS Meeting Abstracts. :2228-2228 |
ISSN: |
2151-2043 |
DOI: |
10.1149/ma2020-02352228mtgabs |
Popis: |
Proton exchange membranes (PEMs) are considered as the most promising material for fuel cell automobile applications due to their high proton conductivity and power density. The radical attacks with peroxide formation cause lower durability, which is a major challenge to further commercialize fuel cell vehicles. Cerium and manganese cations and oxides have been implemented as radical scavenging agents to overcome the challenge from radical attacks. However, the additives tend to not stay on the initial location but move during the operation due to migration and diffusion. The migration results in cluster formation and eventually the additives may dissolve and leave the membrane system. Our previous work modifying commercial fluroelastomers with chemically bonded polyoxometalate resulted in a membrane with radical scavenging properties while inhibiting additive clustering. Advancement in PEM durability with additives has implications not only for the light-duty fuel cell vehicles but also for medium and heavy-duty vehicles applications, which would aid the widespread of commercialization of fuel cell vehicles. This work focuses on characterizing the blended perfluorinated sulfonic acid (PFSA) ionomer membrane with the chemically bound radical scavenger to enhance the durability of the membrane. Proton conductivity of the membrane was characterized under controlled relative humidity and temperature with electrochemical impedance spectroscopy (EIS). Ionic Exchange capacity of two or more proton conductive sites was measured using titration method. Correlation between water uptake and membrane properties is discussed and measuring using dynamic vapor sorption (DVS). Thermal stability was investigated through thermalgravimetric analysis (TGA). |
Databáze: |
OpenAIRE |
Externí odkaz: |
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