EPR spectroscopic investigation of radical-induced degradation of partially fluorinated aromatic model compounds for fuelcell membranes

Literature Information

Publication Date 2009-05-12
DOI 10.1039/B817070C
Impact Factor 3.676
Authors

Frank Schönberger, Jochen Kerres, Herbert Dilger, Emil Roduner


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Abstract

EPR spectroscopic investigations of reactions between monomeric model compounds representing typical structural moieties of poly(aryl) ionomers and photochemically generated hydroxyl radicals are reported. Deoxygenated solutions of the model compounds (in a water/methanol mixture) containing hydrogen peroxide at defined pH values were exposed to UV light in the flow cell within the cavity of an EPR spectrometer. Spectra were analyzed by computer simulation and the formed radicals were assigned by comparing their g-factors and hyperfine coupling constants (hfccs) with those from the literature and from density functional theory (DFT) calculations. The relevance for polymer electrolyte membrane fuel cells (PEMFCs) and alkaline-anion exchange membrane fuel cells (AAEMFCs) is discussed.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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