On the underlying mechanisms of the low observed nitrate selectivity in photocatalytic NOx abatement and the importance of the oxygen reduction reaction

Literature Information

Publication Date 2017-11-27
DOI 10.1039/C7CP05960D
Impact Factor 3.676
Authors

Julia Patzsch, Andrea Folli, Donald E. Macphee, Jonathan Z. Bloh


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Abstract

Semiconductor photocatalysis could be an effective means to combat air pollution, especially nitrogen oxides, which can be mineralized to nitrate. However, the reaction typically shows poor selectivity, releasing a number of unwanted and possibly toxic intermediates such as nitrogen dioxide. Up to now, the underlying principles that lead to this poor selectivity were not understood so a knowledge-based catalyst design for more selective materials was impossible. Herein, we present strong evidence for the slow oxygen reduction being one the causes, as the competing back-reduction of nitrate leads to the release of nitrogen dioxide. Consequently, engineering the photocatalyst for a better oxygen reduction efficiency should also increase the nitrate selectivity.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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