4.8 Article

Tuning oxygen-containing groups of pyrene for high hydrogen peroxide production selectivity

期刊

APPLIED CATALYSIS B-ENVIRONMENTAL
卷 304, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.apcatb.2021.120908

关键词

Oxygen-containing groups; Organic molecules; Charge distribution; Electrocatalysts; Hydrogen peroxide

资金

  1. National Natural Science Foundation of China [22075157, 21805148]
  2. Outstanding Youth of Natural Science in Shandong Province [JQ201713]
  3. Key Research and Development Program of Shandong Province [2017GSF18128]
  4. Taishan Scholars Program [tsqn201909090]
  5. Open Research Fund of State Key Laboratory of Polymer Physics and Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences

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This study investigates the relationship between the structure and activity of oxygen-containing groups (OCGs) modified electrodes, and finds that asymmetrically local charge redistribution of these catalysts can promote oxygen reduction to hydrogen peroxide (ORHP) process.
Oxygen-containing groups (OCGs) modified carbon materials can affect the microstructure and chemical composition, which is important for oxygen reduction to hydrogen peroxide (ORHP). Thus, exploring the relationship between structure and activity of OCG-containing electrodes is of great significance. In this work, we synthesized OCGs modified pyrene-based organic molecules as electrocatalysts for ORHP. Their electrocatalytic performance are correlated with types and locations of the modified OCGs. Particularly, the Pyr-2OMe with better absorption of O-2 exhibits high H2O2 selectivity. DFT calculations reveal that the carbon atoms attached OCGs are the catalytic active sites. More importantly, the groups on one side of the molecules (Pyr-2OMe, Pyr2OH, and Pyr-2CO) with large dipole moments exhibit superior catalytic activity. Thus, for the first time we find that the asymmetrically local charge redistribution of these catalysts can promote ORHP process. This work paves an alternative way to supply constructive information for understanding the structure and selectivity correlations.

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