Donor−π−Acceptor Conjugated Polymeric Photocatalyst for Efficient Deep Oxidation of NO Facilitated by Strong Asymmetric Local Electric Field

Abstract Photocatalytic conversion of low‐concentration NO x into NO 3 − is limited by strong exciton effects, rapid recombination of photogenerated charge carriers, and lack of localized bonding sites of oxygen species in catalysts. Directed enrichment of charge carriers and reactants (O 2 and NO) at active sites is essential for achieving high‐performance photocatalytic NO removal. Herein, a donor–π–acceptor (D–π–A) conjugated polymeric catalyst was engineered by covalently incorporating ultrathin carbon nitride nanosheets with electron‐donating π–pyrene–π molecules, which achieves an exceptional 82.2% NO elimination and 94.9% selectivity toward ionic products (NO 3 − sel. of 75.9%) with stable operation over 1000 mins, outperforming the previously reported carbon nitride photocatalysts. Rapidly reduces NO levels below safe concentration in a simulated environment chamber was also achieved. The generated asymmetric local electric field in D–π–A conjugated polymeric catalyst through intramolecular charge transfer between electron‐accepting heptazine rings and electron‐donating pyrene units facilitates exciton dissociation, accelerating charge transfer kinetics, and offer dual adsorption sites for capture O 2 and NO, thus favoring the O 2 activation for highly selective oxidization of NO to NO 3 − . This work highlights the pivotal role of asymmetric local electric fields in D–π–A architectures for advancing efficient photocatalytic NO oxidation.

Authors

Institutions

Publication Details

Journal
Angewandte Chemie
Published
2025-10-13
DOI
https://doi.org/10.1002/ange.202518300
Primary Topic
Advanced Photocatalysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Donor−π−Acceptor Conjugated Polymeric Photocatalyst for Efficient Deep Oxidation of NO Facilitated by Strong Asymmetric Local Electric Field

Kui Li, Mingshan Zhu, Jingling Yang, Yangsen Xu et al.
Angewandte Chemie
Advanced Photocatalysis Techniques
article

Donor−π−Acceptor Conjugated Polymeric Photocatalyst for Efficient Deep Oxidation of NO Facilitated by Strong Asymmetric Local Electric Field

Kui Li, Mingshan Zhu, Jingling Yang, Yangsen Xu, Jiangping Tu, Mingmei M. Wu, Zhijian Xiao
article en

Abstract

Abstract Photocatalytic conversion of low‐concentration NO x into NO 3 − is limited by strong exciton effects, rapid recombination of photogenerated charge carriers, and lack of localized bonding sites of oxygen species in catalysts. Directed enrichment of charge carriers and reactants (O 2 and NO) at active sites is essential for achieving high‐performance photocatalytic NO removal. Herein, a donor–π–acceptor (D–π–A) conjugated polymeric catalyst was engineered by covalently incorporating ultrathin carbon nitride nanosheets with electron‐donating π–pyrene–π molecules, which achieves an exceptional 82.2% NO elimination and 94.9% selectivity toward ionic products (NO 3 − sel. of 75.9%) with stable operation over 1000 mins, outperforming the previously reported carbon nitride photocatalysts. Rapidly reduces NO levels below safe concentration in a simulated environment chamber was also achieved. The generated asymmetric local electric field in D–π–A conjugated polymeric catalyst through intramolecular charge transfer between electron‐accepting heptazine rings and electron‐donating pyrene units facilitates exciton dissociation, accelerating charge transfer kinetics, and offer dual adsorption sites for capture O 2 and NO, thus favoring the O 2 activation for highly selective oxidization of NO to NO 3 − . This work highlights the pivotal role of asymmetric local electric fields in D–π–A architectures for advancing efficient photocatalytic NO oxidation.

Angewandte ChemieVol. 137(50)
Sun Yat-sen University (CN), Shenzhen Institute of Information Technology (CN), Jinan University (CN)
Openalex Percentile: Top 81%
Advanced Photocatalysis Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.