PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 19, 2024Angewandte Chemie International Edition100 citations

Constructing Donor‐Acceptor Covalent Organic Frameworks for Highly Efficient H2O2 Photosynthesis Coupled with Oxidative Organic Transformations

View Full Paper
JLJianchuan LiuCTChao TuoWXWei-Yun Xiao

Key Points

Key points are not available for this paper at this time.

Abstract

The development of photocatalytic systems that enable the simultaneous production of H2O2 and value‐added organic chemicals presents a dual advantage: generating valuable products while maximizing the utilization of solar energy. Despite the potential, there are relatively few reports on photocatalysts capable of such dual functions. In this study, we synthesized a series of donor‐acceptor covalent organic frameworks (COFs), designated as JUC‐675 to JUC‐677, to explore their photocatalytic efficiency in the co‐production of H2O2 and N‐benzylbenzaldimine (BBAD). Among them, JUC‐675 exhibited exceptional performance, achieving a H2O2 production rate of 22.8 mmol g−1 h−1 with an apparent quantum yield of 15.7%, and its solar‐to‐chemical conversion efficiency was calculated to be 1.09%, marking it as the most effective COF‐based photocatalyst reported to date. Additionally, JUC‐675 demonstrated a high selectivity (99.9%) and yield (96%) for BBAD in the oxidative coupling of benzylamine. The underlying reaction mechanism was thoroughly investigated through validation experiments and density functional theory (DFT) calculations. This work represents a significant advancement in the design of COF‐based photocatalysts and the development of efficient dual‐function photocatalytic platforms, offering new insights and methodologies for enhanced solar energy utilization and the synthesis of value‐added products.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Liu et al. (2024) studied this question.

synapsesocial.com/papers/68e57fadb6db64358751d17ehttps://doi.org/10.1002/anie.202416240
Ask AI
Helpful
Bookmark
Share
View Full Paper