Engineering Cu2O/Cu/N-C Interface to Induce Directional Migration of Charge for Driving Photocatalytic Homo-Coupling of Terminal Alkynes
NANO RESEARCH(2024)
Jiangsu Normal University
Abstract
The efficient utilization of visible light catalysts for organic reactions necessitates not only the effective separation of photogenerated electrons and holes to participate in the reaction, but also their ability to form key intermediates with reactant molecules. The present study successfully synthesized a crusiform-like mesoporous structure of nitrogen-doped carbon-coated Cu2O/Cu (Cu2O/Cu/N-C) with a Cu2O/dual electron acceptor interface using etched HKUST-1 as the precursor. A series of theoretical and experimental studies have demonstrated that the Cu2O/Cu/N-C interface in the photocatalytic homo-coupling of terminal alkynes not only effectively enhances the separation of photogenerated electron-hole pairs, but also facilitates the formation of the key intermediate [Cu2O/Cu/N-C]-phenylacetylide and promotes the rearrangement of its internal charges. As a result, the homo-coupling reaction can be effectively facilitated. The primary reason for the functional role of Cu2O/Cu/N-C interface lies in the downward bending of energy band from Cu2O to N-doped C layers, induced by the different work functions of Cu2O, Cu and N-doped C layers. Consequently, Cu2O/Cu/N-C photocatalysts demonstrate exceptional photocatalytic activity in the homo-coupling reaction of terminal alkynes under blue-light irradiation and air atmosphere. The present study presents a novel research methodology for the development of highly efficient visible light catalysts to facilitate organic reactions in future applications.
MoreTranslated text
Key words
photocatalysis,homo-coupling of terminal alkynes,directional migration of charges,heterojunction interface,Cu2O,carbon coated
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined