The Active Facet of Copper and Its Alloy for Selective and Efficient Electrochemical Reduction of Nitrate to Ammonia
CURRENT OPINION IN GREEN AND SUSTAINABLE CHEMISTRY(2025)
City Univ Hong Kong | South China Univ Technol
Abstract
Electrochemical reduction of nitrate (NO3-) to ammonia (NH3) (the e-NO3RR) is one of the most widely discussed methods to remediate the NO3- concentrations found in industrial and agricultural wastewater. The growing importance of NH3 stems from its central role in fertilizer and advanced chemical production and as an emerging renewable hydrogen carrier due to its excellent hydrogen ratio and liquefiability. This review highlights how the active facets of copper (Cu), the most widely documented electrocatalyst for e-NO3RR, and its alloys transform NO3- to NH3. The literature findings on Faradaic efficiency and the NH3 formation rate in connection with the Cu facet, Cu oxide, and Cu alloys are discussed, followed by a discussion of the potential opportunities of the eNO3RR. We hope this review will provide helpful information to facilitate the design of the next generation of electrocatalysts.
MoreTranslated text
Key words
Electrochemical nitrate reduction,Ammonia synthesis,Active phase
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
Related Papers
2005
被引用175 | 浏览
2018
被引用563 | 浏览
2020
被引用1095 | 浏览
2020
被引用856 | 浏览
2020
被引用36 | 浏览
Alternative Route for Electrochemical Ammonia Synthesis by Reduction of Nitrate on Copper Nanosheets
2020
被引用263 | 浏览
2021
被引用190 | 浏览
2021
被引用229 | 浏览
2022
被引用469 | 浏览
2021
被引用36 | 浏览
2022
被引用50 | 浏览
2023
被引用222 | 浏览
2023
被引用10 | 浏览
2023
被引用113 | 浏览
2023
被引用69 | 浏览
Atomically Ordered PdCu Electrocatalysts for Selective and Stable Electrochemical Nitrate Reduction.
2023
被引用16 | 浏览
2024
被引用6 | 浏览
2024
被引用33 | 浏览
2024
被引用43 | 浏览
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