Electrified Nitrogen-Doped MXene Membrane Electrode for Micropollutants Decontamination Via Peroxymonosulfate Activation
ACS ES&T ENGINEERING(2023)
Abstract
Advanced oxidation processes based on peroxymonosulfate (PMS) activation have attracted tremendous attention as a promising approach for removing micropollutants. Herein, we designed a nitrogen-doped Ti3C2Tx MXene (N-Ti3C2Tx) electrocatalytic filtration system for the activation of PMS to efficiently and selectively degrade micropollutants. The system was configured for flow-through operation, which led to significant improvements in performance compared with a conventional batch reactor system because of the enhanced convective mass transfer. Specifically, a 90.8% removal of 0.04 mmol L-1 sulfamethoxazole (SMX) solution could be achieved in flow-through mode (k = 0.0173 +/- 0.0003 min(-1)) within 120 min under optimal conditions. This value was 4.7-fold higher than the conventional batch mode (k = 0.0037 +/- 0.0001 min(-1)). Radical quenching tests, electron paramagnetic resonance measurements, and electrochemical tests verified that SMX was degraded in the N-Ti3C2Tx/PMS filtration system primarily via nonradical pathways. Density functional theory calculations demonstrated that doping of N changed the PMS activation pathway and enhanced the ability of the N-Ti3C2Tx membrane electrode to transfer electrons. In the presence of inorganic anions or humic acids (15.0 mmol L-1), the SMX removal efficiency remained above 81.1%, illustrating that naturally occurring substances in water did not interfere with the system. This work demonstrates the capabilities of the N-Ti3C2Tx membrane electrode, which should provide beneficial improvements in systems targeting the serious issue of micropollutants in water.
MoreTranslated text
Key words
nitrogen doping,N-Ti3C2Tx membrane electrode,electro-PMS activation,nonradical pathway,water decontamination
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
APPLIED CATALYSIS B-ENVIRONMENT AND ENERGY 2024
被引用9
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
GPU is busy, summary generation fails
Rerequest