WeChat Mini Program
Old Version Features

An Advanced 2D/3D G-C 3 N 4 /tio 2 @mno 2 Multifunctional Membrane for Sunlight-Driven Sustainable Water Purification

Nano Research(2024)

Cited 0|Views21
Abstract
Graphitic carbon nitride (g-C 3 N 4 ) nanosheets have attracted widespread interest in the construction of advanced separation membranes. However, dense stacking and a single functionality have limited the membrane development. Here, an advanced two-/three-dimensional (2D/3D) g-C 3 N 4 /TiO 2 @MnO 2 membrane is constructed by intercalating 3D TiO 2 @MnO 2 nanostructures into g-C 3 N 4 nanosheets. The 3D flower-like nanostructures broaden the transport channels of the composite membrane. The membrane can effectively separate five oil-in-water (O/W) emulsions, with a maximum flux of 3265.67 ± 15.01 L·m −2 ·h −1 ·bar −1 and a maximum efficiency of 99.69% ± 0.45% for toluene-in-water emulsion (T/W). Meanwhile, the TiO 2 @MnO 2 acts as an excellent electron acceptor and provides positive spatial separation of electrons–holes (e − –h + ). The formation of 2D/3D heterojunctions allows the material with wider light absorption and smaller bandgap (2.10 eV). These photoelectric properties give the membrane good degradation of three different pollutants, with about 100% degradation for methylene blue (MB) and malachite green (MG). The photocatalytic antibacterial efficiency of the membrane is also about 100%. After cyclic experiment, the membrane maintains its original separation and photocatalytic capabilities. The remarkable multifunctional and self-cleaning properties of the g-C 3 N 4 based membrane represent its potential value for complex wastewater treatment.
More
Translated text
Key words
graphitic carbon nitride (g-C3N4) based membrane,three-dimensional (3D) nanostructures,self-cleaning,multifunction
求助PDF
上传PDF
Bibtex
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