Ferrocene-Modified Carbon Nitride for Direct Oxidation of Benzene to Phenol with Visible Light

ChemSusChem ◽  
2014 ◽  
Vol 7 (3) ◽  
pp. 738-742 ◽  
Author(s):  
Xiangju Ye ◽  
Yanjuan Cui ◽  
Xinchen Wang
Keyword(s):  
Visible Light ◽  
Carbon Nitride ◽  
Direct Oxidation ◽  
Oxidation Of Benzene

scholarly journals Vanadium supported on graphitic carbon nitride as a heterogeneous catalyst for the direct oxidation of benzene to phenol

2016 ◽  
Vol 37 (11) ◽  
pp. 2003-2008 ◽  
Author(s):  
Cheng Wang ◽  
Liya Hu ◽  
Meiyin Wang ◽  
Yuanhang Ren ◽  
Bin Yue ◽  
...  
Keyword(s):  
Heterogeneous Catalyst ◽  
Carbon Nitride ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Direct Oxidation ◽  
Oxidation Of Benzene

scholarly journals Fabrication of AgCl/Ag3PO4/graphitic carbon nitride heterojunctions for enhanced visible light photocatalytic decomposition of methylene blue, methylparaben and E. coli

RSC Advances ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 6383-6394 ◽  
Author(s):  
Haishuai Li ◽  
Linlin Cai ◽  
Xin Wang ◽  
Huixian Shi
Keyword(s):  
Methylene Blue ◽  
Visible Light ◽  
Photocatalytic Degradation ◽  
Visible Light Irradiation ◽  
Carbon Nitride ◽  
Light Irradiation ◽  
Graphitic Carbon Nitride ◽  
Photocatalytic Decomposition ◽  
E Coli ◽  
Visible Light Photocatalytic

A noval ternary nanocomposite AgCl/Ag3PO4/g-C3N4 was successfully synthesized for photocatalytic degradation of methylene blue, methylparaben and inactivation of E. coli under visible light irradiation, showing excellent photocatalytic degradation performance and stability.

New carbon nitride close to C6N7 with superior visible light absorption for highly efficient photocatalysis

2021 ◽  
Author(s):  
Xinyu Zhao ◽  
Yingnan Zhao ◽  
Huaqiao Tan ◽  
Huiying Sun ◽  
Xing Qin ◽  
...  
Keyword(s):  
Visible Light ◽  
Light Absorption ◽  
Carbon Nitride ◽  
Visible Light Absorption ◽  
Highly Efficient

Amorphous Carbon Nitride with Three Coordinate Nitrogen (N3 C ) Vacancies for Exceptional NO x Abatement in Visible Light

2021 ◽  
pp. 2004001
Author(s):  
Youyu Duan ◽  
Yang Wang ◽  
Liyong Gan ◽  
Jiazhi Meng ◽  
Yajie Feng ◽  
...  
Keyword(s):  
Visible Light ◽  
Amorphous Carbon ◽  
Carbon Nitride ◽  
Amorphous Carbon Nitride

scholarly journals Prediction of Band Gap Energy of Doped Graphitic Carbon Nitride Using Genetic Algorithm-Based Support Vector Regression and Extreme Learning Machine

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 411
Author(s):  
Taoreed O. Owolabi ◽  
Mohd Amiruddin Abd Rahman
Keyword(s):  
Genetic Algorithm ◽  
Visible Light ◽  
Band Gap ◽  
Carbon Nitride ◽  
Activation Function ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Support Vector ◽  
Learning Machine ◽  
Photocatalytic Applications

Graphitic carbon nitride is a stable and distinct two dimensional carbon-based polymeric semiconductor with remarkable potentials in organic pollutants degradation, chemical sensors, the reduction of CO2, water splitting and other photocatalytic applications. Efficient utilization of this material is hampered by the nature of its band gap and the rapid recombination of electron-hole pairs. Heteroatom incorporation due to doping alters the symmetry of the semiconductor and has been among the adopted strategies to tailor the band gap for enhancing the visible-light harvesting capacity of the material. Electron modulation and enhancement of reaction active sites due to doping as evident from the change in specific surface area of doped graphitic carbon nitride is employed in this work for modeling the associated band gap using hybrid genetic algorithm-based support vector regression (GSVR) and extreme learning machine (ELM). The developed GSVR performs better than ELM-SINE (with sine activation function), ELM-TRANBAS (with triangular basis activation function) and ELM-SIG (with sigmoid activation function) model with performance enhancement of 69.92%, 73.59% and 73.67%, respectively, on the basis of root mean square error as a measure of performance. The four developed models are also compared using correlation coefficient and mean absolute error while the developed GSVR demonstrates a high degree of precision and robustness. The excellent generalization and predictive strength of the developed models would ultimately facilitate quick determination of the band gap of doped graphitic carbon nitride and enhance its visible-light harvesting capacity for various photocatalytic applications.

Photocatalytic degradation of tetracycline under visible light using TiO2@sulfur doped carbon nitride nanocomposite synthesized via in-situ method

2021 ◽  
Vol 9 (4) ◽  
pp. 105560
Author(s):  
Krishnan Divakaran ◽  
Amanulla Baishnisha ◽  
Vellaichamy Balakumar ◽  
Krishnan Nattamai Perumal ◽  
Chandran Meenakshi ◽  
...  
Keyword(s):  
Visible Light ◽  
Photocatalytic Degradation ◽  
Carbon Nitride ◽  
In Situ Method
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