A [Fe(bpy)3]2+ grafted graphitic carbon nitride hybrid for visible light assisted oxidative coupling of benzylamines under mild reaction conditions

2016 ◽  
Vol 18 (8) ◽  
pp. 2514-2521 ◽  
Author(s):  
Arvind Kumar ◽  
Pawan Kumar ◽  
Chetan Joshi ◽  
Srikanth Ponnada ◽  
Abhishek K. Pathak ◽  
...  
Keyword(s):  
Visible Light ◽  
Molecular Oxygen ◽  
Oxidative Coupling ◽  
Carbon Nitride ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
White Led ◽  
Reaction Conditions ◽  
Light Emitting

Iron(ii) bipyridine grafted on graphitic carbon nitride (Fe(bpy)3/npg-C3N4) was found to be an efficient photocatalyst for oxidative coupling of benzyl amines using molecular oxygen as an oxidant and a household white LED as a light emitting source.

scholarly journals Efficient Advanced Oxidation Process (AOP) for Photocatalytic Contaminant Degradation Using Exfoliated Metal-Free Graphitic Carbon Nitride and Visible Light-Emitting Diodes

Catalysts ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 662
Author(s):  
Adeem Ghaffar Rana ◽  
Minoo Tasbihi ◽  
Michael Schwarze ◽  
Mirjana Minceva
Keyword(s):  
Visible Light ◽  
Carbon Nitride ◽  
Photocatalytic Performance ◽  
Light Emitting Diodes ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Light Emitting ◽  
X Ray ◽  
Metal Free ◽  
Custom Made

The photocatalytic performance of metal-free graphitic carbon nitride (g-C3N4) was examined using visible light-emitting diodes (LEDs). A comparative and parametric study was conducted using the photocatalytic degradation of phenol as a model reaction. The g-C3N4 photocatalyst was synthesized from melamine using thermal condensation, followed by a thermal exfoliation that increases the catalyst surface area from 11 to 170 m2/g. Different characterization techniques, namely X-ray powder diffraction, X-ray photoelectron spectroscopy, nitrogen adsorption using the Brunauer–Emmett–Teller method, ultraviolet-visible (UV–vis) spectroscopy, transmission electron microscopy, photoluminescence spectroscopy (PL), and zeta potential analysis, were used to characterize the photocatalyst. A comparison of the photodegradation experiments conducted with a full-spectrum xenon lamp and a custom-made single-wavelength LED immersion lamp showed that the photocatalyst performance was better with the LED immersion lamp. Furthermore, a comparison of the performance of exfoliated and bulk g-C3N4 revealed that exfoliated g-C3N4 completely degraded the pollutant in 90 min, whereas only 25% was degraded with bulk g-C3N4 in 180 min because the exfoliated g-C3N4 enhances the availability of active sites, which promotes the degradation of phenol. Experiments conducted at different pH have shown that acidic pH favors the degradation process. The exfoliated g-C3N4 has shown high photocatalytic performance in the photodegradation of other phenolic compounds, such as catechol, m-cresol, and xylenol, as well.

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.

scholarly journals Electrostatic interaction mechanism of visible light absorption broadening in ion-doped graphitic carbon nitride

RSC Advances ◽  
2021 ◽  
Vol 11 (37) ◽  
pp. 22652-22660
Author(s):  
Zengyu Cen ◽  
Yuna Kang ◽  
Rong Lu ◽  
Anchi Yu
Keyword(s):  
Visible Light ◽  
Electrostatic Interaction ◽  
Light Absorption ◽  
Carbon Nitride ◽  
Interaction Mechanism ◽  
Graphitic Carbon ◽  
Electrostatic Attraction ◽  
Graphitic Carbon Nitride ◽  
Visible Light Absorption

H2O2 treated K-doped graphitic carbon nitride presents an enhanced visible light absorption, which is due to the electrostatic attraction between K ions and OOH ions inside graphitic carbon nitride.

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