scholarly journals Alkaline salt-promoted construction of hydrophilic and nitrogen deficient graphitic carbon nitride with highly improved photocatalytic efficiency

2021 ◽  
Author(s):  
Hao Chen ◽  
Wuyou Wang ◽  
Zhenzhen Yang ◽  
Xian Suo ◽  
Ziyang Lu ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Visible Light ◽  
Carbon Nitride ◽  
Graphitic Carbon ◽  
Charge Carriers ◽  
Graphitic Carbon Nitride ◽  
Photocatalytic Efficiency ◽  
Alkaline Salt ◽  
Practical Applications

Graphitic carbon nitride possesses fascinating merits, but its practical applications are limited by the inferior properties of limited visible-light sorption, rapid recombination of photo-excited charge carriers and low electrical conductivity.

Graphitic Carbon Nitride-Titanium Dioxide Nanocomposite for Photocatalytic Hydrogen Production under Visible Light

2016 ◽  
Vol 14 (4) ◽  
pp. 851-858 ◽  
Author(s):  
Mohammad Reza Gholipour ◽  
Francois Béland ◽  
Trong-On Do
Keyword(s):  
Hydrogen Production ◽  
Visible Light ◽  
Carbon Nitride ◽  
Fossil Fuels ◽  
Clean Energy ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Conduction Band Edge ◽  
Photocatalytic Efficiency ◽  
Photocatalytic Reactions

Abstract Hydrogen production from water splitting via photocatalytic reactions can be an alternative clean energy of fossil fuels in the future. Graphitic carbon nitride (g-C3N4) is one of the active photocatalysts in the visible light region that can be combined with other semiconductors in order to increase its photocatalytic efficiency. TiO2 is one of the most appropriate choices to combine with g-C3N4 because of its conduction band edge and variety forms of nanostructures. In this work, nanosheets of g-C3N4 were mixed with the nanoparticles of titanate in order to enhance charge separation and photocatalytic efficiency. Consequently, the hydrogen evolution of this novel nanocomposite produced almost double hydrogen in comparison with g-C3N4.

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.

Linking Melem with Conjugated Schiff-Base Bond to Boost Photocatalytic Efficiency of Carbon Nitride for Overall Water Splitting

Nanoscale ◽  
2021 ◽  
Author(s):  
Hu Liu ◽  
Mengqi Shen ◽  
Peng Zhou ◽  
Zhi Guo ◽  
Xinyang Liu ◽  
...  
Keyword(s):  
Schiff Base ◽  
Visible Light ◽  
Water Splitting ◽  
Visible Light Irradiation ◽  
Carbon Nitride ◽  
Light Irradiation ◽  
Graphitic Carbon Nitride ◽  
Photocatalytic Efficiency ◽  
Metal Free ◽  
Overall Water Splitting

Developing an efficient single component photocatalyst for overall water splitting under visible-light irradiation is extremely challenging. Herein, we report a metal-free graphitic carbon nitride (g-CxN4)-based nanosheet photocatalyst (x = 3.2,...

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