scholarly journals A Contemporary Assessment on Composite Titania onto Graphitic Carbon Nitride-Based Catalyst as Photocatalyst

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Azami M. S. ◽  
Jalil A. A ◽  
Hitam C. N. C. ◽  
Mamat C. R ◽  
Siang T. J. ◽  
...  
Keyword(s):  
Band Gap ◽  
Carbon Nitride ◽  
Wide Band ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Electron Hole ◽  
Electronic Band ◽  
Metal Free ◽  
Physical And Chemical ◽  
Hole Recombination

Titanium dioxide (TiO2) has drawn widespread interest by researchers as a precious semiconductor that is responsive towards photodegradation of various pollutants. This catalyst has its own limitations such as fast electron-hole recombination, wide band gap, and can only be utilised under ultraviolet (UV) region. In order to overcome these problems, the addition of a metal-free dopant is a common practice to prevent electron-hole recombination and enhance photodegradation under visible light. Among various types of metal-free catalysts, carbon nitride material has received much attention due to its numerous benefits such as good in terms of physical and chemical strength, as well as an attractive electronic band combined with a band gap (2.7 eV). This review summarised recent works in the development of titania incorporated with graphitic carbon nitride (g-C3N4) for enhanced photocatalytic activity.

Co3O4/g-C3N4 Nanocomposites Prepared via Ultrasonication as Active Photocatalyst for H2 Generation Beneath Visible Light

2020 ◽  
Vol 12 (3) ◽  
pp. 285-295
Author(s):  
Maha Alhaddad ◽  
R. M. Navarro ◽  
M. A. Hussein ◽  
R. M. Mohamed
Keyword(s):  
Visible Light ◽  
Carbon Nitride ◽  
Hydrogen Generation ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Maximum Efficiency ◽  
Glycerol Solution ◽  
Electron Hole ◽  
H2 Generation ◽  
Hole Recombination

In this paper, we introduce an active photocatalyst for hydrogen generation from aqueous glycerol solution on nanoheterojunctions of graphitic carbon nitride (g-C3N4) and Co3O4 at various Co3O4 loading (1∼4 wt.%). The Co3O4 nanoparticulates were efficiently spread on the exterior of exfoliated mesoporous g-C3N4 by means of ultrasonication-mixture method that allowed the formation of effective Co3O4/g-C3N4 heterojunctions that minimized high recombination of charges observed on bare g-C3N4. The formation of nanoheterojunctions amid Co3O4 and g-C3N4 was demonstrated by XPS and HRTEM. Moreover, their number and efficiency in separation of charges depended on Co3O4 loading (maximum efficiency at 3 mol% of Co3O4). The optimal Co3O4/g-C3N4 nanocomposite demonstrated 22.5 and 33.7 times higher H2 production using visible light compared to the parent g-C3N4 and Co3O4 systems, respectively. The differences in photocatalytic action for the Co3O4/g-C3N4 composites was examined in terms of changes in their capacity to engross the light and to diminution the electron-hole recombination associated with different development of nanoheterojunctions in the composites.

Graphitic carbon nitride (g-C3N4) as a metal-free catalyst for thermal decomposition of ammonium perchlorate

RSC Advances ◽  
2015 ◽  
Vol 5 (31) ◽  
pp. 24507-24512 ◽  
Author(s):  
Qi Li ◽  
Yi He ◽  
Rufang Peng
Keyword(s):  
Thermal Decomposition ◽  
Band Gap ◽  
Valence Band ◽  
Ammonium Perchlorate ◽  
Conduction Band ◽  
Carbon Nitride ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Metal Free

g-C3N4 possesses a band gap of approximately 2.7 eV. The conduction-band electrons (ecb−) and valence band holes (h+) could be generated when g-C3N4 was excited, which accelerate the thermal decomposition of ammonium perchlorate (AP).

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.

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