Cooperative Coupling Strategy for Constructing 0D/2D Carbon Nitride Composites with Strengthened Chemical Interaction for Enhanced Photocatalytic Applications

2021 ◽  
pp. 134075
Author(s):  
Kunqiao Li ◽  
Yanqiu Jiang ◽  
Wei Rao ◽  
Yudong Li ◽  
Xing Liu ◽  
...  
Keyword(s):  
Carbon Nitride ◽  
Chemical Interaction ◽  
Coupling Strategy ◽  
Photocatalytic Applications

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.

Rational nanostructure design of graphitic carbon nitride for photocatalytic applications

2019 ◽  
Vol 7 (19) ◽  
pp. 11584-11612 ◽  
Author(s):  
Na Tian ◽  
Hongwei Huang ◽  
Xin Du ◽  
Fan Dong ◽  
Yihe Zhang
Keyword(s):  
Carbon Nitride ◽  
Review Article ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Comprehensive Overview ◽  
Photocatalytic Applications

This review article provides a comprehensive overview of the nanostructure design of g-C3N4 with various dimensional structures and promising applications.

Construction of functional nanonetwork-structured carbon nitride with Au nanoparticle yolks for highly efficient photocatalytic applications

2018 ◽  
Vol 54 (52) ◽  
pp. 7159-7162 ◽  
Author(s):  
Kunyi Leng ◽  
Weicong Mai ◽  
Xingcai Zhang ◽  
Ruliang Liu ◽  
Xidong Lin ◽  
...  
Keyword(s):  
Carbon Nitride ◽  
Au Nanoparticle ◽  
Highly Efficient ◽  
Photocatalytic Performances ◽  
Photocatalytic Applications

Functional nanonetwork-structured carbon nitride with Au nanoparticle yolks was successfully fabricated, and demonstrated excellent photocatalytic performances.

Porous graphitic carbon nitride for solar photocatalytic applications

2020 ◽  
Vol 5 (5) ◽  
pp. 765-786 ◽  
Author(s):  
Yang Li ◽  
Xin Li ◽  
Huaiwu Zhang ◽  
Quanjun Xiang
Keyword(s):  
Carbon Nitride ◽  
Porous Graphitic Carbon ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Comprehensive View ◽  
The Future ◽  
Morphology Modification ◽  
Photocatalytic Applications

This review summarizes the development of PCN, i.e., synthesis, morphology, modification, and application in recent years. This review can provide a comprehensive view of PCN and lay a foundation for the design of ideal photocatalysts in the future.

scholarly journals Doping of Graphitic Carbon Nitride with Non-Metal Elements and Its Applications in Photocatalysis

Catalysts ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1119
Author(s):  
Halyna Starukh ◽  
Petr Praus
Keyword(s):  
Organic Contaminants ◽  
Carbon Nitride ◽  
Co2 Reduction ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Metal Elements ◽  
A Charge ◽  
Application Fields ◽  
Photocatalytic Applications ◽  
Charge Carrier Lifetime

This review outlines the latest research into the design of graphitic carbon nitride (g-C3N4) with non-metal elements. The emphasis is put on modulation of composition and morphology of g-C3N4 doped with oxygen, sulfur, phosphor, nitrogen, carbon as well as nitrogen and carbon vacancies. Typically, the various methods of non-metal elements introducing in g-C3N4 have been explored to simultaneously tune the textural and electronic properties of g-C3N4 for improving its response to the entire visible light range, facilitating a charge separation, and prolonging a charge carrier lifetime. The application fields of such doped graphitic carbon nitride are summarized into three categories: CO2 reduction, H2-evolution, and organic contaminants degradation. This review shows some main directions and affords to design the g-C3N4 doping with non-metal elements for real photocatalytic applications.

Graphitic Carbon Nitride‐Based Low‐Dimensional Heterostructures for Photocatalytic Applications

Solar RRL ◽  
2019 ◽  
Vol 4 (8) ◽  
pp. 1900435 ◽  
Author(s):  
Muhammad Shuaib Khan ◽  
Fengkai Zhang ◽  
Minoru Osada ◽  
Samuel S. Mao ◽  
Shaohua Shen
Keyword(s):  
Carbon Nitride ◽  
Graphitic Carbon ◽  
Graphitic Carbon Nitride ◽  
Low Dimensional ◽  
Photocatalytic Applications
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