Published November 2019 | Version v1
Journal article

g-C3N4/oxygen-deficient BiOCl nanocomposite assisted by distinguished properties of graphene quantum dots for the efficient photocatalytic removal of organic vapors

  • 1. Department of Environmental Engineering, Kyungpook National University, 80 University Road, Bukgu, Daegu, 702-701 (Korea, Republic of)

Description

In this study, photocatalytic properties of a graphene carbon nitride (g-C3N4) oxygen-deficient BiOCl (ODBOC) nanocomposite, which was assisted by the distinguished properties of graphene quantum dots (GQDs/gCN/ODBOC), in the decomposition of harmful organic vapors were investigated. The GQDs/gCN/ODBOC ternary composite was prepared using a facile chemical-mixing method. The presence of oxygen vacancies in ODBOC and the GQDs/gCN/ODBOC nanocomposite was confirmed by electron spin resonance and X-ray photoelectron spectroscopy. Compared to pristine BiOCl, ODBOC exhibited a higher performance, while compared with those of the selected photocatalyst counterparts, GQDs/gCN/ODBOC exhibited a higher performance; particularly, the removal efficiency of hexanal over this catalyst increased up to 95%. The superior performance of the above photocatalyst was related to two distinguished properties of GQDs: improved visible-light absorption by their upconverted photoluminescence and promoted charge-separation ability by their electron attraction properties, as well as the Z-scheme charge transfer at the junctions between g-C3N4 and ODBOC. In addition, the GQDs/gCN/ODBOC fabricated using a GQD solution of 5 mL revealed the highest performance and satisfactory photochemical stability during recycling tests. Finally, the photocatalytic mechanism for the pollutant degradation over GQDs/gCN/ODBOC was proposed on the basis of band-energy structures and hydroxyl radical measurements.

Additional details

Identifiers

DOI
10.1016/j.apsusc.2019.07.085;
PII
S016943321932121X;

Publishing Information

Journal Title
Applied Surface Science
Journal Volume
493
Journal Page Range
p. 873-881
ISSN
0169-4332
CODEN
ASUSEE

Optional Information

Copyright
Copyright (c) 2019 Elsevier B.V. All rights reserved.