4.7 Article

Fabrication of metal-free two dimensional/two dimensional homojunction photocatalyst using various carbon nitride nanosheets as building blocks

期刊

JOURNAL OF COLLOID AND INTERFACE SCIENCE
卷 507, 期 -, 页码 209-216

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcis.2017.08.002

关键词

Graphitic carbon nitride; Liquid exfoliation; Chemical blowing; Two dimensional nanosheets; Homojunction

资金

  1. Zhejiang Provincial Natural Science Foundation of China [LY178010004]
  2. ZSTU

向作者/读者索取更多资源

Semiconductor photocatalysis currently suffered three main problems, low solar energy utilization, high photo-generated charge recombination rate and the heavy metal ions release by the photo-corrosion. Herein, we developed a visible-light-driven homojunction photocatalyst with the metal-free two-dimensional (2D) graphitic carbon nitride nanosheets (CNNS). By employing liquid exfoliation and chemical blowing approaches, we obtained two kinds of CNNS materials (le-CNNS and cb-CNNS) with different band structures, and subsequently fabricated the homojunction photocatalyst. This 2D/2D nanocomposited homojunction photocatalyst exhibited enhanced photocatalytic performance compared to these individual 2D nanosheets materials. Moreover, its well universality and reusability were also demonstrated by photo-degradation of various organic pollutants and five successive runs. By studying the optical properties and the electrochemical behavior, the band alignment of this homojunction was illustrated and the possible mechanism was proposed, where the transmitted electrons on the conduction band (CB) of le-CNNS would transport to the CB of cb-CNNS, and the holes on the valence band (VB) of cb-CNNS transferred to the VB of le-CNNS, therefore promoting the photo-induced carrier separation. Additionally, the photoluminescence, electrochemical impendence and photocurrent measurements further demonstrated that the recombination of photo-excited electron-hole pairs had been efficiently suppressed in the homojunction and were respectively collected on different CNNS components. (C) 2017 Elsevier Inc. All rights reserved.

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