Suppr超能文献

具有增强可见光光催化活性用于去除一氧化氮(NO)的MoS/g-CN纳米复合材料的合成。

Synthesis of MoS/g-CN nanocomposites with enhanced visible-light photocatalytic activity for the removal of nitric oxide (NO).

作者信息

Wen M Q, Xiong T, Zang Z G, Wei W, Tang X S, Dong F

出版信息

Opt Express. 2016 May 16;24(10):10205-12. doi: 10.1364/OE.24.010205.

Abstract

Molybdenum disulfide and graphitic carbon nitride (MoS-g-CN) nanocomposites with visible-light induced photocatalytic activity were successfully synthesized by a facile ultrasonic dispersion method. The crystalline structure and morphology of the MoS-g-CN nanocomposites were characterized by X-ray diffraction (XRD), transmission electron microcopy (TEM), high-resolution TEM (HRTEM) and scanning electron microscopy (SEM). The optical property of the as-prepared nanocomposites was studied by ultraviolet visible diffusion reflection (UV-vis) and photoluminescence(PL) spectrum. It could be observed from the TEM image that the MoS nanosheets and g-CN nanoparticles were well combined together. Moreover, the photocatalytic activity of MoS-g-CN composites was evaluated by the removal of nitric oxide under visible light irradiation (>400nm). The experimental results demonstrated that the nanocomposites with the MoS content of 1.5 wt% exhibited optimal photocatalytic activity and the corresponding removal rate of NO achieved 51.67%, higher than that of pure g-CN nanoparticles. A possible photocatalytic mechanism for the MoS-g-CN nanocomposites with enhanced photocatalytic activity could be ascribed to the hetero-structure of MoS and g-CN.

摘要

通过简便的超声分散法成功合成了具有可见光诱导光催化活性的二硫化钼与石墨相氮化碳(MoS-g-CN)纳米复合材料。采用X射线衍射(XRD)、透射电子显微镜(TEM)、高分辨率TEM(HRTEM)和扫描电子显微镜(SEM)对MoS-g-CN纳米复合材料的晶体结构和形貌进行了表征。通过紫外可见漫反射(UV-vis)和光致发光(PL)光谱研究了所制备纳米复合材料的光学性质。从TEM图像中可以观察到,MoS纳米片和g-CN纳米颗粒很好地结合在一起。此外,通过在可见光照射(>400nm)下对一氧化氮的去除来评估MoS-g-CN复合材料的光催化活性。实验结果表明,MoS含量为1.5 wt%的纳米复合材料表现出最佳的光催化活性,相应的NO去除率达到51.67%,高于纯g-CN纳米颗粒。具有增强光催化活性的MoS-g-CN纳米复合材料的一种可能的光催化机理可归因于MoS和g-CN的异质结构。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验