CdS/COF core-shell nanorods with efficient chemisorption, enhanced carrier separation, and antiphotocorrosion ability for U(VI) photoreduction

Science China Materials(2023)

引用 0|浏览7
暂无评分
摘要
Reduction of soluble U(VI) to insoluble U(IV) based on semiconductor photocatalysts is a favored U(VI)-extraction method, because of its simplicity, environmental friendliness, and high efficiency. The key to implement this technology is the development of efficient photocatalysts with high activity and stability for sacrificial agents-free U(VI) photoreduction. Herein, we report a new type of CdS/covalent organic framework (COF) core-shell photocatalysts (CdS@COF- X , X = 5, 10, 15, and 20) with efficient chemisorption, enhanced carrier separation, and antiphotocorrosion ability for U(VI) photoreduction without additional sacrificial agents. The two-dimensional COF, formed by the polycondensation of 2,4,6-triformylphloroglucinol and 1,3,5-tris(4-aminophenyl)triazine, was selected to construct the hybrid materials due to its high chemical stability, matching band gaps and efficient chemisorption for U(VI). Remarkably, CdS@COF-10 realized a record high U(VI) extraction capacity of 1825.6 mg g −1 after 90 min. Moreover, the reduction ratio of uranium was up to 82.5%, and the product was identified as uranium dioxide (UO 2 ) after reaction. Further mechanistic studies indicated that the COF shell not only provided chemisorption sites for U(VI) to decrease the activation energy of U(VI) reduction, but also formed a strong built-in electric field at the interface with the CdS core to promote the carrier separation. More importantly, for all CdS@COF- X , CdS-COF-10 with appropriate COF shell content balanced the crystallinity, interfacial contact integrity, light absorption of CdS core, and number of U(VI) chemisorption sites, achieving the highest carrier separation efficiency and U(VI) photoreduction performance.
更多
查看译文
关键词
covalent organic frameworks,core-shell structures,U(VI) photoreduction,carrier separation,antiphotocorrosion
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要