Catalytic selective oxidation of aromatic amines to azoxy derivatives with an ultralow loading of peroxoniobate salts

CATALYSIS SCIENCE & TECHNOLOGY(2022)

引用 1|浏览14
暂无评分
摘要
This work has demonstrated that tartaric acid-coordinated peroxoniobate salts can be employed as highly efficient catalysts in oxidative coupling of aniline to azoxybenzene under green and very mild conditions. These salts were synthesized and characterized thoroughly by FT-IR spectroscopy, elemental analysis, ICP-AES, TGA, ESI-MS, Nb-93 NMR, UV-vis spectroscopy, and EXAFS spectroscopy. Notably, full conversion of aniline and an excellent selectivity to azoxybenzene (more than 95%) were achieved with ppm-level peroxoniobate-based catalysts. Moreover, the reaction can proceed smoothly with stoichiometric amounts of H2O2 without external heating and additives. The salts are also highly active in the conversion of various substituted aromatic amines with excellent selectivity towards azoxy products in simple operations. Mechanistic studies utilizing butylated hydroxytoluene (BHT) as a radical scavenger proved that the reaction proceeded through a catalytic mechanism rather than a radical approach. Besides, HRMS and UV-vis characterization provided clear evidence that Nb-(eta(2)-O-2) species is an active intermediate involved in the selective oxidation of anilines. The hydrogen bond interaction between the -NH2 group and Nb-(eta(2)-O-2) species of the salts played an important role in producing N-phenylhydroxylamine as an intermediate, which was oxidized into nitrosobenzene. Then, the condensation between N-phenylhydroxylamine and nitrosobenzene afforded azoxybenzene quantitatively. This is the first work that shows that peroxoniobate salts demonstrate an exceptionally high TOF value (up to 4435 h(-1)) for the oxidation of arylamines even under ultralow loading conditions. Its exceptional catalytic performance and the green and mild reaction conditions make this catalytic system a promising candidate for oxidative coupling of aromatic amines in further industrial applications.
更多
查看译文
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