Suppr超能文献

可再生原料来源的不饱和大环内酯:合成、开环聚合及应用前景

Unsaturated Macrolactones from Renewable Feedstocks: Synthesis, Ring-Opening Polymerization and Application Prospects.

作者信息

Nifant'ev Ilya, Afanaseva Anna, Vinogradov Alexander, Ivchenko Pavel

机构信息

A.V. Topchiev Institute of Petrochemical Synthesis RAS, 29 Leninsky Pr., 119991 Moscow, Russia.

Chemistry Department, M.V. Lomonosov Moscow State University, 1 Leninskie Gory Str., Building 3, 119991 Moscow, Russia.

出版信息

Int J Mol Sci. 2025 May 23;26(11):5039. doi: 10.3390/ijms26115039.

Abstract

Unsaturated macrolactones (UMs) have long attracted researchers' attention due to a combination of a reactive ester fragment and C=C bond in their structures. UMs of natural origin are comparatively few in number, and the task of developing synthetic approaches to new UMs is relevant. Recent advances in the synthesis of UMs cannot be dissociated from the progress in design of metathesis catalysts, since this catalytic approach is an atom-economy alternative to conventional organochemical methods. In the present review, we summarized and discussed the use of ring-closing metathesis, catalyzed by Ru and Group 6 metal complexes, in the synthesis of Ums and the advantages and shortcomings of the catalytic approach to UMs in comparison with organochemical methods. In a separate section, the use of UMs in the synthesis of unsaturated polyesters, the functionalization of these (co)polymers, and the prospects for practical use of the material obtained are also presented. It is essential that the actual approaches to UMs are often based on the use of renewable feedstocks, thereby meeting Green Chemistry principles.

摘要

不饱和大环内酯(UMs)因其结构中存在反应性酯片段和碳碳双键,长期以来一直吸引着研究人员的关注。天然来源的UMs数量相对较少,因此开发新UMs的合成方法这一任务具有重要意义。UMs合成的最新进展与复分解催化剂设计的进展密不可分,因为这种催化方法是传统有机化学方法的原子经济性替代方案。在本综述中,我们总结并讨论了由钌和第6族金属配合物催化的闭环复分解反应在UMs合成中的应用,以及与有机化学方法相比,UMs催化合成方法的优缺点。在单独的一节中,还介绍了UMs在不饱和聚酯合成中的应用、这些(共)聚合物的功能化以及所得材料的实际应用前景。重要的是,UMs的实际合成方法通常基于可再生原料的使用,从而符合绿色化学原则。

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