Predictive, Data-Driven Design of Red-Light Photoredox Catalysts for C─Heteroatom Bond Formation

基于预测和数据驱动的红光光氧化还原催化剂设计及其在C-杂原子键形成中的应用

阅读:1

Abstract

Photocatalysis is a powerful tool for the synthesis of organic molecules, yet its widespread application is hindered by the dependence on high-energy light sources and expensive metal-based catalysts, which can limit scalability and environmental sustainability. In this study, we present a modular design strategy for organic dyes engineered for efficient red-light absorption, enabling photocatalytic reactions under low-energy irradiation. Our findings establish a clear relationship between the oxidation potential of the photocatalyst and the nature of its donor moiety, as well as between the reduction potential and the electronic characteristics of its core structure. Moreover, we demonstrate that the E(0-0) energy of a photocatalyst can be predicted via multivariate linear regression using the donor's oxidation potential and the core's reduction potential as descriptors. Utilizing this strategy, we synthesized red-light-absorbing photocatalysts that efficiently promote C─heteroatom cross-coupling reactions under mild conditions. This approach overcomes the limitations of blue-light photocatalysis by offering broad substrate compatibility, including π-conjugated aryl bromides and photolabile functional groups, while minimizing undesirable hydrodehalogenation. By reducing reliance on precious metals and improving energy efficiency, our approach provides a scalable alternative to traditional photocatalysis and advances the development of metal-free photocatalysts for sustainable chemistry.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。