Kinetics of N(2) Release from Diazo Compounds: A Combined Machine Learning-Density Functional Theory Study

重氮化合物中N₂释放动力学:机器学习与密度泛函理论相结合的研究

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Abstract

Diazo compounds are commonly employed as carbene precursors in carbene transfer reactions during a variety of functionalization procedures. Release of N(2) gas from diazo compounds may lead to carbene formation, and the ease of this process is highly dependent on the characteristics of the substituents located in the vicinity of the diazo moiety. A quantum mechanical density functional theory assisted by machine learning was used to investigate the relationship between the chemical features of diazo compounds and the activation energy required for N(2) elimination. Our results suggest that diazo molecules, possessing a higher positive partial charge on the carbene carbon and more negative charge on the terminal nitrogen, encounter a lower energy barrier. A more positive C charge decreases the π-donor ability of the carbene lone pair to the π* orbital of N(2), while the more negative N charge is a result of a weak interaction between N(2) lone pair and vacant p orbital of the carbene. The findings of this study can pave the way for molecular engineering for the purpose of carbene generation, which serves as a crucial intermediate for many chemical transformations in synthetic chemistry.

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