Investigations of palladium catalysed 1,1-aminoacyloxylation of unsaturated carboxylic acids via experiments and machine learning

Abstract

Palladium catalyzed aza-Wacker oxidation is one of the most effective ways to construct heterocycles. Understanding the mechanism underlying these approaches facilitates the development of new efficient and practical methods for molecule synthesis. However, mechanistic elucidation often requires extensive experimental efforts and may still overlook key aspects of the underlying reaction pathways. Herein, based on our previous reports utilizing unsaturated carboxylic acids and aryl amines as substrates, a palladium catalyzed 1,1-aminoacyloxylation of unsaturated carboxyl acids has been developed, in conjunction with a mechanistic understanding integrating both experimental investigation and machine learning analysis. This method provides a series of amino-γ-lactone derivatives under mild reaction conditions, demonstrating broad substrate tolerance and yielding the corresponding products in good to excellent yields. Kinetic experiments and deuterium labelled experiments suggest that multiple pathways may be involved in the reaction, which is further verified by DFT calculations. Additionally, an established machine learning model was applied to predict the possible mechanism, highlighting the potential of catalyst deactivation via interactions with inhibitors. These findings suggest the formation of inactive palladium–aryl amine complexes, offering valuable insights that may inform future strategies aimed at mitigating catalyst deactivation and improving reaction efficiency.