A new PEPPSI type N-heterocyclic carbene palladium(II) complex and its efficiency as a catalyst for Mizoroki-Heck cross-coupling reactions in water

Design and synthesis of versatile ligand precursors based on phosphonium ylides for palladalactam formation and catalytic investigation

A new series of ligand precursors designed for the synthesis of palladalactams has been developed. These precursors are easily accessible through a one-step reaction involving 2-chloro-N-phenylacetamide and a wide choice of various monophosphines, offering tunable electronic and steric properties within the ligand framework. The stability of both ligand precursors and resulting palladalactams in ambient air enhances their practical applicability. A newly synthesized palladalactam, featuring an electron-donating triethylphosphine moiety on the anionic phosphonium ylide ligand scaffold exhibited promising catalytic activities in the Mizoroki-Heck coupling reaction between aryl chlorides and alkenes. Theoretical calculations further affirmed that the ligand system in the complex is the most electron-donating, forming the strongest Pd-C bond compared to other complexes with alternative phosphine moieties.

Emerging Trends in Cross-Coupling: Twelve-Electron-Based L1Pd(0) Catalysts, Their Mechanism of Action, and Selected Applications

Monoligated palladium(0) species, L₁Pd(0), have emerged as the most active catalytic species in the cross-coupling cycle. Today, there are methods available to generate the highly active but unstable L₁Pd(0) catalysts from stable precatalysts. While the size of the ligand plays an important role in the formation of L₁Pd(0) during in situ catalysis, the latter can be precisely generated from the precatalyst by various technologies. Computational, kinetic, and experimental studies indicate that all three steps in the catalytic cycle─oxidative addition, transmetalation, and reductive elimination─contain monoligated Pd. The synthesis of precatalysts, their mode of activation, application studies in model systems, as well as in industry are discussed. Ligand parametrization and AI based data science can potentially help predict the facile formation of L₁Pd(0) species.