Cu/Oxalic Diamide-Catalyzed Coupling of Terminal Alkynes with Aryl Halides

6-Hydroxy Picolinohydrazides Promoted Cu(I)-Catalyzed Hydroxylation Reaction in Water: Machine-Learning Accelerated Ligands Design and Reaction Optimization

Hydroxylated (hetero)arenes are privileged motifs in natural products, materials, small-molecule pharmaceuticals and serve as versatile intermediates in synthetic organic chemistry. Herein, we report an efficient Cu(I)/6-hydroxy picolinohydrazide-catalyzed hydroxylation reaction of (hetero)aryl halides (Br, Cl) in water. By establishing machine learning (ML) models, the design of ligands and optimization of reaction conditions were effectively accelerated. The N-(1,3-dimethyl-9H- carbazol-9-yl)-6-hydroxypicolinamide (L32, 6-HPA-DMCA) demonstrated high efficiency for (hetero)aryl bromides, promoting hydroxylation reactions with a minimal catalyst loading of 0.01 mol % (100 ppm) at 80 °C to reach 10000 TON; for substrates containing sensitive functional groups, the catalyst loading needs to be increased to 3.0 mol % under near-room temperature conditions. N-(2,7-Di-tert-butyl-9H-carbazol-9-yl)-6-hydroxypicolinamide (L42, 6-HPA-DTBCA) displayed superior reaction activity for chloride substrates, enabling hydroxylation reactions at 100 °C with 2-3 mol % catalyst loading. These represent the state of art for both lowest catalyst loading and temperature in the copper-catalyzed hydroxylation reactions. Furthermore, this method features a sustainable and environmentally friendly solvent system, accommodates a wide range of substrates, and shows potential for developing robust and scalable synthesis processes for key pharmaceutical intermediates.

TBHP Mediated C-N Bond Cleavage of Tertiary Amines toward the Synthesis of Oxalamides and α,β-Epoxy Amides

An efficient and convenient method for the synthesis of oxalamides by the reaction of β-ketoamides with tertiary amines and TBHP was developed. A variety of β-ketoamides and tertiary amines substrates were well-tolerated in this transformation. Based on the control experiments, a plausible mechanism for this reaction was proposed that involved the tandem oxidation/amination process. In addition, α,β-epoxy amides could be obtained by adjusting the reaction conditions.

Predicting success in Cu-catalyzed C-N coupling reactions using data science

Data science is assuming a pivotal role in guiding reaction optimization and streamlining experimental workloads in the evolving landscape of synthetic chemistry. A discipline-wide goal is the development of workflows that integrate computational chemistry and data science tools with high-throughput experimentation as it provides experimentalists the ability to maximize success in expensive synthetic campaigns. Here, we report an end-to-end data-driven process to effectively predict how structural features of coupling partners and ligands affect Cu-catalyzed C-N coupling reactions. The established workflow underscores the limitations posed by substrates and ligands while also providing a systematic ligand prediction tool that uses probability to assess when a ligand will be successful. This platform is strategically designed to confront the intrinsic unpredictability frequently encountered in synthetic reaction deployment.