Synthesis of 5,6-Dihydrophenanthridines via Palladium-Catalyzed Intramolecular Dehydrogenative Coupling of Two Aryl C−H Bonds

Abstract

5,6-Dihydrophenanthridines are common aza heterocycle frameworks of natural products and pharmaceuticals. Herein, we reported the first palladium-catalyzed intramolecular C−H/C−H dehydrogenative coupling reaction of two simple arenes to generate 5,6-dihydrophenanthridines. The approach features a broad substrate scope and good tolerance of functional groups, offering an efficient alternative synthesis route for important 5,6-dihydrophenanthridine compounds.

Recent advances in nanomaterial-based solid-contact ion-selective electrodes

“…153,154 For example, Yehia et al 155 developed an SC-ISE for flunitrazepam determination in beverages using poly (3,4-ethylenedioxythiophene) nanoparticles, which generated a conductive and hydrophobic polymer layer on the electrode surface to achieve good selectivity and a low detection limit. Zhang and co-workers 156 employed poly(3-octylthiophene-2,5-diyl) and carbon black as the transducer in an SC-ISE to improve the sensitivity for the detection of K + . Various polymeric nanofibers such as poly(3,4ethylenedioxythiophene) have been used in SC-ISEs as a component of the solid contact for the detection of Pb 2+ .…”

Palladium Catalysis: Dependence of the Efficiency of C−C Bond Formation on Carboxylate Ligand and Alkali Metal Carboxylate or Carboxylic Acid Additive. Part A: the C(sp2)−C(sp2), C(sp2)−C(sp3) and C(sp3)−C(sp3) Bonds

“…Recently, Jia, Wang and co-workers disclosed the intramolecular dehydrogenative coupling of two aryl CÀ H bonds using palladium and copper carboxylates in catalytic and stoichiometric amounts, respectively (Scheme 9). [58] The best result arose with the trifluoroacetates at 100 °C in CF 3 CH 2 OH under an air atmosphere. CMD process mediated with trifluoroacetate ligand was proposed by the authors.…”

Chemical language models for molecular design

“…The design of virtual compound libraries via machine translation was one of the first applications of CLMs, for which RNNs [2, 5, 12, 13] and, subsequently, transformers were used [13, 14]. In addition, transformer networks have been employed for other generative compound design applications [15–17]. Furthermore, both RNN and transformer models have been extensively used for chemical reaction prediction [18–21], representing a growth area for CLM applications.…”