Phenylboronic Ester-Activated Aryl Iodide-Selective Buchwald-Hartwig-Type Amination toward Bioactivity Assay.

In this study, a phenylboronic ester-activated aryl iodide-selective Buchwald-Hartwig-type amination was developed. When the reaction of aryl iodides and aryl/aliphatic amines using Ni(acac)2 is carried out in the presence of phenylboronic ester, the Buchwald-Hartwig-type amination proceeds smoothly to afford the corresponding amines in high yields. This reaction does not proceed in the absence of phenylboronic ester. A wide variety of aryl iodides can be applied in the presence of aryl chlorides and bromides, which remain intact during the reaction. The mechanistic studies of this reaction suggest that the phenylboronic ester acts as an activator for the amines to form the ″ate complex″. Chemical kinetics studies show that the reaction of aryl iodides, base, and Ni(acac)2 follows first-order kinetics, while that of amines and phenylboronic ester follows zero-order kinetics. The bioactivity screening of the corresponding products showed that some amination products exhibit antifungal activity.

Design of Experimental Conditions with Machine Learning for Collaborative Organic Synthesis Reactions Using Transition-Metal Catalysts.

To improve product yields in synthetic reactions, it is important to use appropriate catalysts. In this study, we used machine learning to design catalysts for a reaction system in which both Buchwald-Hartwig-type and Suzuki-Miyaura-type cross-coupling reactions proceed simultaneously. First, using an existing dataset, yield prediction models were constructed with machine learning between experimental conditions, including the substrate and catalyst and the yields of the two products. Seven methods for calculating both the substrate and catalyst descriptors were proposed, and the predictive ability of the yield prediction models was discussed in terms of the descriptors and machine learning methods. Then, the constructed models were used to predict the compound yields for new combinations of substrates and catalysts, and the predictions were experimentally validated with high reproducibility, confirming that machine learning can predict yields from experimental conditions with high accuracy. In addition, to design catalysts that will improve the yields in our dataset, we added datasets collected from scientific papers and designed catalyst ligands. The proposed catalyst candidates were tested in actual synthetic experiments, and the experimental results exceeded the existing yields.

Activator-Promoted Aryl Halide-Dependent Chemoselective Buchwald-Hartwig and Suzuki-Miyaura Type Cross-Coupling Reactions.

Herein, we report the development of aryl halide-dependent chemoselective reactions, viz., the Buchwald-Hartwig type coupling reaction of an aryl iodide with an arylboronic acid and an aryl amine in the presence of a heterogeneous and reusable nickel catalyst and the Suzuki-Miyaura type coupling of an aryl chloride under similar conditions. Control experiments revealed that the presence of stoichiometric amounts of the phenylboronic acid/ester and aryl amine are essential for both reactions. NMR and XAFS studies suggested the formation of a boron-amine "ate" complex.

Significant stabilization of palladium by gold in the bimetallic nanocatalyst leading to an enhanced activity in the hydrodechlorination of aryl chlorides.

The stabilization effect of Au towards Pd changed the reactivity of Pd in Au/Pd bimetallic nanoclusters, altering the reaction mechanism from homogeneous to heterogeneous in dechlorination reaction of aryl chlorides. This phenomenon was illustrated by the observed enhancement of the rate of reaction by in situ generated Au-rich bimetallic Au/Pd nanoclusters.