Direct synthesis of α-functionalized amides via heteroatom-hydrogen insertion reactions using amide-sulfoxonium ylides.

α-Functionalized Si-, Ge-, B-, Se-, and S-amide moieties are present in many medicinally active molecules, but their synthesis remains challenging. Here, we demonstrate a high-throughput synthesis using amide-sulfoxonium ylides as carbene precursors in a Si-H, Ge-H, B-H, Se-H, and S-H insertion reactions to target a wide range of α-silyl, α-geryl, α-boryl, α-selenyl, and α-sulfur (hetero)amides. The process is featured as simple operation, mild conditions, broad substrate scope, high functional group compatibility, and excellent chemoselectivity.

High-Throughput Experimentation and Machine Learning-Assisted Optimization of Iridium-Catalyzed Cross-Dimerization of Sulfoxonium Ylides.

A novel and convenient approach that combines high-throughput experimentation (HTE) with machine learning (ML) technologies to achieve the first selective cross-dimerization of sulfoxonium ylides via iridium catalysis is presented. A variety of valuable amide-, ketone-, ester-, and N-heterocycle-substituted unsymmetrical E-alkenes are synthesized in good yields with high stereoselectivities. This mild method avoids the use of diazo compounds and is characterized by simple operation, high step-economy, and excellent chemoselectivity and functional group compatibility.

Simultaneous source localization and polarization estimation via non-orthogonal joint diagonalization with vector-sensors.

Joint estimation of direction-of-arrival (DOA) and polarization with electromagnetic vector-sensors (EMVS) is considered in the framework of complex-valued non-orthogonal joint diagonalization (CNJD). Two new CNJD algorithms are presented, which propose to tackle the high dimensional optimization problem in CNJD via a sequence of simple sub-optimization problems, by using LU or LQ decompositions of the target matrices as well as the Jacobi-type scheme. Furthermore, based on the above CNJD algorithms we present a novel strategy to exploit the multi-dimensional structure present in the second-order statistics of EMVS outputs for simultaneous DOA and polarization estimation.