News Picture Generic

First catalytic asymmetric hydrogenation of quinoxaline-2-carboxylates

May 3, 2016

Villeneuve d’Ascq Cedex / Paris, France First catalytic asymmetric hydrogenation of quinoxaline-2-carboxylates “For the first time, the asymmetric hydrogenation of quinoxaline-2-carboxylates was performed successfully. The best catalysts are based on iridium complexes modified by chiral phosphorous ligands. Accelerated examination of ligands and catalysts has been undertaken by using a Chemspeed workstation, which enables carrying out, in parallel, eight independent catalytic reactions at the laboratory scale. Tetrahydroquinoxaline-2-carboxylates could be obtained with high yields and up to 74% ee.” For details: First catalytic asymmetric hydrogenation of quinoxaline-2-carboxylates Anna M. Maja,*, Svetlana Heyteb, Marcia Araqueb, Franck Dumeignilb,c, Sébastien Paulb, Isabelle Suissea,*, Francine Agbossou-Niedercorna,* a UCCS (Unité de Catalyse et de Chimie du Solide UMR 8181), CNRS, Université de Lille, ENSCL, Cité Scientifique, CS 90108, 59652 Villeneuve d’Ascq Cedex, France b UCCS (Unité de Catalyse et de Chimie du Solide UMR 8181), CNRS, Université de Lille, Ecole Centrale de Lille, Cité Scientifique, CS 20048, 59652 Villeneuve d’Ascq Cedex, France c Institut Universitaire de France, 103 Boulevard Saint-Michel, 75005 Paris, France * Corresponding authors Tetrahedron, Volume 72, Issue 10, 10 March 2016, Pages 1375–1380

Other Recent News

Discover more news articles you might be interested in

Read more about Asymmetric hydrogenation of olefins with transition metal-based catalysts: practical insights from screening to production of APIs
News Picture 1 1 V2
Featured
Jan
20

Asymmetric hydrogenation of olefins with transition metal-based catalysts: practical insights from screening to production of APIs

Selective hydrogenation plays a critical role in modern synthetic chemistry, particularly in the pharmaceutical industry, where the production of chiral molecules with high enantiomeric purity is essential for the efficacy and safety of active pharmaceutical ingredients (APIs). 

Read more about Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography
News Picture 1 1 V2
Featured
Jan
6

Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography

The integration of automated synthesis and machine learning (ML) is transforming analytical chemistry by enabling data-driven approaches to method development. Chromatographic column selection, a critical yet time-consuming step in separation science, stands to benefit substantially from such advances.

© Chemspeed Technologies 2026