Featured
Aug
4
Self-Driving Labs Are Rewriting the Clock on Discovery
North Carolina State University Now Runs the Largest Academic Self-Driving Lab Ecosystem in the US.
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
Featured
Jul
14
High-throughput solid microsampling through stochastic robotic automation
Solid sampling at the sub-milligram and milligram scale remains a major bottleneck for high-throughput chemistry or material sciences, as existing approaches rely on manual handling or slow deterministic microsampling that do not readily scale.
Here we present STORMS, an automated STOchastic Robotic MicroSampling system that enables fast, reliable and parallel sampling of solid materials at sub-milligram and milligram masses.
Jun
30
Parameter efficient multi-model vision assistant for polymer solvation behaviour inference
Polymer–solvent systems exhibit complex solvation behaviours encompassing a diverse range of phenomena, including swelling, gelation, and dispersion. Accurate interpretation is often hindered by subjectivity, particularly in manual rapid screening assessments. While computer vision models hold significant promise to replace the reliance on human evaluation for inference, their adoption is limited by the lack of domain-specific datasets tailored, in our case, to polymer–solvent systems.
Chemspeed is a global team committed to enable automated and digitalized workflows for scientists in R&D and QC.
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