The chemistry community should ban drawing chemical structures with generative AI, chemists warn

AIs like Microsoft's Copilot, Google's Gemini and OpenAI's ChatGPT still make serious errors rendering structural formulae

chemistryworld.com

Stereo-reversed E2 unlocks Z-selective C–H functionalization

The stereoselective functionalization of C–H bonds represents a central challenge in modern organic synthesis. Despite decades of innovation in C–H activation chemistry, methods for Z-selective functi...

science.org

Dr. Corey Stephenson, chemist and CERC Chair

YouTube video by ubcscience

youtube.com

A modular synthesis of azetidines from reactive triplet imine intermediates using an intermolecular aza Paternò–Büchi reaction - Nature Catalysis

Azetidines are four-membered saturated N-heterocycles that are of interest in drug discovery and medicinal chemistry. Here the authors report how sulfamoyl fluoride substituents tune the reactivity of...

nature.com

Elementary Steps in Olefin Metathesis: Nickelacyclobutanes via Cycloaddition to Nickel Carbenes

Olefin metathesis and cyclopropanation, major reactions in the synthetic toolbox, are predominantly catalyzed by platinum-group metals. First-row transition metal alternatives are desirable from the p...

pubs.acs.org

Data-Driven Workflow for the Development and Discovery of <italic toggle&#x3D;"yes">N</italic>-Oxyl Hydrogen Atom Transfer Catalysts

N-oxyl species are promising hydrogen atom transfer (HAT) catalysts to advance C–H bond activation reactions. However, because of the complex structure–activity relationship within the N-oxyl structure, catalyst optimization is a key challenge, particularly for simultaneous improvement across multiple parameters. This paper describes a data-driven approach to optimize N-oxyl hydrogen atom transfer catalysts. A focused library of 50 N-hydroxy compounds was synthesized and characterized by three parameters─oxidation peak potential, HAT reactivity, and stability─to generate a database. Statistical modeling of these activities described by their intrinsic physical organic parameters was used to build predictive models for catalyst discovery and to understand their structure–activity relationships. Virtual screening of 102 synthesizable candidates allowed for rapid identification of several ideal catalyst candidates. These statistical models clearly suggest that N-oxyl substructures bearing an adjacent heteroatom are more optimal HAT catalysts compared to the historical focus, phthalimide-N-oxyl, by striking the best balance among all three target experimental properties.

pubs.acs.org

Data-Driven Workflow for the Development and Discovery of <italic toggle&#x3D;"yes">N</italic>-Oxyl Hydrogen Atom Transfer Catalysts

N-oxyl species are promising hydrogen atom transfer (HAT) catalysts to advance C–H bond activation reactions. However, because of the complex structure–activity relationship within the N-oxyl structure, catalyst optimization is a key challenge, particularly for simultaneous improvement across multiple parameters. This paper describes a data-driven approach to optimize N-oxyl hydrogen atom transfer catalysts. A focused library of 50 N-hydroxy compounds was synthesized and characterized by three parameters─oxidation peak potential, HAT reactivity, and stability─to generate a database. Statistical modeling of these activities described by their intrinsic physical organic parameters was used to build predictive models for catalyst discovery and to understand their structure–activity relationships. Virtual screening of 102 synthesizable candidates allowed for rapid identification of several ideal catalyst candidates. These statistical models clearly suggest that N-oxyl substructures bearing an adjacent heteroatom are more optimal HAT catalysts compared to the historical focus, phthalimide-N-oxyl, by striking the best balance among all three target experimental properties.

pubs.acs.org