Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

AQME, automated quantum mechanical environments, is a free and open‐source Python
package for the rapid deployment of automated workflows using cheminformatics and …

New methods for the general asymmetric synthesis of sulfonimidamides are of great interest
due to their applications in medicinal chemistry, agrochemical discovery, and academic …

The arylation of 2-alkyl aziridines by nucleophilic ring-opening or transition-metal-catalyzed
cross-coupling enables facile access to biologically relevant β-phenethylamine derivatives …

We report a visible-light photoredox-catalyzed method that enables nucleophilic amination
of primary and secondary benzylic C (sp3)–H bonds. A novel amidyl radical precursor and …

Synthetic yield prediction using machine learning is intensively studied. Previous work has
focused on two categories of data sets: high-throughput experimentation data, as an ideal …

Catalyst optimization processes typically rely on inductive and qualitative assumptions of
chemists based on screening data. While machine learning models using molecular …

Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many
impressive applications, but the success of these applications requires a massive amount of …

The application of machine learning (ML) techniques to model high-throughput
experimentation (HTE) datasets has seen a recent rise in popularity. Nevertheless, the …

Chiral ligands are important components in asymmetric homogeneous catalysis, but their
synthesis and screening can be both time-consuming and resource-intensive. Data-driven …