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Chemists often use statistical analysis of reaction data with molecular descriptors to identify structure-reactivity relationships, which can enable prediction and mechanistic understanding. In this study, we developed a broadly applicable and quantitative classification workflow that identifies reactivity cliffs in 11 Ni- and Pd-catalyzed cross-coupling datasets using monodentate phosphine ligands. A distinctive ligand steric descriptor, minimum percent buried volume [% V bur (min)], is found to divide these datasets into active and inactive regions at a similar threshold value. Organometallic studies demonstrate that this threshold corresponds to the binary outcome of bisligated versus monoligated metal and that % V bur (min) is a physically meaningful and predictive representation of ligand structure in catalysis. 

Abstract Autonomous process optimization involves the human intervention-free exploration of a range process parameters to improve responses such as product yield and selectivity. Utilizing off-the-shelf components, we develop a closed-loop system for carrying out parallel autonomous process optimization experiments in batch. Upon implementation of our system in the optimization of a stereoselective Suzuki-Miyaura coupling, we find that the definition of a set of meaningful, broad, and unbiased process parameters is the most critical aspect of successful optimization. Importantly, we discern that phosphine ligand, a categorical parameter, is vital to determination of the reaction outcome. To date, categorical parameter selection has relied on chemical intuition, potentially introducing bias into the experimental design. In seeking a systematic method for selecting a diverse set of phosphine ligands, we develop a strategy that leverages computed molecular feature clustering. The resulting optimization uncovers conditions to selectively access the desired product isomer in high yield. 

Despite the enormous potential for the use of stereospecific cross-coupling reactions to rationally manipulate the three-dimensional structure of organic molecules, the factors that control the transfer of stereochemistry in these reactions remain poorly understood. Here we report a mechanistic and synthetic investigation into the use of enantioenriched alkylboron nucleophiles in stereospecific Pd-catalyzed Suzuki cross-coupling reactions. By developing a suite of molecular descriptors of phosphine ligands, we could apply predictive statistical models to select or design distinct ligands that respectively promoted stereoinvertive and stereoretentive cross-coupling reactions. Stereodefined branched structures were thereby accessed through the predictable manipulation of absolute stereochemistry, and a general model for the mechanism of alkylboron transmetallation was proposed. 

Abstract A synthetic method for the palladium‐catalyzed cyanation of aryl boronic acids using bench stable and non‐toxicN‐cyanosuccinimide has been developed. High‐throughput experimentation facilitated the screen of 90 different ligands and the resultant statistical data analysis identified that ligand σ‐donation, π‐acidity and sterics are key drivers that govern yield. Categorization into three ligand groups – monophosphines, bisphosphines and miscellaneous – was performed before the analysis. For the monophosphines, the yield of the reaction increases for strong σ‐donating, weak π‐accepting ligands, with flexible pendant substituents. For the bisphosphines, the yield predominantly correlates with ligand lability. The applicability of the designed reaction to a wider substrate scope was investigated, showing good functional group tolerance in particular with boronic acids bearing electron‐withdrawing substituents. This work outlines the development of a novel reaction, coupled with a fast and efficient workflow to gain understanding of the optimal ligand properties for the design of improved palladium cross‐coupling catalysts.