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Matthews, Adrian D.; Peters, Ellyn; Debenham, John S.; Gao, Qi; Nyamiaka, Maya D.; Pan, Jianping; Zhang, Li-Kang; Dreher, Spencer D.; Krska, Shane W.; Sigman, Matthew S.; et al (, ACS Catalysis)
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Gensch, Tobias; dos Passos Gomes, Gabriel; Friederich, Pascal; Peters, Ellyn; Gaudin, Théophile; Pollice, Robert; Jorner, Kjell; Nigam, AkshatKumar; Lindner-D’Addario, Michael; Sigman, Matthew S.; et al (, Journal of the American Chemical Society)
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Newman-Stonebraker, Samuel H.; Smith, Sleight R.; Borowski, Julia E.; Peters, Ellyn; Gensch, Tobias; Johnson, Heather C.; Sigman, Matthew S.; Doyle, Abigail G. (, Science)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.more » « less
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