Dozens of aminocatalytic conjugated additions have been described recently with a large range of nucleophiles and enals. Standard optimization procedures have led to contradictory conclusions about what are the best additives for these reactions. For slightly different reagents or reaction conditions, additives with opposite properties, such as acids or bases, have been described as optimal. We have kinetically studied these reactions and spectroscopically characterized all the catalytic resting states during the entire course of the reactions. The results of our studies have revealed the role of the additives used and explained the discrepancies observed in the literature. We conclude that irreproducibility problems are associated to small traces of impurities on the starting materials, which are hard to characterize and control. To overcome these problems, we propose a new method to optimize the rate of a reaction that uses the information derived from catalytic intermediates instead of using concentration of reagents and additives. This method uses the distribution of catalytic species as a characteristic parameter that correlates with the turnover frequency of the reaction. The distribution of catalytic species can be quickly and easily obtained by a simple 1H-NMR spectrum. The distribution of the three main catalytic species under different experimental conditions is plotted in a ternary diagram and the rate for each condition is color coded to form a reactivity map. With this map, any starting reaction conditions can be consistently tuned to the optimal ones. We have built and used this reactivity map to successfully solve problems of irreproducibility in different reactions. More importantly, the map-assisted method has allowed us to reduce the typical catalyst loadings (10-20 mol%) for aminocatalytic conjugated additions to less than 0.2 mol% to complete the reactions in similar times.

Efficient aminocatalytic conjugate addition via mechanistic studies on the role of additives

251st National Meeting (2016)

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