1168104-48-0Relevant articles and documents
Selective Reductive Elimination at Alkyl Palladium(IV) by Dissociative Ligand Ionization: Catalytic C(sp3)?H Amination to Azetidines
Nappi, Manuel,He, Chuan,Whitehurst, William G.,Chappell, Ben G. N.,Gaunt, Matthew J.
, p. 3178 - 3182 (2018/02/28)
A palladium(II)-catalyzed γ-C?H amination of cyclic alkyl amines to deliver highly substituted azetidines is reported. The use of a benziodoxole tosylate oxidant in combination with AgOAc was found to be crucial for controlling a selective reductive elimination pathway to the azetidines. The process is tolerant of a range of functional groups, including structural features derived from chiral α-amino alcohols, and leads to the diastereoselective formation of enantiopure azetidines.
Design of a genetic algorithm for the simulated evolution of a library of asymmetric transfer hydrogenation catalysts
Vriamont, Nicolas,Govaerts, Bernadette,Grenouillet, Pierre,De Bellefon, Claude,Oliant, Olivier
supporting information; experimental part, p. 6267 - 6278 (2010/01/19)
A library of catalysts was designed for asymmetric-hydrogen transfer to acetophenone. At first, the whole library was submitted to evaluation using high-throughput experiments (HTE). The catalysts were listed in ascending order, with respect to their performance, and best catalysts were identified. In the second step, various simulated evolution experiments, based on a genetic algorithm, were applied to this library. A small part of the library, called the mother generation (GO), thus evolved from generation to generation. The goal was to use our collection of HTE data to adjust the parameters of the genetic algorithm, in order to obtain a maximum of the best catalysts within a minimal number of gen-erations. It was namely found that simulated evolution's results depended on the selection of GO and that a random GO should be preferred. We also demonstrated that it was possible to get 5 to 6 of the ten best catalysts while investigating only 10% of the library. Moreover, we developed a double algorithm making this result still achievable if the evolution started with one of the worst GO.
