Optimizing the Heck–Matsuda Reaction in Flow with a Constraint-Adapted Direct Search Algorithm

Bibliographic Details
Parent link:Organic Process Research and Development
Vol. 20, iss. 11.— 2016.— [P. 1979–1987]
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт физики высоких технологий (ИФВТ) Кафедра биотехнологии и органической химии (БИОХ)
Other Authors: Cortes-Borda D. Daniel, Kutonova K. V. Ksenia Valentinovna, Corentin J. Jamet, Trusova M. E. Marina Evgenievna, Zammattio Francoise, Truchet Charlotte, Rodriguez-Zubiri Mireia, Felpin Francois-Xavier
Summary:Title screen
The optimization of a palladium-catalyzed Heck-Matsuda reaction using an optimization algorithm is presented. We modified and implemented the Nelder-Mead method in order to perform constrained optimizations in a multidimensional space. We illustrated the power of our modified algorithm through the optimization of a multivariable reaction involving the arylation of a deactivated olefin with an arenediazonium salt. The great flexibility of our optimization method allows to fine-tune experimental conditions according to three different objective functions: maximum yield, highest throughput, and lowest production cost. The beneficial properties of flow reactors associated with the power of intelligent algorithms for the fine-tuning of experimental parameters allowed the reaction to proceed in astonishingly simple conditions unable to promote the coupling through traditional batch chemistry.
Режим доступа: по договору с организацией-держателем ресурса
Language:English
Published: 2016
Subjects:
Online Access:http://dx.doi.org/10.1021/acs.oprd.6b00310
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654102
Description
Summary:Title screen
The optimization of a palladium-catalyzed Heck-Matsuda reaction using an optimization algorithm is presented. We modified and implemented the Nelder-Mead method in order to perform constrained optimizations in a multidimensional space. We illustrated the power of our modified algorithm through the optimization of a multivariable reaction involving the arylation of a deactivated olefin with an arenediazonium salt. The great flexibility of our optimization method allows to fine-tune experimental conditions according to three different objective functions: maximum yield, highest throughput, and lowest production cost. The beneficial properties of flow reactors associated with the power of intelligent algorithms for the fine-tuning of experimental parameters allowed the reaction to proceed in astonishingly simple conditions unable to promote the coupling through traditional batch chemistry.
Режим доступа: по договору с организацией-держателем ресурса
DOI:10.1021/acs.oprd.6b00310