Computational Study of a Copper-Catalyzed Synthesis of Fluoroalcohols from Alkylboranes and Ketones

Fluoroalcohols are a class of organic compounds containing one or more fluorine atoms together with an alcohol group in their molecular structure. These fluorinated species have a wide range of applications due to their unique properties and are used in medicine and electronics. Herein, we propose a...

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Detalles Bibliográficos
Autores: Gómez-Mudarra, Francisco A., Aullón López, Gabriel, Jover Modrego, Jesús
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/224132
Acceso en línea:https://hdl.handle.net/2445/224132
http://hdl.handle.net/2445/224132
Access Level:acceso abierto
Palabra clave:Reaccions d'addició
Cetones
Hidrocarburs
Addition reactions
Ketones
Hydrocarbons
Descripción
Sumario:Fluoroalcohols are a class of organic compounds containing one or more fluorine atoms together with an alcohol group in their molecular structure. These fluorinated species have a wide range of applications due to their unique properties and are used in medicine and electronics. Herein, we propose a new synthetic procedure, promoted by a copper(I) catalyst, for preparing fluoroalcohols from alkylboranes and symmetric ketones. The reaction has been computationally explored to propose a plausible mechanism, which allows identifying the rate-limiting step and quantitatively evaluating the electronic effects of each substrate on the overall reactivity. These DFT calculations suggest that the combination of electron-poor ketones with electron-rich alkylboranes produce the most efficient catalytic systems for preparing fluoroalcohols. Microkinetic modeling of the studied systems allow the prediction of the activation barrier limit to achieve fully functional reactions and multilinear regression techniques provide a methodology to estimate the overall reaction barriers in a simple manner, opening the way for proposing new catalytic systems.