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Oxidation of secondary hydroperoxides via αC–H abstraction to form ketones and hydroxyl radicals: fluorene autoxidation as a model system

Publication: Canadian Journal of Chemistry
20 September 2023

Abstract

Organic and biological molecules with relatively weak C–H bonds can react with O2 via a free-radical reaction called autoxidation. The primary products of these peroxyl-radical-driven reactions are hydroperoxides, R2CHOOH. If autoxidation continues, the secondary oxidation of hydroperoxides is known to form ketones, R2C═O, but this mechanism is not well characterized. Importantly, we find that ketone formation produces a highly reactive hydroxyl radical, HO. We can trap HO using benzene as a solvent to form quantifiable amounts of phenol. Fluorene was chosen as a model system to study this secondary oxidation in great detail. Kinetic modeling allowed the measurement of rate constants for the primary and secondary autoxidation reactions as 11.3 and 25 mol L−1s−1, respectively. Density functional theory modeling likewise predicts a faster oxidation for the secondary autoxidation. This type of kinetic measurement and modeling approach could be useful to study the autoxidation of plastics, petrochemicals, and lipids.

Graphical Abstract

Résumé

Les molécules organiques et biologiques avec des liaisons C–H relativement faibles peuvent réagir avec l'O2 via une réaction radicalaire appelée auto-oxydation. Les principaux produits de ces réactions induites par les radicaux peroxyles sont les hydroperoxydes, R2CHOOH. Si l'auto-oxydation se poursuit, l'oxydation secondaire des hydroperoxydes peut former des cétones, R2C=O, mais ce mécanisme n'est pas bien caractérisé. Nous proposons que la formation de cétone produit un radical hydroxyle hautement réactif, HO. Nous pouvons piéger ce HO en utilisant le benzène comme solvant pour former des quantités quantifiables de phénol. Le fluorène a été choisi comme système modèle pour étudier en détail cette oxydation secondaire. La modélisation cinétique a permis la mesure des constantes de vitesse pour les réactions d'auto-oxydation primaires et secondaires de 11,3 et 25 mol L−1s−1, respectivement. La modélisation DFT prédit également une oxydation plus rapide pour l'auto-oxydation secondaire. Cette approche de mesure et de modélisation cinétique pourrait être utilisée pour étudier l'auto-oxydation des plastiques, des produits pétrochimiques et des lipides. [Ceci est une traduction fournie par l’auteur du résumé en anglais]

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Supplementary material

Supplementary Material 1 (DOCX / 1.92 MB).

Information & Authors

Information

Published In

cover image Canadian Journal of Chemistry
Canadian Journal of Chemistry
Volume 102Number 1January 2024
Pages: 1 - 6

History

Received: 29 March 2022
Accepted: 28 June 2022
Accepted manuscript online: 26 July 2023
Version of record online: 20 September 2023

Data Availability Statement

Data available within the article and supplementary files.

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Key Words

  1. free radical autoxidation
  2. kinetics
  3. peroxyl radical
  4. fluorene
  5. physical organic chemistry

Authors

Affiliations

Mélanie Sollin
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Data curation, Formal analysis, Validation, Writing – original draft, and Writing – review & editing.
A version of this article was previously included in an M.Sc. dissertation by the manuscript’s first author, Mélanie Sollin.19
Seyedehsan Hosseininasab
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, and Writing – review & editing.
Jason Malenfant
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Formal analysis, Software, Validation, and Visualization.
Mohamed El-Akhrass
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Data curation, Formal analysis, Methodology, Validation, and Writing – review & editing.
Amaia Lopez de Arbina
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Data curation, Formal analysis, and Validation.
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Data curation, Formal analysis, and Methodology.
Département de Chimie, NanoQAM et Centre Québecois sur les Matériaux Fonctionnels, Université du Québec à Montréal, Montréal, QC H2X 2J6, Canada
Author Contributions: Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, and Writing – review & editing.

Author Contributions

Conceptualization: MF
Data curation: MS, SH, ME, ALDA, AM
Formal analysis: MS, SH, JM, ME, ALDA, AM, MF
Funding acquisition: SH, MF
Investigation: SH
Methodology: SH, ME, AM, MF
Project administration: MF
Resources: MF
Software: JM
Supervision: SH, MF
Validation: MS, SH, JM, ME, ALDA, MF
Visualization: SH, JM, MF
Writing – original draft: MS, SH, MF
Writing – review & editing: MS, SH, ME, MF

Competing Interests

The authors declare there are no competing interests.

Funding Information

NSERC: RGPIN-2016-06773

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