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Radical Autoxidation01:20

Radical Autoxidation

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The oxidation of an organic compound in the presence of air or oxygen is called autoxidation. For example, cumene reacts with oxygen to form hydroperoxide. Autoxidation involves initiation, propagation, and termination steps. Many organic compounds are susceptible to autoxidation—especially ethers in the presence of oxygen, which form hydroperoxides. Even though this reaction is slow, old ether bottles contain small amounts of peroxide, which leads to laboratory explosions during ether...
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Radicals, the highly reactive species, gain stability by undergoing three different reactions. The first reaction involves a radical-radical coupling, in which a radical combines with another radical, forming a spin‐paired molecule. The second reaction is between a radical and a spin‐paired molecule, generating a new radical and a new spin‐paired molecule. The third reaction is radical decomposition in a unimolecular reaction, forming a new radical and a spin‐paired...
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Radicals adjacent to electron-donating groups are called nucleophilic radicals. These radicals readily react with electrophilic alkenes. The SOMO–LUMO interactions are the driving force for the reaction, where the high-energy SOMO of the electron-rich, nucleophilic radicals interacts with the low-energy LUMO of the electron-deficient, electrophilic alkenes. Such SOMO–LUMO interactions are the basis of reactive radical traps, affecting the selectivity in radical reactions. For...
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The radical chain-growth polymerization mechanism consists of three steps: initiation, propagation, and termination of polymerization. The polymerization initiates when a free radical generated from the radical initiator adds to the unsaturated bond in the monomer. The unpaired electron of the free radical and one π electron in the unsaturated bond creates a σ bond between the free radical and the monomer. As a result, the other π electron in the unsaturated bond converts this...
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Oxidation and Reduction of Organic Molecules01:19

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Energy production within a cell involves many coordinated chemical pathways. Most of these pathways are combinations of oxidation and reduction reactions, which occur at the same time. An oxidation reaction strips an electron from an atom in a compound, and the addition of this electron to another compound is a reduction reaction. Because oxidation and reduction usually occur together, these pairs of reactions are called redox reactions.
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Area of Science:

  • Environmental Chemistry
  • Computational Chemistry
  • Chemical Kinetics

Background:

  • Machine learning (ML) offers potential for new insights into organic structure effects on reactive oxygen species (ROS) oxidation.
  • Interpreting ML models remains a challenge for understanding underlying chemical mechanisms.

Purpose of the Study:

  • To develop interpretable ML models for predicting second-order rate constants (k•OH) between hydroxyl radicals (•OH) and organic compounds.
  • To identify key organic structural features influencing these reaction rates.
  • To develop a rapid method for judging reaction mechanisms.

Main Methods:

  • Development of interpretable machine learning models.
  • Prediction of second-order rate constants (k•OH).
  • Application of unsupervised learning for clustering organic compounds based on reaction mechanisms.

Main Results:

  • Identified highest occupied molecular orbital energy (E_HOMO), number of aromatic rings (N_AR), and number of carbon atoms (N_C) as significant factors impacting k•OH.
  • Established a positive correlation between k•OH and E_HOMO, linked to electrophilic reactions.
  • Observed relationships between k•OH, N_AR, and N_C related to reactive sites.
  • Developed a clustering method to categorize organics into three groups for rapid mechanism judgment.
  • Extended the methodology to reactions involving sulfate radicals.

Conclusions:

  • Interpretable ML provides a rational model for predicting reaction mechanisms in ROS oxidation.
  • Organic molecular structure significantly influences reaction kinetics with hydroxyl and sulfate radicals.
  • Big data approaches enhance understanding of structure-reactivity relationships in environmental chemistry.