Singlet-oxygen reactions sensitized on solid surfaces of lignin or titanium dioxide: Product studies from hindered secondary amines and from lipid peroxidation
Bibliographic record
Abstract
Product analyses and kinetic methods were used to determine the role of singlet oxygen in lignin-catalyzed oxidations of organic substrates. Method A used the ESR analysis of nitroxide radicals formed by singlet oxygen (Type II) on 2,2,6,6-tetramethylpiperidine, 1, or tetramethylpiperidone, 2. Method B used HPLC analysis of the 9- and 13-linoleate chain hydroperoxides formed on oxidation of methyl linoleate to distinguish free-radical peroxidation (Type I) from singlet-oxygen oxidation (Type II) on the basis of different cis,trans (kinetic) to trans,trans (thermodynamic) product ratios. Applications of method A to solid dispersions of lignin or titanium dioxide (TiO 2 , a known singlet-oxygen sensitizer) indicated singlet-oxygen reactions. In addition to the nitroxide triplet, irradiation of lignin produces a persistent broad signal in the solid attributed to phenoxyl radicals. Benzophenone and 3,5-di-tert-butyl-ortho-benzoquinone, 5, coated on silica gel were used as models to compare the effects of irradiating such compounds on the products and kinetics of methyl linoleate oxidation. Benzophenone acted as an initiator, giving free-radical peroxidation, whereas 5 or lignin coated with methyl linoleate acted as singlet-oxygen sensitizers, according to both product studies (method B) and the kinetic order in oxygen consumption during UV photolysis. Photolysis of phase-separated sensitizer (TiO 2 or lignin) and substrate (methyl linoleate) resulted in typical singlet-oxygen products. These results indicate that singlet oxygen plays a significant role in the photo-yellowing of high-lignin-content wood pulps. Key words: lignin, singlet oxygen, mechanism, peroxidation, products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".