Electron Paramagnetic Resonance Detection of Singlet Oxygen: Opportunities and Pitfalls of Sterically Hindered Amine Trapping Agents
Bibliographic record
Abstract
Singlet oxygen ( 1 O 2 ), a nonradical reactive oxygen species, has shown great potential for driving redox reactions. Electron paramagnetic resonance (EPR) spectroscopy has become a widely utilized tool for identifying the adducts formed by 1 O 2 with sterically hindered amines and indirectly determining the concentrations of 1 O 2 . However, the characteristic 1:1:1 triplet EPR signal of 1 O 2 adduct can arise from other molecules and impurities. In this work, we demonstrate the presence of N ‐oxyl impurities in commercial 2,2,6,6‐tetramethylpiperidine (TEMP) derivatives can lead to overestimation of 1 O 2 in redox systems. Additionally, the relatively low water solubility of TEMP may cause underestimation of 1 O 2 in aqueous media, while more soluble 4‐substituted derivatives (4‐amino, 4‐oxo, and 4‐hydroxy TEMP) undergo untargeted oxidation, forming products besides their corresponding N ‐oxyl derivatives. This study proposes vacuum distillation of TEMP to minimize paramagnetic impurities and recommend the combined use of EPR and mass spectrometry (MS) for accurate identification of N ‐oxyl adducts, particularly for 4‐substituted TEMP in aqueous media. Our findings on the solubility and oxidation behavior of TEMP derivatives provide an improved and robust detection and quantification strategy of singlet oxygen ( 1 O 2 ) in aqueous environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".