Free Radical Sensor Based on CdSe Quantum Dots with Added 4-Amino-2,2,6,6-Tetramethylpiperidine Oxide Functionality
Bibliographic record
Abstract
The association and resulting fluorescence quenching of CdSe quantum dots by 4-amino-2,2,6,6-tetramethylpiperidine oxide (4-amino-TEMPO), a persistent nitroxide, have been examined using electron paramagnetic resonance (EPR) and fluorescence spectroscopy. EPR data suggest binding constants around (8 +/- 4) x 10(6) M(-1) for green (2.4-2.5 nm) nanoparticles, and the application of Job's method indicates that the preferred mode of binding involves one or two quencher molecules per quantum dot, although more quenchers could bind at high concentrations of 4-amino-TEMPO. Fluorescence quenching by 4-amino-TEMPO is at least 3 orders of magnitude more efficient than by TEMPO itself, reflecting the strong binding confirmed by the EPR data. Stern-Volmer plots are nonlinear and in light of the EPR data probably reflect ready accessibility of the CdSe surface to one or two 4-amino-TEMPO molecules, while additional quenchers can only bind if they displace trioctylphosphine oxide ligands. Quantum dot-4-amino-TEMPO complexes can be used as free radical sensors, since the fluorescence (quenched by the nitroxide) is readily restored when radicals are trapped to form alkoxyamines.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".