Fluorescence Intermittency Limits Brightness in CdSe/ZnS Nanoparticles Quantified by Fluorescence Correlation Spectroscopy
Bibliographic record
Abstract
Traditional fluorophores often impose inconvenient limitations because of their narrow excitation spectra, broad emission bands, and significant photobleaching. Quantum dots (QDs) have grown in popularity because of their high emission quantum yields, broad absorbance spectra, and narrow, tunable emission spectra. Here, coated CdSe/ZnS QDs with emission maxima at 496 nm (T2−496), ∼520 nm (QD520), and ∼560 nm (QD560 and Qdot565) were characterized while freely diffusing in solution using confocal fluorescence correlation spectroscopy (FCS) and were compared with well-known fluorophores such as Alexa 488 to reveal critical photophysical properties. Comparisons are made between dots synthesized by similar methods (QD520 and QD560 nm) differing in their emission spectra and outer coating for biofunctionalization. The same photophysical principles also describe the T2−496 and Qdot565 dots, which were synthesized by different, proprietary methods. All of the tested QDs had larger hydrodynamic radii and slower diffusion coefficients than Alexa 488 and underwent numerous transitions between bright and dark states, especially at high illumination intensities, as described here by a new FCS fitting function. The QDs with the fastest transitions between the bright and dark states had the lowest average occupancies in dark states and correspondingly higher maximum brightness per particle. Although these QDs were in some cases brighter than Alexa at low excitation intensities, the QDs saturated at lower intensities than did Alexa and had generally somewhat lower maximum brightness per particle, except for the Qdot565s. Thus, it appears that intermittency (at least in part) limits maximum brightness in QDs, despite the potential for high fluorescence emission rates that is expected from their large extinction coefficients. These results suggest possibilities for significant improvement of QDs for biological applications by adjustments of manufacturing techniques and environmental conditions.
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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 | 0.001 | 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 | 0.001 | 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".