Fluorescence Behavior and Mechanisms of Poly(ethylene glycol) and Their Applications in Fe<sup>3+</sup> and Cr<sup>6+</sup> Detections, Data Encryption, and Cell Imaging
Bibliographic record
Abstract
In contrast to conventional fluorescent polymers featured by large conjugation structures, a new class of fluorescent polymers without any conjugations is gaining great interest in immerging applications beyond the possibility to achieve by the conjugated polymers. Poly(ethylene glycol) (PEG), widely used in biomedical fields for a long time owing to its nontoxicity and nonimmunogenicity, is found to be fluorescence emissive in the solid state and in aqueous solution, though deemed as not fluorescent in numerous reports. Through systematic study under different conditions, the emission is ascribed to the cluster formation of its chains; thereby the blue-shift of the emission with the excitation wavelength was interpreted through the Förster resonance energy transfer. The clusterization was ascertained through size measurements, Fourier transform infrared spectroscopy, NMR analyses, and the dependence on temperature, pH, and nonsolvent presence. Tested in the presence of competitive metal ions, selective emission quenching by Fe3+ and Cr6+ was observed. PEG was used as a sensor for the detection of Cr6+, Fe3+, and H2O2, outperforming most of the reported sensors alike. Its uses for data encryption and cell imaging were also presented. This work provides therefore a novel face of PEG with great potential in a variety of emerging applications, in particular, as sensors in the biomedical area.
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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 | 0.000 |
| 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".