Multiway data analysis approach toward understanding of photoluminescence and energy transfer in carbon nanodots
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this study, dilution analysis and anion exchange chromatography (AEC) were employed to provide insights into the photoluminescence (PL) of carbon nanodots (CNDs). A stepwise dilution process revealed that some of the fluorophores with higher energy emission were quenched in the high concentration solution and appeared in the dilute solutions. AEC fractionation led to seven sorts of CND fractions with similar surface charges. The fractionation for this CND mixture showed that excitation wavelength dependence was lower for separated CND particles. The wavelength dependence of excitation spectra could be due to energy exchange between particles that was reduced in diluted solutions and separated fractions. Multivariate analysis of AEC's data demonstrated that there were five distinct fluorophores, which formed the total CND emission. It is interesting that none of these fluorophores had a clear contribution to the surface charge of the CND particles. Further characterization through FTIR spectroscopy and 1 H NMR revealed that optical properties of CNDs did not follow the surface functional groups in CNDs. This situation means that the optical behaviour of particles and their fluorophores differed depending on the surface functional groups.
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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 | 0.001 |
| 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 it