Probe sonication-assisted rapid synthesis of highly fluorescent sulfur quantum dots
Bibliographic record
Abstract
A new type of heavy-metal free single-element nanomaterial, called sulfur quantum dots (SQDs), has gained significant attention due to its advantages over traditional semiconductor QDs for several biomedical and optoelectronic applications. A straightforward and rapid synthesis approach for preparing highly fluorescent SQDs is needed to utilize this nanomaterial for technological applications. Until now, only a few synthesis approaches have been reported; however, these approaches are associated with long reaction times and low quantum yields (QY). Herein, we propose a novel optimized strategy to synthesize SQDs using a mix of probe sonication and heating, which reduces the reaction time usually needed from 125 h to a mere 15 min. The investigation employs cavitation and vibration effects of high energy acoustic waves to break down the bulk sulfur into nano-sized particles in the presence of highly alkaline medium and oleic acid. In contrast to previous reports, the obtained SQDs exhibited excellent aqueous solubility, desirable photostability, and a relatively high photoluminescence QY up to 10.4% without the need of any post-treatment. Additionally, the as-synthesized SQDs show excitation-dependent emission and excellent stability in different pH (2-12) and temperature (20 °C-80 °C) environments. Hence, this strategy opens a new pathway for rapid synthesis of SQDs and may facilitate the use of these materials for biomedical and optoelectronic applications.
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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 | 0.001 |
| 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 | 0.001 |
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 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".