Noninjection, One-Pot Synthesis of Photoluminescent Colloidal Homogeneously Alloyed CdSeS Quantum Dots
Bibliographic record
Abstract
Colloidal photoluminescent CdSeS quantum dots (QDs) were readily prepared via a noninjection, one-pot approach, with air-stable compounds cadmium acetate dihydrate (Cd(OAc) 2 ·2H 2 O), elemental selenium (Se), and elemental sulfur (S) as Cd, Se, and S source compounds, respectively. The homogeneously alloyed CdSeS QDs were synthesized at 240 °C in a reaction flask containing the source compounds together with myristic acid, 2,2′-dithiobisbenzothiazole (MBTS), and 1-octadecene (ODE). All of these chemicals were loaded at room temperature with this newly developed approach. The effects of Cd/Se/S and S/MBTS feed molar ratios affecting the growth of the CdSeS QDs were investigated, via monitoring the temporal evolution of the optical properties (namely, absorption and emission) of the growing nanocrystals. The resulting ternary nanocrystals can be tuned easily to emit in the range of 470−550 nm of the electromagnetic spectrum; such an emission window is hard to manage with binary CdS and CdSe QDs alone. The bandgap engineering was accomplished readily via tuning the different Cd/Se/S and S/MBTS feed molar ratios. High Cd/Se/S feed molar ratios lead to an increase in both size and Se composition of the resulting CdSeS nanocrystals and, thus, a small bandgap; it is the composition that plays a relatively important role as compared to the size. Low S/MBTS feed molar ratios also lead to CdSeS QDs with a small bandgap, which is due to a high S activity, resulting in a fast growth in size. The CdSeS QDs were characterized by TEM, XPS, and XRD: they are homogeneous alloys with a cubic crystal structure. This noninjection, one-pot approach developed in our laboratories, which is the first regarding the synthesis of CdSeS QDs, features easy handling and large-scale production with excellent synthetic reproducibility.
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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 | 0.000 |
| 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) | 0.001 | 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".