Colloidal CdSe Nanocrystals from Tri-n-Octylphosphine: Part II: Control of Growth Rate for High Quality and Large-Scale Production by Tuning Cd-to-Se Stoichiometry
Bibliographic record
Abstract
Colloidal CdSe nanocrystals were synthesized in reaction media consisting of tri-n-octylphosphine (TOP) without addition of other species; the single-step approach used cadmium oxide (CdO) and TOPSe as Cd and Se sources, respectively. The temporal evolution of the optical properties of the growing TOP-capped CdSe nanocrystals was monitored for a couple of hours, showing that there are two distinguishable stages of growth: an early stage (less than 5 minutes) and a later stage; the growth kinetics of the two stages is a function of the Cd-to-Se precursor molar ratios. A rational choice of 2-6Cd-to-1Se molar ratio was found, based on the temporal evolution of the photoluminescent (PL) efficiency (studied as PL intensity and sensitivity to the media of dispersion, and non-resonant Stokes shifts). For a 2Cd-to-1Se synthesis, the growth in size was slow in the early stages and became fast in the later stages; this fast-later-stage feature could be suppressed by going to a synthesis with a 4-6Cd-to-1Se mole ratio: the nanocrystals between 0.5-60 min growth time exhibit very much similar optical properties, with less than 19 nm redshift of bandgap absorption and emission occurring. Thus, the synthetic route developed here, with a rational 4-6Cd-to-1Se molar ratio, enables us to produce high-quality CdSe nanocrystals on a large-scale with a high degree of synthetic reproducibility. The insights gained facilitate a deeper understanding of the concept of what constitutes high-quality nano-crystals: high PL efficiency resulting from a low growth rate, which can be thoroughly and readily investigated by the red-shift rate of the band-gap peak positions; in addition, the insights gained help us to define a proper synthetic approach for large-scale production with high-quality product.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".