A Two‐Pathway Model for the Evolution of Colloidal Compound Semiconductor Quantum Dots and Magic‐Size Clusters
Bibliographic record
Abstract
A fundamental understanding of formation pathways is critical to the controlled synthesis of colloidal semiconductor nanocrystals. As ultrasmall-size quantum dots (QDs) sometimes emerge in reactions along with magic-size clusters (MSCs), distinguishing their individual pathway of evolution is important, but has proven difficult. To decouple the evolution of QDs and MSCs, an unconventional, selective approach has been developed, along with a two-pathway model that provides a fundamental understanding of production selectivity. For on-demand production of either ultrasmall QDs or MSCs, the key enabler is in how to allow a reaction to proceed in the time prior to nucleation and growth of QDs. In this prenucleation stage, an intermediate compound forms, which is the precursor compound (PC) to the MSC. Here, the two-pathway model and the manipulation of such PCs to synthesize either ultrasmall QDs or binary and ternary MSCs are highlighted. The two-pathway model will assist the development of nucleation theory as well as provide a basis for a mechanism-enabled design and predictive synthesis of functional nanomaterials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".