Atomic Identification of Interfaces in Individual Core@shell Quantum Dots
Bibliographic record
Abstract
CdSe@CdS Core@shell quantum dots (QDs) have been widely studied in recent years, due to their architecture which allows to tailor properties by controlling structure and composition. However, since CdSe and CdS have the same crystal structure, same cations, and similar lattice parameters, it is very challenging to image the interface. Herein, high-resolution transmission electron microscopy, high-angle annular dark-field imaging, and energy-dispersive X-ray spectroscopy elemental mapping are combined to characterize the core@shell structure and identify the interface in the CdSe@CdS QDs with different CdS shell thicknesses. By examining changes in lattice spacing in an individual CdSe@CdS quantum dot, the atomic core@shell interface is identified. For thin-shelled QDs, an ideal coherent interface forms between core and shell due to the small lattice mismatch, and the lattice spacing remains unchanged at the core and shell regions. For thick-shelled QDs, the lattice spacing is different at the core and shell regions, while the heterostructured interface is still coherent and cannot be clearly imaged. As the shell thickness further increases, a sharp core@shell interface appears. The results define an approach to characterize the heterostructure of two materials with the same crystalline structure and cations.
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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) | 0.000 | 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 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".