Synthesis and surface control of colloidal Cr<sup>3 +</sup>-doped SnO<sub>2</sub>transparent magnetic semiconductor nanocrystals
Bibliographic record
Abstract
The synthesis of colloidal Cr(3+)-doped SnO(2) nanocrystals prepared under mild conditions via a hydrolysis method is described. We show by means of nanocrystal surface ligand exchange that even under mild reaction conditions a significant fraction of the dopant ions reside on the nanocrystal surfaces. Two different approaches aimed at achieving internal dopant incorporation-surface-bound dopant complexation and isocrystalline shell growth-are described and compared. While free-standing nanocrystals are paramagnetic, the films prepared from the same nanocrystals exhibit ferromagnetic ordering at room temperature. The measured magnetization is associated with structural defects formed at the interfaces of nanocrystals in their films, and discussed in terms of the defect-related itinerant-electron-mediated mechanism. The observed ferromagnetism is compared to ferromagnetism in Cr(3+)-doped In(2)O(3) nanocrystalline films. These results demonstrate the possibility of controlling surface structure and composition of doped oxide nanocrystals using different approaches. Furthermore, this work emphasizes the importance of surface structure and composition in tailoring properties of doped multifunctional transparent conducting oxide nanostructures.
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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".