Atomic-level 2-dimensional chemical mapping and imaging of individual dopants in a phosphor crystal
Bibliographic record
Abstract
The ability to visualize and identify individual dopants, as well as measure their local physical and chemical environments in a bulk, provides deep insight for designing new functional materials and predicting their properties. However, a full understanding of dopants inside a solid has been limited by currently available characterization techniques. We demonstrate the first atomic-level 2-dimensional elemental maps of Pr dopants using the electron energy-loss spectroscopy (EELS) technique and we image Al dopants located in a lattice. Based on spectroscopic and imaging evidence we provide plausible local defect configurations of implanted Pr(+) and Al(+) ions within SrTiO3 single crystals. Our results demonstrate the detection of single Pr atoms and the formation of Al-rich nanoscale clusters ranging from 1 to 3 nm in size randomly distributed in the implanted lattice. These results provide insight into the mechanism of red light emission in doped SrTiO3.
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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 | 0.000 |
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".