Experimental and DFT investigation of electronic structure, defect states, and visible luminescence in Co-doped ZnO nanocrystals
Bibliographic record
Abstract
We report on surface defects, electronic structure, and visible luminescence in pristine and Co-doped ZnO nanocrystals (NCs) by combining experimental characterization with density functional theory (DFT) calculations. Co doping notably reduced the crystallite size (25–18 nm) and nearly doubled the dislocation density (δ), indicating a decline in crystal quality. X-ray photoelectron spectroscopy (XPS) confirmed the incorporation of Co ions in a high-spin Co2+ (3d7, e4t23) configuration, with no detectable traces of Co3+ or metallic Co0 clusters. Photoluminescence (PL) spectra exhibited a dominant blue emission (2.7–2.8 eV), primarily due to electron transitions from the conduction band to zinc vacancy (VZn) acceptor states, further enhanced by Co-induced defects. A strong correlation between the experiment and DFT (Perdew–Burke–Ernzerhof generalized gradients approximation + U with mBJ corrections) elucidates the defect states responsible for visible emission. Our findings show how local atomic defects tune the optical properties and highlight the potential of Co-doped ZnO nanocrystals for blue light-emitting diode applications.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".