A comparative study of band structures and quantum confinement effects in graphene and nitrogen-doped carbon quantum dots
Bibliographic record
Abstract
Graphene quantum dots (GQDs) and carbon quantum dots (CQDs) are promising nanomaterials with tunable electronic and optical properties influenced by quantum confinement effects and structural morphology. In this study, the band structures of GQDs and nitrogen-doped CQDs (N-CQDs) were compared to elucidate how particle size, structure, and synthesis methods affect their electronic properties. GQDs were synthesized via electrochemical exfoliation, allowing size control through current density adjustments, while N-CQDs were synthesized hydrothermally with citric acid and urea as precursors to ensure compositional similarity. Transmission electron microscopy, photoluminescence spectroscopy, UV–Vis spectroscopy, and synchrotron-based X-ray photoelectron spectroscopy were employed to characterize particle sizes, band structures, and semiconductor behavior. Results indicate that GQDs exhibit stronger quantum confinement than N-CQDs, attributed to their sp 2 -hybridized, two-dimensional structures, which supports lateral electron mobility and increased axial quantum confinement. Furthermore, GQDs exhibited n-type semiconductor behavior, while N-CQDs displayed p-type characteristics, underscoring a fundamental difference in charge transport mechanisms. These findings highlight the critical role of structural and morphological factors in tuning the electronic properties of quantum dots, offering insights into the design of nanomaterials for optoelectronic 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) | 0.000 | 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".