Correlation between Material Properties, Crystalline Transitions, and Point Defects in RF Sputtered (N,Mg)-Doped Copper Oxide Thin Films
Bibliographic record
Abstract
In the present work, we investigate the effects of N and Mg doping on the optical and electrical properties of Cu 2 O thin films deposited using radiofrequency magnetron sputtering at room temperature. Additionally, crystalline phases are studied through complementary X-ray diffraction and energy dispersive X-ray spectroscopy measurements. It is shown that nitrogen incorporation enhances both the electrical and optical properties, with resistivity reaching a value as low as 1.15 Ωcm and an average transmittance in the visible range of 31.74%. Raman spectroscopy measurements indicate an increase in the number of (N 2 ) Cu shallow acceptor point defects, explaining the probed enhancement of p-type majority charge carriers. Also, in Mg-doped samples, marginal improvement of the optoelectrical properties is established. Conversely, we demonstrate that co-doping with Mg and N degrades the material crystallinity, leading to a reduction of thin film conductivity that could be attributed to high nitrogen incorporation. Subsequently, the influence of dopants on the electrical and optical properties is discussed via the analysis of the correlation between defects and Raman activities in the studied copper oxide thin films. This work contributes to the assessment of Mg and N as doping species, unveiling the dominant behavior of specific point defects. The results obtained in the study can therefore benefit future developments in copper-based p-type semiconducting oxides with enhanced optical and electrical properties.
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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".