Optoelectronic Properties of Ce<sup>3+</sup> Doped Silicon Oxide and Oxynitride Electroluminescent Devices
Bibliographic record
Abstract
In this work, we propose a new type of silicon-based electroluminescent device. The thin film emitting layers of the device were deposited using Electron-Cyclotron-Resonance Plasma Enhanced Chemical-Vapor Deposition (ECR-PECVD) with in-situ Ce3+ doping on a P-type silicon substrate. Oxygen was gradually substituted by nitrogen to produce silicon oxynitride thin films with different layer compositions. Refractive indices extracted from variable-angle spectroscopic ellipsometry (VASE) measurements classified the thin films into two main groups, silicon oxide (SiOx) and silicon oxynitride (SiOxNy). The thin film composition was studied by Rutherford Backscattering Spectrometry (RBS), verifying the gradual increase in oxygen content. Photoluminescence (PL) spectroscopy of the emitting layer was obtained using a 375 nm laser as an excitation source. All samples were subjected to the post-deposition annealing treatment for 1 hour at different temperatures varying from 600 to 1200°C in 95% N2 and 5% H2 ambient gas environment, yielding considerably stronger blue PL emission than as-deposited ones. PL intensity of SiOx showed a sudden increase due to the formation of Ce2Si2O7 clusters when annealed at 1200°C. Internal Quantum Efficiency (IQE) and External Quantum Efficiency (EQE) were measured using an integrating sphere and a UV-Vis-NIR spectrometer. The optimum layer composition and annealing condition to produce SiOxNy thin films with maximized Ce3+ excitation efficiency were obtained. To further investigate the electrical performance of the produced samples, the thin films were coated with indium tin oxide (ITO) and aluminum (Al) on the top and bottom side of the thin film respectively. Current-Voltage (I-V) measurements showed improved charge injections in SiOxNy compared to SiOx, due to the reduction of the bandgap upon the incorporation of nitrogen.
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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 | 0.001 | 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".