Structural and Optical Analysis of NV Centers in Diamonds Synthesized by MPCVD With Controlled Nitrogen Doping Time
Bibliographic record
Abstract
The magnetic field-dependent fluorescence properties of NV${}^{-}$center defects embedded within a diamond matrix have made them a candidate for solid-state qubits for quantum computing and magnetic field sensing. Microwave plasma-assisted chemical vapor deposition (MPCVD) of diamonds with in situ nitrogen doping has provided reproducibility and uniformity in the production of NV${}^{-}$centers on multiple substrates. What remains to be understood is the impact of the nitrogen doping time on the MPCVD process and its impact on the creation of NV${}^{-}$centers. Analysis of the NV${}^{-}$-containing diamond films has been carried out using X-ray diffraction (XRD), Raman spectroscopy, and optical microscopy. This study aims to investigate the effect of nitrogen doping time and its effect on the produced spectral lines associated with the 1333-cm−1diamond Raman spectra peak, 637-nm photoluminescence NV${}^{-}$spectral peak, and the (111) and (220) diamond XRD peaks. Here, we demonstrate that using a Voigt model to curve fit the 637-nm P-luminescence line produces a method by which the zero phonon line can be measured. Furthermore, the Williamson–Hall plot method provided a relationship between the strain and crystal size of associated films.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".