Near‐Infrared Fluorescence from Silicon‐ and Nickel‐Based Color Centers in High‐Pressure High‐Temperature Diamond Micro‐ and Nanoparticles
Bibliographic record
Abstract
Abstract Fluorescent color centers in diamond are invaluable room temperature quantum systems in fundamental scientific studies and vital for many emerging applications from inertial navigation to quantum sensing in biology. Yet, controlled production of specific color centers in synthetic diamond at scale remains challenging. Characteristics of silicon‐ and nickel‐based defects with strong fluorescence in the 700–950 nm spectral region formed in Si‐ and Ni‐doped diamond, created via high‐pressure high‐temperature synthesis in commercial quantities without irradiation, are reported. Using electron paramagnetic resonance spectroscopy and fluorescence spectroscopy, the presence of defects including the negatively charged silicon‐vacancy (SiV−), silicon‐boron (SiB) and positively charged substitutional nickel center (Nis+) in micrometer‐sized particles is identified and quantified. The color centers’ optical properties are investigated via time‐resolved and steady‐state fluorescence spectroscopy below 10 K and at room temperature. In ensemble measurements, the particles show no detectable signals from nitrogen‐vacancy (NV−) defects. The particles’ relative fluorescence brightness is quantified and compared to particles containing ≈1 ppm NV− centers. It is demonstrated that the Nis+ center fluorescence characteristics are preserved in 50 nm nanoparticles. The work paves the way for the use of fluorescent nanodiamonds in the first near‐infrared biological window between 700 nm and 950 nm in biomedical 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".