Donor ionization in size controlled silicon nanocrystals: The transition from defect passivation to free electron generation
Bibliographic record
Abstract
We studied the photoluminescence spectra of silicon and phosphorus co-implanted silica thin films on (100) silicon substrates as a function of isothermal annealing time. The rapid phase segregation, formation, and growth dynamics of intrinsic silicon nanocrystals are observed, in the first 600 s of rapid thermal processing, using dark field mode X-TEM. For short annealing times, when the nanocrystal size distribution exhibits a relatively small mean diameter, formation in the presence of phosphorus yields an increase in the luminescence intensity and a blue shift in the emission peak compared with intrinsic nanocrystals. As the mean size increases with annealing time, this enhancement rapidly diminishes and the peak energy shifts further to the red than the intrinsic nanocrystals. These results indicate the existence of competing pathways for the donor electron, which depends strongly on the nanocrystal size. In samples containing a large density of relatively small nanocrystals, the tendency of phosphorus to accumulate at the nanocrystal-oxide interface means that ionization results in a passivation of dangling bond (Pb-centre) type defects, through a charge compensation mechanism. As the size distribution evolves with isothermal annealing, the density of large nanocrystals increases at the expense of smaller nanocrystals, through an Ostwald ripening mechanism, and the majority of phosphorus atoms occupy substitutional lattice sites within the nanocrystals. As a consequence of the smaller band-gap, ionization of phosphorus donors at these sites increases the free carrier concentration and opens up an efficient, non-radiative de-excitation route for photo-generated electrons via Auger recombination. This effect is exacerbated by an enhanced diffusion in phosphorus doped glasses, which accelerates silicon nanocrystal growth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".