Competitive gettering of iron in silicon photovoltaics: Oxide precipitates versus phosphorus diffusion
Bibliographic record
Abstract
Experiments have been conducted to understand the behaviour of iron in silicon containing oxide precipitates and associated defects (dislocations and stacking faults), which is subjected to phosphorus diffusion gettering. Injection-dependent minority carrier lifetime measurements are analysed to provide quantitative information on the degree to which the precipitates and associated defects are decorated with iron impurities. These data are correlated with bulk iron measurements based on the photodissociation of FeB pairs. Iron in the vicinity of oxide precipitates in samples with relatively low levels of bulk iron contamination (< 5 × 1012 cm−3) can be gettered to some extent. Higher levels of bulk iron contamination (> 1.2 × 1013 cm−3) result in irreversible behaviour, suggesting iron precipitation in the vicinity of oxide precipitates. Bulk iron is preferentially gettered to the phosphorus diffused layer opposed to the oxide precipitates and associated defects.
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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) | 0.001 | 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".