Effect of dissociation of iron–boron pairs in crystalline silicon on solar cell properties
Bibliographic record
Abstract
Abstract The effect of dissociation of interstitial iron‐substitutional boron (FeiBs) pairs, as it occurs under illumination in iron‐contaminated silicon solar cells, on the solar cell properties has been studied on the basis of numerical device simulations using reported recombination parameters for Fei and FeiBs. Most cell parameters are found to degrade during FeiBs dissociation. However, the open‐circuit voltage can also increase within certain ranges of the iron concentration. Critical iron concentrations are determined, giving the threshold contamination level above which a significant degradation in the corresponding cell parameter can be observed. The threshold iron contamination level of the open‐circuit voltage degradation is found to be up to two orders of magnitude larger than the threshold iron level of the short‐circuit current degradation. As the behaviour of the cell parameters under illumination is specific to the dissociation of FeiBs pairs, the characteristic changes in the cell parameters due to illumination may be used as a simple way of identifying iron contamination problems in silicon solar cells. Copyright © 2005 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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".