Thin multicrystalline silicon solar cells with silicon nitride front and rear surface passivation
Bibliographic record
Abstract
State-of-the-art multicrystalline silicon (mc-Si) material with minority carrier diffusion lengths exceeding the wafer thickness is commercially available today. It is expected that the diffusion length to wafer thickness ratio will be increasing further due to improved material quality and due to the trend towards thinner wafers to reduce material costs. In order to fully exploit the material quality, a solar cell process that includes excellent rear surface passivation is needed. In this paper we first discuss loss mechanism due to the bulk resistivity of thin wafers, optical losses and losses due to rear surface recombination. Solar cell results for thin mc-Si solar cells with silicon nitride front and rear surface passivation are presented. Experimental results demonstrate that due to the excellent rear surface passivation of our plasma SiN/sub x/ films, the presented solar cell process is capable of improving the solar cell performance with decreasing cell thickness.
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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".