Experimental evidence of parasitic shunting in silicon nitride rear surface passivated solar cells
Bibliographic record
Abstract
Abstract Many solar cells incorporating SiNxfilms as a rear surface passivation scheme have not reached the same high level of cell performance as solar cells incorporating high‐temperature‐grown silicon dioxide films as a rear surface passivation. In this paper, it is shown by direct comparison of solar cells incorporating the two rear surface passivation schemes, that the performance loss is mainly due to a lower short‐circuit current while the open‐circuit voltage is equally high. With a solar cell test structure that features a separation of the rear metal contacts from the passivating SiNxfilms, the loss in short‐circuit current can be reduced drastically. Besides a lower short‐ circuit current, dark I–V curves of SiNxrear surface passivated solar cells exhibit distinct shoulders. The results are explained by parasitic shunting of the induced floating junction (FJ) underneath the SiNxfilms with the rear metal contacts. The floating junction is caused by the high density of fixed positive charges in the SiNxfilms. Other two‐dimensional effects arising from the injection level dependent SRV of the Si/SiNxinterfaces are discussed as well, but, are found to be of minor importance. Pinholes in the SiNxfilms and optical effects due to a different internal rear surface reflectance can be excluded as a major cause for the performance loss of the SiNxrear surface passivated cells. Copyright © 2002 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) | 0.003 | 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".