Separating the two polarities of the POLO contacts of an 26.1%-efficient IBC solar cell
Bibliographic record
Abstract
Abstract By applying an interdigitated back contacted solar cell concept with poly-Si on oxide passivating contacts an efficiency of 26.1% was achieved recently. In this paper the impact of the implemented initially intrinsic poly-Si region between p-type poly-Si and n-type poly-Si regions is investigated. Two recombination paths are identified: The recombination at the interface between the initially intrinsic poly-Si and the wafer as well as the recombination across the resulting p(i)n diode on the rear side which is aimed to be reduced by introducing an initially intrinsic region. By using test structures, it is demonstrated that the width of the initially intrinsic region ((i) poly-Si region) has a strong influence on the recombination current through the p(i)n diode and that this initially intrinsic region needs to be about 30 μm wide to sufficiently reduce the recombination across the p(i)n diode. Lateral and depth-resolved time of flight secondary ion mass spectrometry analysis shows that the high-temperature annealing step causes a strong lateral inter-diffusion of donor and acceptor atoms into the initially intrinsic region. This diffusion has a positive impact on the passivation quality at the c-Si/SiOx/i poly-Si interface and is thus essential for achieving an independently confirmed efficiency of 26.1% with 30 μm-wide initially intrinsic poly-Si regions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".