Large‐Area PEDOT:PSS/c‐Si Heterojunction Solar Cells With Screen‐Printed Metal Contacts
Bibliographic record
Abstract
A large‐area BackPEDOT solar cell with a phosphorus‐diffused emitter and a high‐temperature‐fired screen‐printed Ag grid on the front surface and PEDOT:PSS as hole‐collecting and passivating layer at the cell rear is developed. As base material, 15.6 × 15.6 cm2pseudo‐square industrial‐type boron‐dopedp‐type Czochralski‐grown silicon wafers are used. The set‐peak firing temperature (Tset) is varied from 850 to 870 °C with a total number of 32 processed solar cells. The optimumTsetof 870 °C results in a median solar cell efficiency of 19.0%. The best large‐area BackPEDOT solar cell achieves an efficiency of 20.2%. Based on external quantum efficiency measurements, a rear surface recombination velocitySrear < 70 cm s−1is determined, a value which is on a par with today's industrial high‐efficiency solar cells. Furthermore, a low‐temperature metal paste is introduced, which is shown to be capable of metalizing the PEDOT:PSS‐covered rear surface of the solar cells without damaging the rear surface passivation. The principle feasibility of such a rear metallization scheme is demonstrated. The parasitic absorption of infrared light within the PEDOT:PSS layer is identified as the major loss mechanism in the current cells, which might be overcome in the future by adding infrared‐transparent additives to the PEDOT:PSS dispersion.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".