Influence of Solder Pads to PERC Solar Cells for Module Integration
Bibliographic record
Abstract
The majority of screen printed solar cells has silver pads at the rear side to enable soldering for the module manufacturing. The pads increase the recombination at the silicon/metal interface due to the absence of a back surface field (BSF) at the solder pads. This reduces the efficiency of full-area Al-BSF solar cells. For passivated emitter and rear cells (PERC), a large area fraction of the rear side is covered with the passivation layer. When using specially designed Ag pastes for the rear side of PERC cells, the passivation of this layer is maintained, and the rear recombination is reduced. A comparison of solar cells with and without solder pads confirms that there is no loss in solar cell performance, both cell types achieve an efficiency of 19.6%. We investigate the influence of solder pads to PERC solar cells by calculating the effective rear surface recombination. The calculations confirm that there is a loss in open circuit voltage of less than 2 mV due to the solder pads. A 54-cell PERC PV module is manufactured. The cell-to-module loss reveals that the module process is still to be optimized. Comparable modules made from 9 solar cells lost less than 1% relative in all J-V parameters after a 1000 h damp-heat test.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".