22.2 % All-Aluminum Screen-Printed Silicon Solar Cells
Bibliographic record
Abstract
In this work, we present our current development status for all-aluminum screen-printed poly-Si on oxide p-type back junction solar cells. This cell type already features an aluminum front grid which forms locally p+-type layers to collect holes. For the rear side metallization, we use special aluminum-silicon (Al-Si) alloy pastes to locally contact the n+-type poly-Si after opening the dielectric layer by laser ablation. We compare two different glass frits (A and B) and two different concentrations of silicon in the pastes (low and high). Totally, three pastes are used for rear side metallization: (1) Al-Si paste with low Si and glass frit system A, (2) Al-Si paste with low Si and glass frit system B and (3) Al-Si paste with high Si and glass frit system A. The front and rear side of our solar cells were printed and fired separately. The glass frit system B in paste 2, results in reduced shunt resistance of below 5 kΩ∙cm², negatively influencing the open circuit voltage. The high silicon content in paste 3 prevents local shunting in the cells, consequently reducing the series resistance and leading to a fill factor gain of more than 3 %abs compared to the other pastes. Our best Ag-free solar cell shows a power conversion efficiency of 22.2 % with an open circuit voltage of 718 mV and was printed using the high-Si amount paste. In a simulation-based synergistic efficiency gain analysis, we identify the rear side recombination at the contacts and the front grid shading as the two dominant factors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".