Ultrafast Random‐Pyramid Texturing for Efficient Monocrystalline Silicon Solar Cells
Bibliographic record
Abstract
Herein, an ultrafast random‐pyramid texturing process is proposed for monocrystalline silicon (mono‐Si) solar cells by combining metal‐catalyzed chemical etching (MCCE) and the standard alkaline texturing process. Namely, large numbers of artificial defects are introduced on the wafer surface in 3 min by MCCE; therefore, the process duration of alkaline texturing is largely shortened from 420 s for the as‐cut wafer to 180 s for the wafer with artificial defects due to its high surface reactivity. Moreover, those tiny artificial defects are apt to form small pyramids, resulting in a better light‐trapping performance. As a demonstration, the passivated emitter rear contact solar cell with ultrafast random pyramid texture achieves a power conversion efficiency of 23.02%. Therefore, such a cost‐effective ultrafast texturing strategy can open a promising new route toward the mass production of high‐efficiency industrial mono‐Si solar cells.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".