Plasma etching applications in concentrated photovoltaic cell fabrication
Bibliographic record
Abstract
Photovoltaic cells are conventionally electrically isolated (isolation) and then separated from the wafer (singulation) by saw dicing at the end of the fabrication process. However, saw dicing presents limitations in terms of cell shapes and causes excessive material losses. We propose isolation and singulation by plasma etching as an alternative to saw dicing. The etching process proposed also allows via hole etching for through cell via contacts (TCVC) [1]. This technology uses isolated metallized vias to carry front-side generated carriers to the backside. This new architecture could increase the efficiency and increase the energy production per wafer for concentrated photovoltaic (CPV) cells. In this paper, those two plasma etching applications for CPV cell fabrication are discussed. More precisely, triple junction solar cells have been fabricated with either a plasma singulation or with via holes and compared with reference cells (without via hole and saw dicing singulation). One sun IV measurements, external quantum efficiency (EQE) and 100 suns IV characteristics show that no performance losses can be observed on cells with plasma singulation. Via hole etching induces open circuit voltage (VOC) and fill factor (FF) losses below 3 % that can be recovered with a surface passivation.
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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 | 0.001 | 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".