Excellent low temperature passivation scheme with reduced optical absorption for back amorphous-crystalline silicon heterojunction (BACH) photovoltaic device
Bibliographic record
Abstract
Low temperature processing of silicon photovoltaic (PV) solar cells with excellent passivation quality enables the effective use of ultra-thin wafers for solar cell manufacturing, thus paving the way for high-efficiency low-cost silicon photovoltaics. This article presents Back Amorphous-Crystalline Silicon Heterojunction (BACH) cell performance using low temperature (x) dual layer passivation scheme. The cell performance is also compared with the BACH cells fabricated using intrinsic hydrogenated amorphous silicon (i-aSi:H) and PECVD SiNxlayer passivation. Reduced optical absorption in the native oxide-SiNxpassivation layer resulted in a higher short-circuit current, JSC, compared to the i-aSi:H-SiNxpassivated cells. The fill-factor also improved for the native oxide-SiNxpassivated cells owing to the improved transport properties. The i-aSi:H-SiNxpassivated cells exhibited optimum cell performance of 10.9% efficiency with VOCof 598.7 mV, JSCof 34.3 mA/cm2and fill-factor of 0.531. In contrast, a maximum cell efficiency of 16% is obtained for native oxide-SiNxpassivated cells with VOCof 651 mV, JSCof 35.4 mA/cm2and fill-factor of 0.694 for a 1 cm2untextured cell (all measurements having been performed under AM 1.5 global spectrum illumination). The above untextured cell performance is a record efficiency for a back amorphous-crystalline silicon heterojunction PV device synthesized using all low temperature processes, exceeding the previously reported highest cell efficiency of ~15%.
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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".