H<sub>2</sub> plasma treatment at the p/i interface of a hydrogenated amorphous Si absorption layer for high‐performance Si thin film solar cells
Bibliographic record
Abstract
ABSTRACT Plasma treatment (PT) of the buffer layer for highly H2‐diluted hydrogenated amorphous silicon (a‐Si:H) absorption layers is proposed as a technique to improve efficiency and mitigate light‐induced degradation (LID) in a‐Si:H thin film solar modules. The method was verified for a‐Si:H single‐junction and a‐Si:H/microcrystalline silicon (µc‐Si:H) tandem modules with a size of 200 × 200 mm2 (aperture area of 382.5 cm2) under long‐term light exposure. H2 PT at the p/i interface was found to eliminate non‐radiative recombination centers in the buffer layer, and plasma‐enhanced chemical vapor deposition at low radio‐frequency power was found to suppress the generation of defects during the growth of a‐Si:H absorption layers on the treated buffer layers. With optimized H2 PT of the a‐Si:H single‐junction module, the stabilized short circuit current and fill factor increased, and the stabilized open circuit voltage moves beyond its initial value. The results demonstrate 7.7% stabilized efficiency and 10.5% LID for the a‐Si:H single‐junction module and 10.82% stabilized efficiency and 7.76% LID for the a‐Si:H/µc‐Si:H tandem module. Thus, the growth of an a‐Si:H absorption layer on a H2 PT buffer layer can be considered as a practical method for producing high‐performance Si thin film modules. Copyright © 2012 John Wiley & Sons, Ltd.
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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".