Dependence of open circuit voltage in a-Si:H and μc-Si:H solar cells on defect density in absorber layer varied by 2 MeV electron bombardment
Bibliographic record
Abstract
Theoretically predicted values of the open circuit voltage (VOC) for a-Si:H or μc-Si:H based solar cells are substantially higher than the values achieved in of state-of-the-art devices. Fundamentally, open circuit voltage is determined by generation-recombination kinetics, where recombination is often controlled by the defect density in the absorber layer of a solar cell. The latter aspect is the focus of the paper. The relation between the VOC and the bulk recombination in the absorber layer is addressed in experiment by varying the defect density. The absorber layer defect density (spin density, NS, monitored with ESR) in a-Si:H and μc-Si:H solar cells was varied over two orders of magnitude using a 2 MeV electron bombardment and successive stepwise annealing. The results of the electron bombardment experiment are analyzed with respect to the illumination intensity dependency of the VOC, measured for the same set of a-Si:H and μc-Si:H solar cells. We find that the VOC of a-Si:H solar cells is not limited by defects in the bulk of the absorber layer, even at relatively high defect density up to 3–5 × 1016 cm−3 and, therefore, other limiting mechanisms have to be identified to improve voltage in these devices. In contrast, μc-Si:H solar cells show nearly classical VOC–NS relation. The bulk defect density in μc-Si:H absorber layer is thus likely the key limiting factor for VOC in these devices at present status of material quality (NS of 3–7 × 1015 cm−3). Further optimization of μc-Si:H in terms of bulk defect density is highly relevant for VOC improvement in 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".