The role of bulk and interface states on performance of a-Si : H p-i-n solar cells using reverse current–voltage technique
Bibliographic record
Abstract
The defect state densities in the bulk of the i-layer and at the p/i interface have been studied in hydrogenated amorphous silicon (a-Si?:?H) solar cells using reverse current?voltage (J?V) measurements. In this work the cells have been soaked with blue and red lights prior to measurements. The voltage-dependent reverse current has been analysed on the basis of thermal generation of the carriers from midgap states in the i-layer and the carrier injection through the p/i interface. Based on the reverse current behaviour, it has been analysed that at lower reverse bias (reverse voltage, Vr < 5?V) the defect states in the bulk of the i-layer and at higher bias (Vr ~ 25?V) the defect states at the p/i interface are contributing to the reverse currents. The applied reverse bias annealing (RBA) treatment on these cells shows more significant annihilation of defect states at the p/i interface as compared with the bulk of the i-layer. An analytical model is developed to explain the observed behaviour. There is good agreement between the theory and the experimental observations. The fitted defect state densities are 9.1 ? 1015?cm?3 and 8 ? 1018?cm?3 in the bulk of the i-layer and near the p/i interface, respectively. These values decrease to 2.5 ? 1015?cm?3 and 6 ? 1017?cm?3, respectively, in the samples annealed under reverse bias at 2?V.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".