Light induced changes in the amorphous—crystalline silicon heterointerface
Bibliographic record
Abstract
The photostability of the amorphous—crystalline silicon heterointerface is investigated. It is revealed that the metastability of hydrogenated amorphous silicon (a-Si:H) causes significant light induced changes in the heterointerface. Unlike bulk a-Si:H, the photostability of the heterointerface is not controlled by the microstructural properties of a-Si:H but rather by the initial heterointerface properties. Interfaces that initially have low interface defect density show the greatest degradation while those that initially have high interface defect density actually show light-induced improvement. It is shown that the degree of light induced change in the interface defect density is linearly proportional to the natural logarithm of the initial interface defect density. Further, it is revealed that the kinetics of light-induced change in the heterointerface defect density can be faster or slower than light-induced changes in bulk a-Si:H films depending on the initial properties of the heterointerface. Light soaking measurements on heterointerfaces with doped a-Si:H films reveal that interface defect density of these structures improves with light soaking. It is proposed that this is caused by a combination of the high initial interface defect density of samples using doped a-Si:H films and reduced generation of defects near the heterointerface due to the enhanced field effect provided by the doped films.
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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) | 0.002 | 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".