Investigation of metastability and instability effects on the minority carrier transport properties of microcrystalline silicon thin films by using the steady-state photocarrier grating technique
Bibliographic record
Abstract
Metastability effects in hydrogenated microcrystalline silicon thin films due to air, high purity nitrogen, helium, argon, and oxygen were investigated using temperature-dependent dark conductivity, photoconductivity, and steady-state photocarrier grating methods. It was found that short-term air, nitrogen, and inert gases caused a small reversible increase of σDark and σphoto within a factor of two, but they did not affect the minority carrier μτ-products significantly. These changes are partially reduced by vacuum treatment and completely reduced after heat treatment at 430 K. However, oxygen gas treatment at 80 °C resulted in more than an order of magnitude increase in both σDark and σphoto and an increase in the diffusion length, LD, by 50% from that of the annealed-state value in highly crystalline samples, while no significant metastability is detected in amorphous and low crystalline silicon thin films. A following heat treatment partially recovers both σDark and σphoto to their annealed-state values, while LD decreases only slightly. Such increase in the LD values could be due to a decrease in the density of recombination centers for holes below the Fermi level, which may be related to passivation of defects by oxygen on the surface of crystalline grains.
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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) | 0.000 | 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 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".