Photo-crystallization in a-Se layer structures: Effects of film-substrate interface-rigidity
Bibliographic record
Abstract
Amorphous selenium (a-Se) films deposited on rigid substrates can undergo photo-induced crystallization (PC) even at temperatures (T) well below the glass transition, Tg ∼ 313 K. Substrate-generated shear strain is known to promote the PC process. In the present work, we explore the influence of different substrates (Si and glass), and different film-layer-substrate combinations, on the PC in a variety of a-Se films and film-structures. The intermediate layers (indium tin oxide and polyimide) are chosen to promote conductivity and/or to be a buffer against interface strain in structures of interest for digital imaging applications. The PC characteristics in these samples are evaluated and compared using optical microscopy, atomic-force microscopy, Raman mapping, and T-dependent Raman spectroscopy. Both the presence of a soft intermediate layer, and the thermal softening that occurs for T increasing through Tg, inhibit the tendency for the onset of PC. The extensive PC mapping results in the wide range of samples studied here, as well as the suppression of PC near Tg in this array of samples, strongly support the generality of this behavior. As a consequence, one may expect that the stability of a-Se films against PC can be enhanced by decreasing the rigidity of the film-substrate interface. In this regard, advanced film structures that employ flexible substrates, soft intermediate layers, and/or are designed to be operated near Tg should be explored.
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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".