X-ray sensing materials stability: influence of ambient storage temperature on essential thermal properties of undoped vitreous selenium
Bibliographic record
Abstract
Amorphous selenium (a-Se) is currently used in x-ray image detectors as an x-ray photoconductor. Normally a-Se films used in device applications are fabricated by the evaporation of vitreous bulk material loaded into boats in a typical vacuum deposition system. The resistance against crystallization is an important factor in both film and bulk forms of a-Se. Previous work has indicted that the resistance to crystallization is surprisingly more pronounced around 35 °C [1]. In this work we have therefore examined the essential thermal properties of vitreous selenium (99.999%) samples that have been stored at different temperatures. The thermal characterization experiments involved a series of DSC (Differential Scanning Calorimetry) measurements in which have monitored the glass transition and melting endotherms, and the crystallization exotherm in heating-cooling-heating scans. In DSC experiments, a sample would be heated to a temperature above the melting temperature, equilibrated, then cooled at a fixed rate down to 20 °C, then equilibrated and finally scanned again under a heating schedule. The samples were isothermally stored at temperatures corresponding to 18, 35 and 55 °C. The thermal analysis results show that there are distinct differences in the thermal properties. We have examined the stability in terms of the difference in the crystallization onset temperature ( T c ) and the onset of glass transition temperature ( T g ). We also examined the Hruby coefficient ( K gl ) of these samples, that is K gl = ( T c – T g )/( T m – T c ) where T c is the crystallization onset temperature and T m is the melting onset temperature. We have found K gl to depend on the storage temperature. Surprisingly, we observed that the Hruby coefficient is actually larger at 35 °C compared to the values at 18 and 55 °C.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".