Amorphous lead oxide (a-PbO): suppression of signal lag via engineering of the layer structure
Bibliographic record
Abstract
Abstract Presence of a signal lag is a bottle neck of performance for many non-crystalline materials, considered for dynamic radiation sensing. Due to inadequate lag-related temporal performance, polycrystalline layers of CdZnTe, PbI2, HgI2 and PbO are not practically utilized, despite their superior X-ray sensitivity and low production cost (even for large area detectors). In the current manuscript, we show that a technological step to replace nonhomogeneous disorder in polycrystalline PbO with homogeneous amorphous PbO structure suppresses signal lag and improves time response to X-ray irradiation. In addition, the newly developed amorphous lead oxide (a-PbO) possesses superior X-ray sensitivity in terms of electron-hole pair creation energy $${W}_{\pm }$$ W ± in comparison with amorphous selenium – currently the only photoconductor used as an X-ray-to-charge transducer in the state-of-the-art direct conversion X-ray medical imaging systems. The proposed advances of the deposition process are low cost, easy to implement and with certain customization might potentially be applied to other materials, thus paving the way to their wide-range commercial use.
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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".