Bilayer lead oxide X-ray photoconductor for lag-free operation
Bibliographic record
Abstract
Polycrystalline Lead Oxide (poly-PbO) was considered one of the most promising photoconductors for the direct conversion X-ray medical imaging detectors due to its previous success in optical imaging, i.e., as an optical target in so-called Plumbicon video pick-up tubes. However, a signal lag which accompanies X-ray excitation, makes poly-PbO inapplicable as an X-ray-to-charge transducer in real-time X-ray imaging. In contrast, the recently synthesized Amorphous Lead Oxide (a-PbO) photoconductor is essentially lag-free. Here, we report on our approach to a PbO detector where a thin layer of a-PbO is combined with a thick layer of poly-PbO for lag-free operation. In the presented a-PbO/poly-PbO bilayer structure, the poly-PbO layer serves as an X-ray-to-charge transducer while the a-PbO acts as a lag prevention layer. The hole mobility in the a-PbO/poly-PbO bilayer structure was measured by photo-Charge Extraction by Linearly Increasing Voltage technique at different temperatures and electric fields to investigate charge transport properties. It was found that the hole mobility is similar to that in a-Se-currently the only commercially viable photoconductor for the direct conversion X-ray detectors. Evaluation of the X-ray temporal performance demonstrated complete suppression of signal lag, allowing operation of the a-PbO/poly-PbO detector in real-time imaging.
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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 | 0.001 |
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".