Comparative Analysis of Multilayer Lead Oxide-Based X-ray Detector Prototypes
Bibliographic record
Abstract
Lead oxide (PbO) photoconductors are proposed as X-ray-to-charge transducers for the next generation of direct conversion digital X-ray detectors. Optimized PbO-based detectors have potential for utilization in high-energy and dynamic applications of medical X-ray imaging. Two polymorphs of PbO have been considered so far for imaging applications: polycrystalline lead oxide (poly-PbO) and amorphous lead oxide (a-PbO). Here, we provide the comparative analysis of two PbO-based single-pixel X-ray detector prototypes: one prototype employs only a layer of a-PbO as the photoconductor while the other has a combination of a-PbO and poly-PbO, forming a photoconductive bilayer structure of the same overall thickness as in the first prototype. We characterize the performance of these prototypes in terms of electron–hole creation energy (W±) and signal lag—major properties that define a material’s suitability for low-dose real-time imaging. The results demonstrate that both X-ray photoconductive structures have an adequate temporal response suitable for real-time X-ray imaging, combined with high intrinsic sensitivity. These results are discussed in the context of structural and morphological properties of PbO to better understand the preparation–fabrication–property relationships of this material.
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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 | 0.001 |
| 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 | 0.001 | 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".