A Low-Temperature Processed Organic Hole-Blocking Contact Layer for Amorphous Selenium X-Ray Photoconductor
Bibliographic record
Abstract
Amorphous selenium (a-Se) X-ray detectors have been used commercially for two decades in mammography because of their high spatial resolution. However, these devices face challenges in high spatial resolution tomography and angiography where lower radiation exposures and dynamic imaging are required. Higher voltages across the selenium layer can potentially improve sensitivity and temporal performance, but dark current is a concern. Although organic polyimide (PI) layers were previously demonstrated to have excellent hole-blocking properties that enabled high voltage mode operation with selenium devices, their higher baking and curing temperatures have restricted usage on the top surface of temperature-sensitive selenium as a hole-blocking layer. In this study, we explore low-temperature SU-8 as a hole-blocking layer for selenium. Our findings reveal that the devices with SU-8 as a hole-blocking layer in either top or bottom configurations maintained a dark current below 1 pA/mm2 even at an increased electric field of 40 V/$\mu \text{m}$. Devices with the SU-8 hole-blocking layer at the top surface exhibited a sensitivity loss of 18% after exposure to a cumulative 0.175 Gray (Gy) X-ray while maintaining lag or persistent photoconductivity below 1% at 20 V/$\mu \text{m}$. As a comparison, devices fabricated in the same run that utilized the previously reported PI hole-blocking layer at the bottom surface resulted in a sensitivity drop of 24.1% and with lag of ≈3.1%. These results indicate that higher-performance selenium detectors are achievable with SU-8 blocking layers and can expedite the commercial development of low-lag, high-gain selenium X-ray detectors for dynamic medical 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".