High spatial resolution direct conversion amorphous selenium X-ray detectors with monolithically integrated CMOS readout
Bibliographic record
Abstract
Abstract Recent progress in the field of micron-scale spatial resolution direct conversion X-ray detectors for high-energy synchrotron light sources serve applications ranging from nondestructive and noninvasive microscopy techniques which provide insight into the structure and morphology of crystals, to medical diagnostic measurement devices. Amorphous selenium (a-Se) as a wide-bandgap thermally evaporated photoconductor exhibits ultra-low thermal generation rates for dark carriers and has been extensively used in X-ray medical imaging. Being an amorphous material, it can further be deposited over large areas at room temperatures and at substantially lower costs as compared to crystalline semiconductors. To address the demands for a high-energy and high spatial resolution X-ray detector for synchrotron light source applications, we have thermally evaporated a-Se on a Mixed-Mode Pixel Array Detector (MM-PAD) Application Specific Integrated Circuit (ASIC). The ASIC format consists of 128 × 128 square pixels each 150 μm on a side. A 200 μm a-Se layer was directly deposited on the ASIC followed by a metal top electrode. The completed detector assembly was tested with 45 kV Ag and 23 kV Cu X-ray tube sources. The detector fabrication, performances, Modulation Transfer Function (MTF) measurements, and simulations are reported.
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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) | 0.002 | 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".