Technical Note: Nanometric organic photovoltaic thin film detectors for dose monitoring in diagnostic x‐ray imaging
Bibliographic record
Abstract
PURPOSE: To fabricate organic photovoltaic (OPV) cells with nanometric active layers sensitive to ionizing radiation and measure their dosimetric characteristics in clinical x-ray beams in the diagnostic tube potential range of 60-150 kVp. METHODS: Experiments were designed to optimize the detector's x-ray response and find the best parameter combination by changing the active layer thickness and the area of the electrode. The OPV cell consisted of poly (3-hexylthiophene-2,5-diyl): [6,6]-phenyl C61 butyric acid methyl ester photoactive donor and acceptor semiconducting organic materials sandwiched between an aluminum electrode as an anode and an indium tin oxide electrode as a cathode. The authors measured the radiation-induced electric current at zero bias voltage in all fabricated OPV cells. RESULTS: The net OPV current as a function of beam potential (kVp) was proportional to kVp(-0.5) when normalized to x-ray tube output, which varies with kVp. Of the tested configurations, the best combination of parameters was 270 nm active layer thicknesses with 0.7 cm(2) electrode area, which provided the highest signal per electrode area. For this cell, the measured current ranged from approximately 0.7 to 2.4 nA/cm(2) for 60-150 kVp, corresponding to about 0.09 nA-0.06 nA/mGy air kerma, respectively. When compared to commercial amorphous silicon thin film photovoltaic cells irradiated under the same conditions, this represents 2.5 times greater sensitivity. An additional 40% signal enhancement was observed when a 1 mm layer of plastic scintillator was attached to the cells' beam-facing side. CONCLUSIONS: Since both OPVs can be produced as flexible devices and they do not require external bias voltage, they open the possibility for use as thin film in vivo detectors for dose monitoring in diagnostic x-ray 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".