Dosimetric properties of colloidal quantum dot-based systems for scintillation dosimetry
Bibliographic record
Abstract
Abstract Colloidal quantum dots (cQDs) are starting to be used in radiation detection, either combined with an organic fluorophore or used as a sole luminescent material. In the latter case, only few studies report on cQD-based detectors for medical applications, especially for scintillation dosimetry in radiation therapy. Moreover, most of these studies focus on the effects of radiation on cQD photoluminescence but do not look into the properties of the scintillation signal itself. The present article provides a study of those cQD scintillation properties not previously investigated including the linearity of the signal as a function of dose, the signal dose rate and beam energy dependencies. The latter was also characterized for the commercially available scintillating fiber BCF-60 and liquid scintillator Ultima Gold. CdSe multishell cQDs in two physical forms were used as a sensitive dosimeter volume: a cQD powder to constitute a fiber optic based dosimeter and cQD liquid dispersions to be volumetric dosimeters. The signal linearity was assessed with a R 2 coefficient >0.999 over a clinically relevant dose range at kV and MV beam energies. The cQDs had a good overall dose rate independence, with a change from the relative dose of 1% at MV energies and 2% at kV energies, of their scintillation output when irradiated with an orthovoltage device and a linear accelerator. Regarding the beam energy dependence, the cQD powder had the highest dependence amongst all the scintillators compared, the 120 kVp light output being up to almost 4 times that of the 6 MV beam. The smallest effect of the beam energy was reported for the cQD alkylbenzene liquid dispersion, having a variation of light signal normalized to 6 MV of 15% that is even less than for BCF-60 and Ultima Gold.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".