SU‐E‐T‐763: Towards the Mechanical Doping of Plastic Scintillators
Bibliographic record
Abstract
Purpose: The doping of plastic scintillators with high‐Z elements changes the radiation interaction cross section of the medium and therefore changes the intrinsic response of the detector. The selection of doped plastic scintillators available commercially is limited. This research aims to develop a novel methodology for the mechanical doping of plastic scintillating materials. The ultimate goal of this project is to use doped scintillators of varying intrinsic behavior to unfold the LET (energy) spectrum of any radiation beam. Methods: Commercially available BC408 plastic scintillator was obtained and crushed into uniform powder (using ball mill). Two separate materials were tested for light output signal: uncrushed scintillator and scintillating powder bound by glue. Commercially available U301 UV‐hardening glue was used. Scintillation response was measured by creating a thin housing of black acrylic that allowed light from each scintillator to be guided to an optical fiber via a taper. The optical fiber was connected to a PMT; signal was measured using an electrometer. Tests were conducted to determine if crushing+bonding distorted linearity and energy dependence of detector response. Linearity was tested for by irradiating (uncrushed and crushed+glued) for varying durations ensuring signal scaled accordingly; this was done using 300kV x‐rays and 6MeV electrons. The effect on energy dependence was examined by obtaining a signal ratio (100kV vs. 300kV; 6MeV vs. 18MeV) for both uncrushed and crushed+glued scintillating material. Results: Crushing and binding with U301 glue did not have an effect on linearity. Energy dependence was changed by 20.3%; crushing+bonding decreased the sensitivity at low energy radiation. Conclusion: This work indicates that crushing and binding of plastic scintillating material does not change the linearity of its response to radiation but does have an effect on the energy dependence. Future work involves addition of high‐Z dopants (W, Mo, Pb) and characterization of the detector response.
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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 | 0.000 | 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 | 0.000 | 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".