Radiation damage and recovery of plastic scintillators under ultra-high dose rate 200 MeV electrons at CERN CLEAR facility
Bibliographic record
Abstract
The FLASH effect holds significant potential in improving radiotherapy treatment outcomes. Very high energy electrons (VHEEs) can effectively target tumors deep in the body and can be accelerated to achieve ultra-high dose rates (UHDR), making them a promising modality for delivering FLASH radiotherapy in the clinic. However, apart from suitable VHEE sources, clinical translation requires accurate dosimetry, which is challenging due to the limitation of standard dosimeters under UHDR. Water-equivalent and real-time plastic scintillation dosimeters (PSDs) may offer a solution. In this study, a 4-channel PSD, consisting of polystyrene-based BCF12 and Medscint proprietary scintillators, polyvinyltoluene (PVT)-based EJ-212 and a clear plastic fiber channel for Cherenkov subtraction was exposed to the 200 MeV VHEE UHDR beam at the CLEAR CERN facility. The Hyperscint RP200 platform was used to assess linearity to dose pulses of up to 90 Gy and dose rates up to 4.6x10$^9$ Gy/s, and to investigate radiation damage and recovery after dose accumulation of 37.2 kGy. While clear fiber response was linear across the entire dose range studied, light output saturated above ~50 Gy/pulse for scintillators. Despite radiation damage, linearity was preserved, though it resulted in a decrease of scintillator and clear fiber light output of <1.85 %/kGy and a shift in spectra towards longer wavelengths. Short-term recovery (<100h) of these changes was observed and depended on rest duration and accumulated dose. After long-term rest (<172 days), light output recovery was partial, with 6-22% of residual permanent damage remaining, while spectral recovery was complete. We showed that PSDs are sensitive to radiation damage, but maintain dose linearity even after accumulated dose of 37.2 kGy, and exhibit significant response recovery. This work highlights the potential of PSDs for dosimetry in UHDR conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".