Modeling the Impact of Viscosity on Fricke Gel Dosimeter Radiolysis: A Radiation Chemical Simulation Approach
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Bibliographic record
Abstract
The Fricke gel dosimeter, a hydrogel-based chemical dosimeter containing dissolved ferrous sulfate, measures 3D radiation dose distributions by oxidizing Fe2+ to Fe3+ upon irradiation. This study investigates the variation in Fricke yield, G(Fe3+), from a radiation–chemical perspective in both standard and gel-like Fricke systems of varying viscosities, under low- and high-linear energy transfer (LET) conditions. We employed our Monte Carlo track chemistry code IONLYS-IRT, using protons of 300 MeV (LET~0.3 keV/µm) and 1 MeV (LET~25 keV/µm) as radiation sources. To assess the impact of viscosity on G(Fe3+), we systematically varied the diffusion coefficients of all radiolytic species in the Fricke gel, including Fe2+ and Fe3+ ions. Increasing gel viscosity reduces Fe3+ diffusion and stabilizes spatial dose distributions but also lowers G(Fe3+), compromising measurement accuracy and sensitivity—especially under high-LET irradiation. Our results show that an optimal Fricke gel dosimeter must balance these competing factors. Simulations with lower sulfuric acid concentrations (e.g., 0.05 M vs. 0.4 M) further revealed that G(Fe3+) values at ~100 s are nearly identical for both low- and high-LET conditions. This study underscores the utility of Monte Carlo simulations in modeling viscosity effects on Fricke gel radiolysis, guiding dosimeter optimization to maximize sensitivity and accuracy while preserving spatial dose distribution integrity.
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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 it