Monte-Carlo Simulation of -ray and Fast Neutron Radiolysis of Liquid Water and 0.4 M H2SO4 Solutions at Temperatures up to 325oC
Bibliographic record
Abstract
Monte-Carlo simulations were used to study the radiolysis of liquid water at 25-325C when subjected to low linear energy transfer (LET) of 60Co -ray radiation and fast neutrons of 2 and 0.8 MeV. The energy deposited in the early stage of 60Co -ray irradiation was approximated by considering short segments (~150 m) of 300 MeV proton tracks, corresponding to an average LET of ~0.3 keV/m. In case of 2 MeV fast neutrons, the energy deposited was considered by using short segments (~5 m) of energy at 1.264, 0.465, 0.171, 0.063 and 0.24 MeV. 0.8 MeV fast neutrons were approximated by 0.505, 0.186, 0.069 and 0.025 MeV protons. The effect of 0.4 M H2SO4 solution on radiolysis was also studied by this method for both 60Co -rays and 0.8 MeV fast neutrons. The simulated results at the time of 10-7s after irradiation were obtained and compared with the available experimental results published by other researchers to be in excellent agreement with them over the entire temperature ranges and radiation sources studied. Except for g(H2) that increase with temperature rises, the general behaviors of higher radical products and lower molecular products at higher temperatures were obtained. The LET effect is also validated by this study, showing that the increase in LET would yield higher molecular and lower radical products. Studies on 0.4 M H2SO4 solutions also show good agreement between the computed and experimental data for -ray irrradiation: the presence of 0.4 M H+, except for g(H2) that gives lower value at 25C and higher value at 325C, gives the higher values for radicals and g(H2O2) at 25C and lower values at 325C, compared with that for neutral water. The computed data show good agreement with the experimental data for 0.4 M H2SO4 solutions induced by 0.8 MeV fast neutrons, except for g(H2) and g(H●) that gives good agreement up to 50C, then the opposite tendencies with the further temperature rises. However, the simulated fast neutron radiolysis on acidic demonstrates similar tendencies on temperature dependence with that for simulated 60Co -radiolysis, but in different magnitude. For better understanding, more experimental data for fast neutrons are needed, especially under the acidic conditions
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".