Calculation of the Yields for the Primary Species Formed from the Radiolysis of Liquid Water by Fast Neutrons at Temperatures between 25–350°C
Bibliographic record
Abstract
Monte Carlo simulations were used to calculate the yields for the primary species (e(-)aq, H(•), H2, (•)OH and H2O2) formed from the radiolysis of neutral liquid water by mono-energetic 2 MeV neutrons at temperatures between 25-350°C. The 2 MeV neutron was taken as representative of a fast neutron flux in a reactor. For light water, the moderation of these neutrons generated elastically scattered recoil protons of ∼1.264, 0.465, 0.171 and 0.063 MeV, which at 25°C, had linear energy transfers (LETs) of ∼22, 43, 69 and 76 keV/μm, respectively. Neglecting the radiation effects due to oxygen ion recoils and assuming that the most significant contribution to the radiolysis came from these first four recoil protons, the fast neutron yields could be estimated as the sum of the yields for these protons after allowance was made for the appropriate weightings according to their energy. Yields were calculated at 10(-7), 10(-6) and 10(-5) s after the ionization event at all temperatures, in accordance with the time range associated with the scavenging capacities generally used for fast neutron radiolysis experiments. The results of the simulations agreed reasonably well with the experimental data, taking into account the relatively large uncertainties in the experimental measurements, the relatively small number of reported radiolysis yields, and the simplifications included in the model. Compared with data obtained for low-LET radiation ((60)Co γ rays or fast electrons), our computed yields for fast neutron radiation showed essentially similar temperature dependences over the range of temperatures studied, but with lower values for yields of free radicals and higher values for molecular yields. This general trend is a reflection of the high-LET character of fast neutrons. Although the results of the simulations were consistent with the experiment, more experimental data are required to better describe the dependence of radiolytic yields on temperature and to test more thoroughly our modeling calculations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".