Temperature Dependence of the Primary Species Yields of Liquid Water Radiolysis by 0.8-MeV Fast Neutrons
Bibliographic record
Abstract
The yields of species such as e-aq, H • , • OH, H 2 and H 2 O 2 , formed from the radiolysis of neutral liquid water by the incidence of 0.8-MeV neutrons at temperatures between 25 and 350°C, were calculated by using Monte Carlo simulations. The slowing down of these neutrons through elastic scattering produced recoil protons elastically of ~0.5057, 0.186, and 0.0684 MeV which had linear energy transfers (LETs) of ~40, 67 and 76 keV/µm, respectively, at 25°C. The effects of neutron radiation can be predicted based on the contribution of those first three recoil protons by neglecting the radiation effects due to oxygen ion recoils. Then, the fast neutron yields could be estimated by summing the yields of contributing protons after corresponding weightings were used according to their energy. In this work, yields were calculated at 10 -7 and 10 -6 s after incidence of neutron radiation in water at the aforementioned temperature range. Overall, there is a reasonably good agreement between our calculated and existing experimental G -values for the entire temperature range. However, we proposed an hypothesis that the not very significant difference between experimental data and our calculated data is due to the different measuring time used in obtaining the experimental data as compared to the ones used in our calculation. Our computed yields for 0.8-MeV fast neutron radiation show an essentially similar temperature dependences over the range of temperature studied with 2-MeV fast neutron and low-LET radiation, but with lower values for yields of free radicals and higher values for molecular yields. Received: 04 October 2014 ; Revised: 23 March 2016 ; Accepted: 23 March 2016
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 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".