The Role of Dissolved Hydrogen on the Corrosion/Dissolution of Spent Nuclear Fuel
Bibliographic record
Abstract
The literature on nuclear fuel dissolution and radionuclide release studies in aqueous solutions containing dissolved hydrogen has been reviewed. These studies include investigations with spent PWR and MOX fuels, fuel specimens doped with alpha emitters to mimic “aged” fuels, SIMFUELs fabricated to simulate spent fuel properties, and unirradiated uranium dioxide pellets and powders. In all these studies, dissolved hydrogen was shown to suppress fuel corrosion and in spent fuel studies to suppress radionuclide release. A number of mechanisms have been either demonstrated or proposed to explain these effects, all of which involve the activation of hydrogen to produce the strongly reducing H • radical, which scavenges radiolytic oxidants and suppresses fuel oxidation and dissolution (i.e., corrosion). Both gamma and alpha radiation have been shown to produce H • surface species. With gamma radiation this could involve the absorption of gamma energy by the solid leading to water decomposition to OH • and H • radicals, with the OH • radical subsequently reacting with hydrogen to yield an additional H • . This latter radical then suppresses fuel oxidation and scavenges radiolytic oxidants. With alpha radiation, the need to neutralize oxygen vacancies generated by recoil events can initiate the same process by decomposing water. In the absence of radiation fields activation can occur on the surface of noble metal (epsilon) particles. Since these particles are galvanically-coupled to the fuel matrix they act as anodes for hydrogen oxidation (which proceeds through surface H • species) and forces the UO 2 to adopt a low potential. Also, there is some evidence to suggest that H 2 can be activated on the UO 2 surface in the presence of hydrogen peroxide, but the process appears to be inefficient. Depending on the radiation fields present and the number density of epsilon particles, complete suppression of fuel corrosion appears possible even for hydrogen pressures as low as 0.1 to 1 bar. Since the corrosion of steel liners within failed waste containers could produce hydrogen pressures up to 50 bar, fuel corrosion could be completely suppressed under the long-term conditions expected in sealed repositories.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".