zeo19: A thermodynamic database for assessing zeolite stability during the corrosion of nuclear waste immobilization glasses
Bibliographic record
Abstract
Abstract Stable, durable immobilization of radioactive wastes requires robust understanding of the sub-surface geochemical processes that occur in repository environments. For example, the accelerated dissolution (corrosion) of nuclear waste immobilization glasses (i.e., the so-called “Stage III” corrosion) following the precipitation of zeolitic phases is a significant issue that could result in radionuclide release. However, current uncertainties in establishing the tendency for the persistence of zeolites results in difficulties in estimating the chemical environments and state variables that favor zeolite precipitation. To assess the tendency for Stage III corrosion, we compiled a unified, internally-consistent thermodynamic database to estimate zeolite stability under conditions relevant to nuclear waste repositories (namely, p = 1 bar and T < 95 °C), i.e., for compounds including: analcime, clinoptilolite, mordenite, erionite, thomsonite, bikitaite, brewsterite, dachiardite, epistilbite, ferrierite, gonnardite, harmotome, leonhardite, paranatrolite, tetranatrolite, yugawaralite zeolite X, and zeolite P(Ca). The database, which features both existing and/or newly-derived thermodynamic properties, is integrated with a Gibbs (free) energy minimization (GEM) solver to estimate stable zeolite phase equilibria and their partitioning at equilibrium. The database offers favorable predictions of the solubility of the zeolite phases as a function of temperature. The validity of the database is ascertained by comparing newly-constructed equilibrium activity diagrams with experimental observations of zeolite formation during glass dissolution across conditions encompassing diverse solution chemistries, pH’s, and temperatures.
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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) | 0.001 | 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 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".