He bubble growth in nickel simulated by object kinetic Monte Carlo
Bibliographic record
Abstract
When Ni-based alloys are exposed to neutron irradiation , (n, α ) transmutation introduces helium to the metal, leading to the formation of bubbles, which can severely affect the properties of the material. Identifying the key parameters controlling bubble growth can help us design materials with improved radiation tolerance. In this study, we parameterized an object kinetic Monte Carlo (OkMC) framework able to simulate the coalescence and growth of helium bubbles in pure Ni during and after helium ion implantation . The simulated bubbles size is consistent with phenomenological models based on past experimental studies. Our simulations indicate that the mean He bubble size is strongly correlated with temperature and inversely correlated with the implantation dose rate. The interactions between irradiation-induced defects and interfaces (sinks) are shown to play a key role in determining the size and stability of bubbles. Furthermore, our simulations suggest that the controlling reaction in swelling is the annihilation of self-interstitial defects at sinks, not the presence of He.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".