He bubble growth in nickel simulated by object kinetic Monte Carlo
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it