Combining 2D simulations with atom probe tomography to investigate radiation-induced segregation near nanoscale cavities
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Radiation-induced segregation (RIS) is a non-equilibrium phenomenon that can significantly alter local composition and degrade material properties. Although extensive research has focused on RIS near grain boundaries, much less attention has been given to RIS near nanosized cavities, including voids and gas-filled bubbles, which are primary contributors to material swelling. Compared with grain boundaries, cavities exhibit unique characteristics as defect sinks, such as spherical geometry, potentially higher density, and shorter distances between sinks. Although conventional one-dimensional (1D) models can capture basic features of RIS near isolated cavities, our calculations showed that they failed to reproduce experimental RIS profiles near closely spaced bubbles, an arrangement commonly observed in irradiated materials due to heterogenous bubble nucleation. In this study, we combined two-dimensional (2D) simulations with atom probe tomography (APT) experiments to investigate RIS near helium bubbles in a Ni 50 Fe 50 model alloy. The 2D simulations achieved good agreement with the experimental data. Moreover, we identified a non-linear coupling effect between neighboring bubbles: Ni segregation between two bubbles was higher than that from a single bubble, but lower than the linear sum of two isolated bubbles. These results demonstrate that the 2D RIS model is essential for simulating complex RIS behavior near cavities, thereby enabling more accurate predictions of microstructural evolution and property changes in materials under extensive irradiation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it