Cavity morphology in a Ni based superalloy under heavy ion irradiation with hot pre-injected helium. II
Bibliographic record
Abstract
In the current investigation, TEM in-situ heavy ion (1 MeV Kr2+) irradiation with helium pre-injected at elevated temperature (400 °C) was conducted to simulate in-reactor neutron irradiation induced damage in CANDU spacer material Inconel X-750, in an effort to understand the effects of helium on irradiation induced cavity microstructures. Three different quantities of helium, 400 appm, 1000 appm, and 5000 appm, were pre-injected directly into TEM foils at 400 °C. The samples containing helium were then irradiated in-situ with 1 MeV Kr2+ at 400 °C to a final dose of 5.4 dpa (displacement per atom). Cavities were formed from the helium injection solely and the cavity density and size increased with increasing helium dosage. In contrast to previous heavy ion irradiations with cold pre-injected helium, heterogeneous nucleation of cavities was observed. During the ensuing heavy ion irradiation, dynamical observation showed noticeable size increase in cavities which nucleated close to the grain boundaries. A “bubble-void” transformation was observed after Kr2+ irradiation to high dose (5.4 dpa) in samples containing 1000 appm and 5000 appm helium. Cavity distribution was found to be consistent with in-reactor neutron irradiation induced cavity microstructures. This implies that the distribution of helium is greatly dependent on the injection temperature, and helium pre-injection at high temperature is preferred for simulating the migration of the transmutation produced helium.
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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 | 0.000 | 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 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".