Effect of simultaneous helium implantation on the microstructure evolution of Inconel X-750 superalloy during dual-beam irradiation
Bibliographic record
Abstract
This study focuses on investigation into the effect of helium implantation on microstructure evolution in Inconel X-750 superalloy during dual-beam (Ni+/He+) irradiation. The 1 MeV Ni+ ions with the damage rate of 10−3 dpa/s as well as 15 keV He+ ions using rate of 200 appm/dpa were simultaneously employed to irradiate specimens at 400 °C to different doses. Microstructure characterization has been conducted using high-resolution analytical transmission electron microscopy (TEM). The TEM results show that simultaneous helium injection has significant influence on irradiation-induced microstructural changes. The disordering of γ′ (Ni3 (Al, Ti)) precipitates shows noticeable delay in dose level compared to mono heavy ion irradiation, which is attributed to the effect of helium on promoting the dynamic reordering process. In contrast to previous studies on single-beam ion irradiation, in which no cavities were reported even at high doses, very small (2–5 nm) cavities were detected after irradiation to 5 dpa, which proved that helium plays crucial role in cavity formation. TEM characterization also indicates that the helium implantation affects the development of dislocation loops during irradiation. Large 1/3 〈1 1 1〉 Frank loops in the size of 10–20 nm developed during irradiation at 400 °C, whereas similar big loops detected at higher irradiation temperature (500 °C) during sole ion irradiation. This implies that the effect of helium on trapping the vacancies can help to develop the interstitial Frank loops at lower irradiation temperatures.
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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".