Effect of simultaneous helium implantation on the microstructure evolution of Inconel X-750 superalloy during dual-beam irradiation
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
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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