Helium bubble nucleation at grain boundaries and its influence on intergranular fracture
Bibliographic record
Abstract
An in-depth understanding of the formation of intergranular helium bubbles and its relation to embrittlement is an important issue in the nuclear industry. In this paper, a thermodynamic model is developed to analyze the nucleation of intergranular helium bubbles. Microstructural observation using scanning electron microscopy and electron backscatter diffraction gives a detailed description for the relation between the bubble formation and the grain-boundary (GB) misorientation in helium-implanted nickel and Inconel X750. The theoretical and the experimental results confirm that the nucleation of intergranular helium bubbles is GB structure-dependent, the helium-to-vacancy ratio plays an important role in the bubble precipitation, and the interfacial tension of bubbles cannot be approximated to be the interfacial energy. The bubble-induced intergranular embrittlement in a polycrystal is modelled. The GB misorientation distribution, the intergranular bubble nucleation and growth and the GB connectivity are the key factors affecting the GB fracture toughness. The hoop ductility of the cladding tubes containing helium is analyzed. The hoop stress-induced increase in the GB energy promotes the precipitation of bubbles at the radial GBs and lead to the loss of tube ductility. Based on this work, the complicated correlation among the intergranular helium bubbles, the GB structure, the helium concentration, the applied stress and the helium embrittlement is clarified.
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.
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".