Dissolution kinetics and morphological changes of<b>γ</b>′ in AD730<sup><b>TM</b></sup>superalloy
Bibliographic record
Abstract
Alloy AD730TM is a recently developed Nickel base superalloy for application as turbine disk in modern gas turbines with improved thermal efficiency. Ingot casting followed by open die-forging and then heat treatments are the main manufacturing steps for the production of parts made of this alloy. Solution heat treatment operations are applied at different stages of the manufacturing in order to ease the deformation processing and/or prepare the microstructure for final heat treatment. In this research, the influence of various solution heat treatment schedules on morphology and distribution of the γ′ phase are investigated and documented. The obtained results will contribute to a better understanding of microstructure evolution of AD730TM during solution heat treatments. Differential Thermal Analysis (DTA) is used for the purposes of measurement of temperatures of phase transformations of the alloy. Based on DTA results, three solutionizing temperatures and three holding times were selected for performing and assessing the solution heat treatment process. Optical and electron microscopy were used to study the morphological evolution as well as the coarsening and dissolution of secondary phases at solvus and subsolvus temperatures. The results indicated that precipitate agglomeration and Ostwald ripening are the governing mechanisms during the initial stages and splitting and partial dissolution of γ′ precipitates takes place during subsolvus solution treatments.
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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".