HRTEM Observation and Atomic Modeling of α/β Interphase Boundary in a Ti-22V-4Al Alloy
Bibliographic record
Abstract
In order to study interface boundary structures, a three dimensional Near-Coincidence Site lattice (Near-CSL) model based on Bollmann’s O-lattice method has been proposed. Previous studies have shown that intragranular α-phase precipitates in a Ti–22V–4Al alloy have a morphology of lath-like, with two well defined facet planes. A detailed TEM observation of the laths has been made in this study and the results correlated to the present analysis. Accommodation mechanism of misfit dislocations and the Burgers vector of the defects observed at the broad face and side facet plane of the intragranular α-phase precipitates have been determined. The structural ledges at the side facet, as predicted by the present analysis, is consistent with HRTEM observation. The Burgers vector of misfit dislocations at the broad face is in good agreement with that previously reported for a Zr–2.6Nb alloy, that has almost the same lattice parameter ratio as the Ti–22V–4Al alloy used in the present study. Although the Burgers vector of the defects on the broad face can be determined by HRTEM observation, the boundary plane is not well defined. However, it can be demonstrated that the interface boundary structure of the broad face can be rationalized from the results of both the Near-CSL analysis and the HRTEM observations.
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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".