Characterization of aluminum/alumina/TiC hybrid composites in 3D produced by anodizing and accumulating roll bonding process using synchrotron radiation tomography
Bibliographic record
Abstract
Hybrid composites of Al/Al 2 O 3 /TiC were produced by anodizing and accumulative roll bonding processes. We implemented 3D imaging of the composites using synchrotron radiation tomography at Biomedical Imaging and Therapy’s 05B1-1 beamline at Canadian Light Source to collect information on internal structure of these hybrid composites i.e. distribution of particles and voids, particle/matrix interface and surface area distribution after different accumulative roll bonding passes. The volume and interface surface area distribution are responsible for strength and toughness of the composites along with other factors such as strain hardening and formation of ultrafine grains. We found that the mechanical properties improved as the number of accumulative roll bonding passes increases and the internal homogeneity of structure also improved. The composites after different accumulative roll bonding passes are studied where the number of reinforced particles and voids and their shape and size distribution were accurately being quantified in 3D to relate with mechanical properties of the composite. Such information should be of importance in analysis and improvement of the manufacturing process of these types of composites.
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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".