Effects of surface roughness parameters on the shear strength of AA 6061-T6 aluminium alloy in structural adhesive bonding applications
Bibliographic record
Abstract
This study aims to investigate the effects of the surface roughness of an aluminium substrate on the adhesive joint strength of aluminium–aluminium specimens prepared using epoxy and methyl methacrylate adhesives for shear strength tests. Aluminium surfaces were mechanically abraded using silicon carbide (SiC) papers with different grit sizes in two different modes. The evaluated bonding performance characteristics included the maximum bonding strength and residual strength of the adhesive joints after their exposure to various environmental conditions. The results demonstrated that excellent adhesion characteristics were obtained at the optimum SiC grit size (grit-80) regardless of the adhesive type. In addition, the topographical and morphological properties of the aluminium surfaces were studied before and after mechanical abrasion via surface profilometry and scanning electron microscopy, respectively. A possible mechanism was proposed to explain the observed shear strength changes and respective modes of fracture after sample exposure to air, de-ionised water, and aqueous salt solutions.
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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 | 0.001 |
| 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".