Investigation of the Mechanical Behavior of Electroless Ni–P–Ti Composite Coatings
Bibliographic record
Abstract
Abstract To improve the toughness of Ni–P coatings, NiTi superelastic particles were introduced into the Ni–P matrix through the electroless co-depositing of Ni–P and Ti particles and annealing Ni–P–Ti coatings. The mechanical properties of the coatings were determined through bend testing bilayer specimens and tensile testing the standalone coating. The effects of Ti content and annealing on Young’s modulus, toughness, and fracture strength were investigated. After annealing, the toughness and strength improved considerably. The formation of the superelastic NiTi phase after annealing led to the improvement of toughness and fracture strength of the composite coating through transformation toughening, crack deflection, bridging, and shielding. Different toughening mechanisms interacted with each other and operated together. This contributed to the enhancement of toughness and fracture strength.
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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".