A Preliminary Study to Enhance the Tribological Performance of CoCrMo Alloy by Fibre Laser Remelting for Articular Joint Implant Applications
Bibliographic record
Abstract
CoCrMo alloy has long been used as a pairing femoral head material for articular joint implant applications because of its biocompatibility and reliable tribological performance. However, friction and wear issues are still present for CoCrMo (metal)/CoCrMo (metal) or CoCrMo (metal)/ultrahigh molecular weight polyethylene (UHMWPE) (plastic) pairs in clinical observations. The particulate wear debris generated from the worn surfaces of CoCrMo or UHMWPE can pose a severe threat to human tissues, eventually resulting in the failure of implants and the need for revision surgeries. As a result, a further improvement in tribological properties of this alloy is still needed, and it is of great interest to both the implant manufacturers and clinical surgeons. In this study, the surface of CoCrMo alloy was laser-treated by a fibre laser system in an open-air condition (i.e., no gas chamber required). The CoCrMo surfaces before and after laser remelting were analysed and characterised by a range of mechanical tests (i.e., surface roughness measurement and Vickers micro-hardness test) and microstructural analysis (i.e., XRD phase detection). The tribological properties were assessed by pin-on-disk tribometry and dynamic light scattering (DLS). Our results indicate that the laser-treated surfaces demonstrated a friction-reducing effect for all the tribopairs (i.e., CoCrMo against CoCrMo and CoCrMo against UHHMWPE) and enhanced wear resistance for the CoCrMo/CoCrMo pair. Such beneficial effects are chiefly attributable to the presence of the laser-formed hard coating on the surface. Laser remelting possesses several competitive advantages of being a clean, non-contact, fast, highly accurate and automated process compared to other surface coating methods. The promising results of this study point to the possibility that laser remelting can be a practical and effective surface modification technique to further improve the tribological performance of CoCr-based orthopaedic implants.
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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".