An investigation into the tribological behaviour of cutting fluid additives on <scp>Ti‐6Al‐4V</scp> alloy
Bibliographic record
Abstract
Abstract The performance of polymer‐based and phosphorus‐based cutting fluid additives have been shown to depend on the machining conditions employed. This study investigated the tribological behaviour behind the previously reported machining performance of polymer‐based and phosphorus‐based additives on Ti‐6Al‐4V using ball‐on‐disc tests. The coefficient of friction (COF) was evaluated using ball‐on‐disc tests, surface characterisation was performed on the Ti‐6Al‐4V and steel ball counterfaces to investigate the wear and friction reduction mechanisms. The tribological performance of the phosphorus‐based additive was observed to be influenced by the applied load and temperature. The activation of this additive resulted in a reduction in COF at elevated temperatures. However, the activation temperature was observed to be influenced by the applied load. The COF associated with the polymer‐based additive was noted to increase as the temperature increased, regardless of the applied load. The formation of tribolayers from the additives was related to the COF behaviour as well as the surface damage on Ti‐6Al‐4V and lower material transfer to the steel counterfaces.
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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 | 0.001 | 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".