Self-lubrication of machining tools in dry via in-situ formed tribofilms.
Bibliographic record
Abstract
Green manufacturing technology has become a significant innovative keyword to reduce the environmental burden and CO2 emission at the stage of manufacturing and production. In daily operations by machining, huge amount of lubricating oils and cleansing agents is wasted so that dry machining technology provides us a way to completely reduce these wastes. Among several candidates, self-lubrication via in-situ formation of lubricious oxide films is accommodated to protective coatings in order to attain low friction and wear state even at higher cutting speed range. Materials science of in-situ formed lubricious oxide tribofilms is stated with consideration of accommodation mechanism via the chlorine implantation. Mechanical characterization is made for evaluation on elasto-plastic deformation of lubricious oxides. Turning test is employed to evaluate dry machinability of various tools for wide range of cutting speed. Self-lubrication in dry machining is described both for bare WC and TiCN-coated WC tools with and without chlorine implantation. Precise microstructure analyses are made by using the laser microscope, EDS and XPS. In-situ formation of lubricous oxides proves that self-lubrication process takes place even in dry machining to reduce the flank wear and friction coefficient.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".