Effect of electrical current on sliding friction and wear mechanisms in a-C and ta-C amorphous Carbon coatings
Bibliographic record
Abstract
This study investigated the sliding wear behaviour of amorphous carbon (a-C) and tetrahedral amorphous carbon (ta-C) coatings, two forms of diamond-like carbon (DLC) coatings, against SAE 52100 steel using a modified ball-on-disk tribometer with applied electrical currents ranging from 100 mA to 1800 mA. It focused on the variations in sliding friction and wear characteristics of these coatings as electrical currents increased under constant load and speed conditions. The a-C coatings exhibited lower coefficient of friction (COF) values and reduced volumetric wear losses up to 1500 mA, while ta-C coatings studied displayed higher wear, similar to uncoated M2 steel, at 300 mA with degradation occurring at low currents, resulting in failure due to severe oxidational wear. The a-C coatings showed no significant electrical damage at these currents. Raman spectroscopy revealed structural changes on the wear tracks of sp 2 -rich a-C coatings, specifically the formation of graphene layers. In comparison, the wear tracks of sp 3 -rich ta-C coatings did not display such transformation under the conditions studied. The graphene coverage on the surfaces of the a-C coatings increased with the increase in the current as revealed by the Raman intensity maps of 2D peaks and this increase was accompanied by a higher defect density in the graphene. The low COF of graphene-covered a-C surfaces was consistent with the proposed mechanisms of moisture adsorption. However, at currents exceeding 900 mA, surface temperatures of a-C coatings exceeded 100 °C, impairing graphene's ability to maintain low friction, resulting in an increased COF. • At 300 mA, M2 steel shows micro pits and a 40x increase in wear loss. • Ta-C coatings develop micro pitting and oxide at 100 mA; fail by 300 mA. • a-C coatings withstand up to 1500 mA with minimal damage due to graphene layers. • Increased currents boost graphene coverage, enhancing friction reduction on a-C. • Above 900 mA, high temperatures reduce the friction benefits of graphene on a-C.
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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 | 0.001 | 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) | 0.000 | 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".