Tribological Evaluation of Lead-Free MoS2-Based Solid Film Lubricants as Environmentally Friendly Replacements for Aerospace Applications
Bibliographic record
Abstract
Solid lubricants, such as MoS2 have been widely used in the aerospace industry with the primary purpose of reducing the friction and wear of tribological interfaces. MoS2 based solid film lubricants are generally doped with other compounds, which can help overcome some of their limitations related to environmental conditions. For instance, compounds like Sb2O3 and Pb have been traditionally used to improve the endurance life of these lubricants. However, with the recent zest in transferring to eco-friendly lubricants, there is a strong push to eliminate Pb based compounds. The main purpose of this work is to better understand the influence of Pb based compounds on the tribological behavior of MoS2 based solid film lubricants as well as to critically evaluate the performance of Pb free lubrication strategies. More specifically, the baseline ‘non-green’ lubricant was doped with Pb compound and Sb2O3 and the Pb compound in the ‘Green’ alternative lubricant was replaced by more Sb2O3. The wear test was done using a ball-on-disk tribometer for specific loads and for 5000 cycles. Ex-situ analysis was conducted using Scanning Electron Microscope (SEM), Atomic Force Microscopy (AFM), and micro-Raman to capture the interfacial processes of these lubricants at different loads. Overall, the non-green lubricant performed better in terms of the tribological behavior (i.e., lower friction and wear), which was attributed to the formation of a dense MoS2-based tribo-/transfer-film with the basal planes oriented in the parallel direction to the sliding. The finding on the interfacial phenomena provided critical insights into the development of novel green alternatives that may have the ability to replace Pb based compounds in the future for a sustainable environment.
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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 | 0.001 |
| 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".