Tribological interaction of plasma functionalized CaCO3 nanoparticles with zinc and ashless dithiophosphate additives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Surface-modified CaCO 3 nanoparticles, synthesized through plasma-enhanced chemical vapor deposition (PECVD), were employed to improve lubricant additive technology for internal combustion engines via reduction and/or replacement of additives, such as zinc dialkyl dithiophosphate (ZDDP), in engine oil. Various oil formulations were prepared with functionalized CaCO 3 nanoparticles, in combination with ashless dialkyl dithiophosphate (DDP) and ZDDP at low concentrations of phosphorus. Tribological test results indicate synergistic interaction of functionalized CaCO 3 nanoparticles with ZDDP and DDP, providing enhanced friction and wear performance under boundary lubrication. A comparative study of the tribo-surfaces morphology and chemistry was assessed via atomic force microscopy and X-ray absorption near-edge spectroscopy. Improved wear protection by functionalized CaCO 3 BM (borate and methacrylate coated) nanoparticles under boundary lubrication was attributed to the formation of calcium and boron-rich 50–80 nm thick tribofilms on the worn surfaces. XANES results revealed that plasma functionalized CaCO 3 nanoparticles interact with ZDDP and DDP and participate in tribofilm formation through tribo-chemical reactions and metal cation supply to form stable and wear-resistant tribofilms. These results provide strong support for the potential application of plasma functionalized CaCO 3 nano-additives to reduce the concentration of harmful P-based additives in automotive lubricants.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it