Preparation of 2,5-Dimercaptothiadiazole Mixed Phosphate Diamine Salt and Its Tribological Performance in Low-Viscosity Lubricating Oil
Bibliographic record
Abstract
Abstract In this paper, 2,5-dimercaptothiadiazole mixed phosphate diamine salt (SNP), an antiwear additive, was formulated via stepwise temperature-controlled amination. Its structure and thermal stability were characterized using infrared (IR) spectroscopy, nuclear magnetic resonance (NMR), mass spectrometry (MS), and thermogravimetric analysis (TGA). Results confirmed that SNP contains a thiadiazole ring, phosphate ester, and amine functional groups, with its main thermal decomposition stage at 290.24–332.99 °C. The tribological performance of SNP in HVIP6 base oil was evaluated and compared with that of commercial phosphite, phosphate, and borate esters. Four-ball tests showed that 1% SNP yielded a wear scar diameter of 0.359 mm, 55.18% smaller than that of the base oil and significantly lower than those of phosphite ester (0.499 mm), phosphate ester (0.484 mm), and borate ester (0.810 mm). scanning electron microscopy and X-ray photoelectron spectroscopic analyses revealed that SNP dissociates into PO43− and NH4+ at the friction interface, forming a dense nanocrystalline FePO4 protective film; the positive charge of NH4+ enhances the orderliness of the FePO4 film. In contrast, phosphite and phosphate esters exhibited poor antiwear performance, primarily due to insufficient stability of the formed tribofilms. In contrast, borate esters barely generated effective protective films. The self-synthesized SNP consequently provides a new approach for the design of antiwear additives in low-viscosity lubricating oils.
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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 | 0.000 |
| 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 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".