XANES Study of Tribofilm Formation With Low Phosphorus Additive Mixtures of Phosphonium Ionic Liquid and Borate Ester
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
The development of low phosphorus engine oils is important to minimize phosphorus-induced exhaust catalyst poisoning and resulting in harmful emissions. In this study, low phosphorus oil formulations were prepared by using an ashless additive mixture of borate ester (SB) with ionic liquid composed of a phosphonium cation and phosphate anion (P_DEHP) at 350 and 700 ppm phosphorus. Tribological properties of this binary additive system were evaluated using a reciprocating cylinder on a flat test configuration. Favorable interaction between P_DEHP and SB resulted in a significant reduction in friction coefficient and wear volume, in particular for P_DEHP(700P) + SB oil blend. Time-scale analysis of tribofilm formation was determined by running the tribological experiments for 5, 15, and 60 min duration. Electrical contact resistance (ECR) results revealed that the addition of P_DEHP at 350 ppm of phosphorus to SB at 500 ppm of boron can reduce the incubation time from 300 to 100 s for stable tribofilm formation. X-ray absorption near-edge spectroscopy (XANES) analysis of tribofilms indicates that the tribofilm mechanism for additive mixtures of P_DEHP and SB initially involves the formation of boron oxide-based films, which later interact with phosphorus to form boron phosphates in addition to iron phosphates. Incorporation of the high amount of boron phosphates in addition to boron oxide/acid and iron phosphates in the tribofilms contributed to the improved tribological performance of P_DEHP(700P) + SB oil. XANES results reveal that tribofilms formed due to the interaction of SB and P_DEHP evolve to a cross-linked structure, wherein the chain length of polyphosphates is increased with the increase in rubbing time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it