Nanoscale Studies of the Role of ZDDPs in the Wear Protection in the Automobile Engine
Bibliographic record
Abstract
The improvement of fuel consumption is an important driving force for research and development in the automobile industry in order to minimize greenhouse gas emissions as well as improving fuel economy. Aluminum alloys are a class of alternative materials that are being used to replace cast iron in motor components due to the concomitant weight savings which result in improved fuel efficiency, and cost savings. Our research focuses on these alternative Al-based alloys as well as traditional steel interfaces, and the protective films that form on the surfaces. Currently the zinc dialkyl-dithiophosphates (ZDDPs) have been used as engine oil additives for over 60 years. They are important chemically-active additives, known for their antioxidant and antiwear characteristics. ZDDPs are known to form a protective film (tribofilms) at rubbed surfaces, typically on iron containing metals surfaces commonly used in the automotive industry; however ZDDPs and the products formed are not well suited for the environment as they can readily poison the catalytic converters and their efficacy on Al-Si alloys is not well established.
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.
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".