Tribochemistry of Aldehydes Sheared between (0001) Surfaces of α-Alumina from First-Principles Molecular Dynamics
Bibliographic record
Abstract
First-principles molecular dynamics (FPMD) simulations are used to explore the tribological behavior of systems consisting of two Al 2 O 3 (0001) surfaces separated by acetaldehyde molecules. The simulations were performed with normal pressures, P, that ranged from 0 to 20 GPa. The simulations show that sliding occurs with little or no significant changes in the structure of the aldehydes when P is low. Meanwhile, tribochemical reactions between aldehydes to yield oligomers, and between the oligomers and the surfaces, occur at higher P . The occurrence of these reactions leads to slip mechanisms that are dominated by the dissociation of chemical bonds. The different slip mechanisms affect the friction forces required to maintain motion of the surfaces. Slip mechanisms that do not involve bond rupture require low forces, with a friction coefficient of 0.034 to 0.044. The friction forces are much larger for the slip processes involving the rupture of bonds. Interestingly, the results indicate that the friction forces associated with slip mechanisms involving bond rupture are lower when the longer oligomers are involved in the slip process. Overall, this work sheds light on the atomic-level chemical processes that occur when lubricated surfaces move past one another, and may aid in the rational use of tribochemical reactions in functional lubrication.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".