Finite Temperature Structure and Dynamics of Zinc Dialkyldithiophosphate Wear Inhibitors: A Density Functional Theory and ab Initio Molecular Dynamics Study
Bibliographic record
Abstract
The thermal decomposition of several zinc dialkyldithiophosphate (ZDDP) antiwear additives has been explored with both finite temperature gas-phase ab initio molecular dynamics (MD) simulations and static quantum chemical calculations at the density functional (DFT) level of theory. Calculations have been performed on the ZDDP monomers (Zn(S 2 P(OR) 2 ) 2 ), ZDDP dimers, and the corresponding linkage isomers (LI-ZDDPs) with a variety of substituents (R = H, Me, Et, i Pr, t Bu, Ph). The results show that the monomeric form of ZDDP likely dominates at finite temperatures for all substituents considered and that the LI-ZDDP isomer is nearly thermoneutral with respect to the parent ZDDP monomer. Optimized geometries of the ZDDP monomer give 4-coordinate Zn structures that are consistent with previously reported theoretical calculations. However, ab initio molecular dynamics simulations of the ZDDP monomers at elevated temperatures show that 2- and 3-coordinate complexes are instead favored and that the decrease in coordination number has a significant effect on the electronic structure of the molecule that may affect the reactivity of ZDDPs with other chemical species present in engine oils. The ab initio MD simulations also provide insight into several decomposition pathways of the various ZDDP species that include the loss of either alkyl or alkoxy radicals as well as the elimination of olefins and sulfides from the ZDDP molecule. The results are discussed in terms of how the observed processes will affect the overall abilities of the antiwear film.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".