Energy dissipation via quantum chemical hysteresis during high-pressure compression: A first-principles molecular dynamics study of phosphates
Bibliographic record
Abstract
The chemomechanical response of triphosphates (TPs) and zinc phosphates (ZPs) to changes in pressure $p$ and temperature $T$ is studied through first-principles molecular dynamics. The maximum values of$p(>20\phantom{\rule{0.3em}{0ex}}\mathrm{GPa})$ and $T(\ensuremath{\approx}1000\phantom{\rule{0.3em}{0ex}}\mathrm{K})$ are chosen to mimic roughly the extreme conditions to which phosphates may be exposed during their role as engine antiwear films. In all systems, atoms undergo pressure-induced changes in coordination number. Upon decompression, these chemical changes are partially reversible but nevertheless show strong hysteresis effects. This leads to significant energy dissipation, which contributes to the high friction coefficients of ZP antiwear pads. ZPs remain a covalently cross-linked network after decompression, while TPs revert to a disconnected state. The decompressed TPs have a larger bulk modulus $(\ensuremath{\approx}35\phantom{\rule{0.3em}{0ex}}\mathrm{GPa})$ than the uncompressed TPs $(\ensuremath{\approx}27\phantom{\rule{0.3em}{0ex}}\mathrm{GPa})$. This increase is due to symmetry-breaking proton transfer reactions, which are irreversible on the time scale of the simulation. Temperature has little effect on the results.
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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 | 0.001 | 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".