Compression-induced transformation of aldehydes into polyethers: A first-principles molecular dynamics study
Bibliographic record
Abstract
First-principles molecular dynamics simulations are used to investigate the behavior of bulk acetaldehyde (MeCHO) under conditions of increasing pressure. The results demonstrate that increasing pressure causes the aldehydes to polymerize, yielding polyethers through a process involving the rapid formation of C-O bonds between multiple neighboring MeCHO molecules. Attempts to induce polyether formation at different densities through the application of geometric constraints show that polymerization occurs only once a critical density of approximately 1.7 g/cm(3) has been reached. The results of simulations performed at several different temperatures are also consistent with a process that is induced by reaching a critical density. The origins of this effect are rationalized in terms of the structural requirements for the formation of C-O bonds between multiple MeCHO molecules in rapid succession. Specifically, the collective formation of C-O bonds requires the typical distance between the sp(2) carbon atoms and oxygen atoms in neighboring MeCHO molecules to reach a value of approximately 2.5 A. Radial distribution functions calculated at different densities show that this structural requirement is reached when the density is near the observed threshold. The observed reaction may be useful in the context of lubrication, with polyethers being effective lubricants and the extreme conditions experienced in sliding contacts providing the ability to reach the high densities needed to induce the reaction. In this context, the calculations indicate that polyether formation is associated with significant energy dissipation, while energy dissipation is minimal once the polyethers are formed. Furthermore, the polyethers are stable with respect to multiple compression/decompression cycles and pressures of at least 60 GPa.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".