Bibliographic record
Abstract
A polarizable, flexible model for ethanol is obtained based on an extensive series of B3LYP/6-311++G(d,p) calculations and molecular dynamics simulations. The ethanol model includes electric-field dependence in both the atomic charges and the intramolecular degrees of freedom. Field-dependent intramolecular potentials have been attempted only once previously, for OH and HH stretches in water [P. Cicu et al., J. Chem. Phys. 112, 8267 (2000)]. The torsional potential involving the hydrogen-bonding hydrogen in ethanol is found to be particularly field sensitive. The methodology for developing field-dependent potentials can be readily generalized to other molecules and is discussed in detail. Molecular dynamics simulations of bulk ethanol are performed and the results are assessed based on comparisons with the self-diffusion coefficient [N. Karger et al., J. Chem. Phys. 93, 3437 (1990)], dielectric constant [J. T. Kindt and C. A. Schmuttenmaer, J. Phys. Chem. 100, 10373 (1996)], enthalpy of vaporization [R. C. Wilhoit and B. J. Zwolinski, J. Phys. Chem. Ref. Data, Suppl. 2, 2 (1973)], and experimental interatomic distributions [C. J. Benmore and Y. L. Loh, J. Chem. Phys. 112, 5877 (2000)]. The simultaneous variation of the atomic charges and the intramolecular potentials requires modified equations of motion and a multiple time step algorithm has been implemented to solve these equations. The article concludes with a discussion of the bulk structure and properties with an emphasis on the hydrogen bonding network.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".