Structure and discrimination in chiral fluids: A molecular dynamics and integral equation study
Bibliographic record
Abstract
An analysis of structure and discrimination in simple chiral fluids is presented. The chiral molecules consist of a central carbon bonded to four distinct groups. Molecular-dynamics simulations have been performed on a one-component chiral fluid and on two racemic mixtures. For the racemates, discrimination, as measured by differences in pair distribution functions, is present but found to be small. Intermolecular pair interaction energies are found to be good predictors of the magnitude and the sign (mirror-image pairs favored) of the differences observed in site–site distribution functions. For the one-component fluid, the quality of structural predictions from the reference-interaction-site method and Chandler–Silbey–Ladanyi (CSL) integral equation theories, with the hypernetted chain (HNC) and Percus–Yevick closures, has been examined. These theories generally provide a qualitatively correct description of the site–site distributions. Extensions beyond the HNC level have been explored: Two-field-point bridge diagrams have been explicitly evaluated and included in the CSL theory. The inclusion of these diagrams significantly improves the quality of the integral equation theories. Since the CSL theory has not been used extensively, and bridge diagrams have been evaluated in only a few instances, a detailed analysis of their impact is presented. For racemic mixtures, diagram evaluation is shown to be crucial. Specifically, the differences in site–site distributions for sites on identical and mirror-image molecules are found to originate from bridge diagrams which involve interactions between four-site, or larger, clusters. Discrimination cannot be predicted from an integral equation theory which neglects these diagrams.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".