Molecular Dynamics Study of the Effect of <scp>l</scp>-Alanine Chiral Dopants on Diluted Chromonic Solutions
Bibliographic record
Abstract
Atomistic molecular dynamics simulations have been performed for disodium cromoglycate (DSCG) chromonic solutions mixed with l-alanine chiral dopants. We study the fundamental molecular mechanisms induced by low concentrations of l-alanine on diluted DSCG solutions, including their effect on the chromonic aggregates, the solvent, and sodium counterions. Simulations reveal that l-alanine molecules primarily interact with DSCG stacks establishing salt bridges between their respective ammonium and carboxylate groups. Our results demonstrate that l-alanine and sodium counterions jointly establish an intricate network of noncovalent interactions around DSCG aggregates that decreases the global electrostatic repulsion of the chromonic system. Two possible structural effects in DSCG aggregates arise from this electronic stabilization: the increment of the total number of consecutively stacked aromatic planes per DSCG aggregate (intracolumnar effect) or the partial separation reduction between neighboring DSCG columnar sections due to the simultaneous bridging of intercolumnar DSCG carboxylate sites by sodium counterions, forming sodium bridges (intercolumnar effect). Sodium bridges may be responsible for the formation of stacking faults in DSCG aggregates in the form of lateral overlap junctions. This mechanism would explain the difference between lower X-ray correlation lengths with the expected persistence length in chromonics.
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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 | 0.000 |
| 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".