Infrared and vibrational circular dichroism spectra of methyl β‐D‐glucopyranose in water: The application of the <i>quantum cluster growth</i> and <i>clusters‐in‐a‐liquid</i> solvation models
Bibliographic record
Abstract
Abstract The infrared (IR) and vibrational circular dichroism (VCD) spectra of methyl β‐D‐glucopyranose in water were measured. Both implicit and explicit solvation models were utilized to explain the observed spectra. The vast body of existing experimental and theoretical data suggested that about eight explicit water molecules are needed to account for the solvent effects, supported by the current Quantum Cluster Growth (QCG) analysis. Extensive manual and systematic conformational searches of the molecular target and its water clusters were carried out by using a recently developed conformational searching tool, conformer‐rotamer ensemble sampling tool (CREST), and the microsolvation model in the associated QCG code. The Boltzmann averaged IR and VCD spectra of the methyl β‐D‐glucopyranose‐(water) n ( n = 8) conformers in the PCM of water provide better agreement with the experimental ones than those with n = 0, 1, and 2. The explicit solvation with eight water molecules was shown to greatly modify the conformational preference of methyl β‐D‐glucopyranose from its monomeric form. Further analyses show that the result is consistent with the existence of long‐lived methyl β‐D‐glucopyranose monohydrates with the additional explicit water effects being accounted for with the quantum mechanical treatment of the other seven close‐by water molecules in the PCM of water.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".