A study of the eigenvectors of the low-frequency vibrational modes in crystalline adenosine via high pressure Raman spectroscopy
Bibliographic record
Abstract
High-pressure Raman spectroscopy has been used to study the eigenvectors and eigenvalues of the vibrational modes of crystalline adenosine at 295 K by evaluating the logarithmic derivative of the vibrational frequency with respect to pressure: [Formula: see text]. Crystalline samples of molecular materials such as adenosine will have vibrational modes that are localized within a molecular unit ("internal" modes) as well as modes in which the molecular units vibrate against each other ("external" modes). The value of the logarithmic derivative is found to be a diagnostic probe of the nature of the eigenvector of the vibrational modes. Stretching modes which are predominantly internal to the molecule have low logarithmic derivatives while external modes have higher logarithmic derivatives. Particular interest is paid to the low-frequency (≤150 cm(-1)) modes. Based on the pressure dependence of its logarithmic derivative, a mode near 49 cm(-1) is identified as internal mode. The other modes below 400 cm(-1) have pressure dependences of their logarithmic derivatives consistent with being either (1) modes which are mainly external, meaning that the molecules of the unit cell vibrate against each other in translational or librational motions (or linear combinations thereof), or (2) torsional or bending modes involving a large number of atoms, mainly within a molecule. The modes above 400 cm(-1) all have pressure dependences of their logarithmic derivatives consistent with being mainly internal modes.
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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) | 0.002 | 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".