Accurate New Method for Molecular Orientation Quantification Using Polarized Raman Spectroscopy
Bibliographic record
Abstract
The physical properties of polymers are strongly affected by their molecular orientation. In this paper, we demonstrate for the first time a new and improved Raman spectroscopy method to characterize this key parameter. In recent years, Raman spectroscopy has emerged as an indispensable tool for this purpose, but its widespread use is still largely restricted by the experimental complexity and the limitations imposed by the standard quantification procedure, referred in this article as the depol constant (DC) method. We have very recently proposed and established theoretically a simplified quantification approach that is based on the most probable orientation distribution (MPD method). Herein, we demonstrate its experimental validity and its wide applicability by studying a series of samples from three highly dissimilar polymers (HDPE, PET, and PS), and covering the full possible orientation range. We show that the new MPD method overcomes the experimental and theoretical difficulties faced with the current DC method and that it leads to more accurate orientation values. We expect that this method will greatly extend the accessibility of Raman spectroscopy for molecular orientation studies of polymer systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".