Quantitative Analysis of Hydrogen Bonding in Poly(4-Vinylphenol) Blends Using near Infrared Spectroscopy
Bibliographic record
Abstract
Quantitative evaluation of hydrogen bonding of poly(4-vinyl phenol)/poly(ethylene oxide) PVPh/PEO blends was conducted using Fourier transform near infrared (FT-NIR) spectroscopy. Absorption coefficients of the free ( a F ), intra- (PVPh–PVPh) ( a A ) and inter-associated (PVPh–PEO) hydroxyl groups ( a I ) were estimated. Two sets of approximations were tested, including adopting a least-squares refinement method to calculate absorption coefficients from all NIR spectra or using a literature value for a F . Each set of absorption coefficients thus estimated were used to determine hydroxyl concentration for the free and hydrogen-bonded hydroxyl overtone bands in the blends. A comparison is made among the resultant concentrations of the free, intra- and inter-associated hydroxyl groups. The concentration of free hydroxyl groups markedly decreases with PEO percentage, and that of intra-associated hydroxyl remains almost constant. Concentration for the inter-associated hydroxyl groups in the blends increases very slowly above 0.2 PEO weight fraction. When concentration of OH groups is reported per PVPh chain, FT-NIR measurements show a broad maximum in the number of interchain hydrogen bonds. This result can be used to explain partially previous orientation behaviour observed for PVPh/PEO blends.
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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) | 0.001 | 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".