Spectroscopic analysis of CdCl<sub>2</sub> doped PVA–PVP blend films
Bibliographic record
Abstract
The changes in molecular chemical structure of polyvinyl alcohol (PVA) and polyvinyl pyrrolidone (PVP), caused by doping PVA–PVP blend with cadmium chloride (CdCl2), have been studied using ultraviolet–visible (UV-Vis) spectroscopy, Fourier transform Raman spectroscopy and Fourier transform infrared (FTIR) spectroscopy. The formation of cadmium nano-structures and microstructures in CdCl2-doped PVA–PVP blend has been visualized using scanning electron microscopy, in the range of doping levels varying from 0.5 up to 10.2 wt% (doping level in weight percentage). The incorporation of dopant in PVA–PVP blend is confirmed using energy dispersive X-ray spectroscopy. The optical absorbance (UV-Vis) spectra of PVA–PVP blend films doped with CdCl2 from 0.5 up to 2.2 wt%, showed a prominent absorption hump with peak at the wavelength 370 nm, in addition to other intermediate energy bands caused by the interactions of CdCl2 with molecules of PVA and PVP. The photo-luminescence (emission and fluorescence) spectra show significant quenching of fluorescence in CdCl2-doped PVA–PVP blend films. Analysis of FTIR and Raman spectra suggest the possible modes of interaction of cadmium ions (Cd2+) and chlorine ions (Cl−) with reactive functional groups (C–N, hydroxyl and carbonyl groups) of polymeric molecules in the blend. A reaction scheme for interaction of CdCl2 with PVA–PVP blend is proposed, on the basis of spectroscopic studies on these films.
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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".