Effect of metal salts on high‐voltage atmospheric cold plasma‐induced polymerization of acrylamide
Bibliographic record
Abstract
Abstract Acrylamide polymerization in solution was successfully induced by high‐voltage atmospheric cold plasma (HVACP) treatment, using nitrogen gas. Addition of metal sulfates greatly increased acrylamide polymerization, with ZnSO 4 and MgSO 4 yielding 89% and 62% polyacrylamide polymer, respectively. Presence of excited nitrogen species during HVACP treatment was demonstrated using optical emission spectroscopy. Proton NMR (H 1 NMR) and attenuated total reflectance‐Fourier transform infrared spectroscopy were performed to verify the degree of polymerization. Rheology experiments and viscosity measurements showed that acrylamide samples treated with HVACP in the presence of ZnSO 4 , MgSO4 had higher viscoelastic moduli, and intrinsic viscosity (η) compared to those treated in deionized (DI) water, due to the higher degree of polymerization. Addition of ZnSO 4 yielded the greatest viscoelastic moduli and intrinsic viscosity (the storage modulus was G' = 1.26·10 4 ± 1.8·10 3 Pa and the loss modulus was G" = 3.06·10 3 ± 1.10·10 3 Pa, and [η] ≈ 26 L/g). With MgSO 4 , the viscoelastic moduli were G' = 5.93·10 3 ± 1.40·10 3 Pa and G" = 1.60·10 3 ± 2.6·10 2 Pa, and (η) ≈ 4.7 L/g. In DI water G' = 1.55·10 3 ± 2.1·10 2 Pa and G" = 7.44·10 2 ± 1.37·10 2 Pa, and (η) ≈ 2. PAM prepared with ZnSO 4 also had the highest molecular weight, as determined by mass spectroscopy. ZnCl 2 and MgCl 2 hindered acrylamide polymerization, highlighting the effect of the sulfate ions on acrylamide polymerization using HVACP treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".