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 ZnSO4 and MgSO4 yielding 89% and 62% polyacrylamide polymer, respectively. Presence of excited nitrogen species during HVACP treatment was demonstrated using optical emission spectroscopy. Proton NMR (H1NMR) 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 ZnSO4, 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 ZnSO4 yielded the greatest viscoelastic moduli and intrinsic viscosity (the storage modulus was G' = 1.26·104 ± 1.8·103 Pa and the loss modulus was G" = 3.06·103 ± 1.10·103 Pa, and [η] ≈ 26 L/g). With MgSO4, the viscoelastic moduli were G' = 5.93·103 ± 1.40·103 Pa and G" = 1.60·103 ± 2.6·102 Pa, and (η) ≈ 4.7 L/g. In DI water G' = 1.55·103 ± 2.1·102 Pa and G" = 7.44·102 ± 1.37·102 Pa, and (η) ≈ 2. PAM prepared with ZnSO4 also had the highest molecular weight, as determined by mass spectroscopy. ZnCl2 and MgCl2 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 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".