Synthesis, Characterization and Antibacterial Application of Copolymers Based on N,N-Dimethyl Acrylamide and Acrylic Acid
Bibliographic record
Abstract
Hydrogel copolymers based on N,N-dimethyl acrylamide (DMA) and acrylic acid (AAc) were synthesized using a solution polymerization technique with different monomer ratios and ammonium persulfate as an initiator. This paper investigates the thermal stability, physical and chemical properties of the hydrogel copolymer. Testing includes Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and elemental analysis (CHNS). The copolymer composition was determined by elemental analysis, and the reactivity ratios of monomers were calculated through linearization methods such as Fineman–Ross (FR), inverted Fineman–Ross (IFR), Kelen–Tudos (KT) and Mayo–Lewis (ML). Good agreement was observed between the results of all four methods. The ratio of r1 and r2 were 0.38 (r1) and 1.45 (r2) (FR), 0.38 (r1) and 1.46 (r2) (IFR), 0.38 (r1) and 1.43 (r2) (KT), and 0.38 (r1) and 1.45 (r2) (ML). Hydrogel copolymers exhibited good thermal stability, and SEM showed three-dimensional porous structures. Antibiotic-free and antibiotic-loaded hydrogels demonstrated antimicrobial properties against both Gram-positive and Gram-negative bacteria. As the ratio of DMA in hydrogel copolymer increased, the activity of copolymer against bacteria enhanced. The results indicated that these hydrogels have the potential to be used as antibacterial materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".