Synthesis, Characterization and Molecular Modeling of Novel Oxoethyl methacrylate Polymers
Bibliographic record
Abstract
The monomer 2-(2-methoxyphenylamino)-2-oxoethyl methacrylate (2MPAEMA) was synthesized and polymerized for the first time into its homopolymer and a copolymer with methyl methacrylate via free-radical polymerization. Structural verification was conducted using FT-IR and NMR spectroscopy, while thermal analysis confirmed the two-stage decomposition of both polymers. Quantum chemical calculations at the B3LYP/LanL2DZ level supported the experimental data, revealing significant intramolecular interactions, electronic delocalization, and thermal stability. The homopolymer exhibited a narrower HOMO-LUMO gap (4.954 eV) than the copolymer (5.207 eV), implying enhanced charge-transport potential. Molecular Electrostatic Potential and Density of States analyses further confirmed well-defined charge distribution and greater orbital overlap in the homopolymer. These results provide new insights into the structure-property relationships of 2MPAEMA-based polymers, highlighting their potential for optoelectronic, sensing, and thermoresponsive applications. Future studies will explore their biological activity and functional performance in targeted environments. FT-IR/NMR, thermal analysis, and DFT collectively indicate that 2MPAEMA polymers are wide-band gap and thermally robust, suggesting their suitability as dielectric matrices or UV-absorbing hosts.
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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".