Fabrication and Thermo-Mechanical Characterization of HEMA Treated UV Photo-Cured Biodegradable Chitosan Film
Bibliographic record
Abstract
Chitosan was extracted from dried prawn shell via chitin and was characterized by Fourier Transformed Infrared (FTIR) Spectroscopy. Thin film of chitosan was prepared by solution casting using a 2% chitosan solution. Chitosan was dissolved in 2% acetic acid. Mechanical properties like tensile strength (TS) and elongation at break (Eb%) of chitosan film were studied. Eight formulations (M1: 5% HEMA to M8: 40% HEMA) were developed with 2-hydroxyethyl methacrylate (HEMA) monomer in methanol (MeOH) along with photoinitiator Darocur-4043 (2%). The film was soaked in those formulations for 1 min and cured under UV radiation at different radiation intensities for the improvement of physico-mechanical properties of the film. The cured films were then subjected to various characterization tests like TS, Eb%, water absorption, FTIR spectroscopy, polymer loading (PL), differential thermal analysis (DTA), and thermo gravimetric analysis (TGA). The M6 formulation containing 30% HEMA in MeOH solution showed the best performance at 20th UV pass. The highest TS, Eb% and PL were found to be 31 MPa, 71.25% and 26.38%, respectively, for the same formulation at 20th UV pass. The DTA/TGA study showed that the film with M6 formulation at 20th UV pass was thermally more stable than non-radiated chitosan film. The FTIR analysis revealed the crosslinking between HEMA and chitosan.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".