Characterization of Methyl Methacrylate Grafting onto Preirradiated Biodegradable Lignocellulose Fiber by <i>γ</i>‐Radiation
Bibliographic record
Abstract
Gamma-radiation-induced graft copolymerization of methyl methacrylate onto natural lignocellulose (jute) fiber was carried out by the preirradiation method in an aqueous medium by using octylphenoxy-polyethoxyethanol as an emulsifier. The different factors that influenced the graft copolymer reaction process were investigated. In the case of radiation-dose-dependent grafting, samples irradiated in the presence of air produced up to 73% graft weight compared to 53% obtained in the case of irradiation in a nitrogen environment. By assuming Arrhenius reaction kinetics, the activation energy (E(a)) of the grafting reaction process was evaluated for different reaction temperatures. Moreover, the graft copolymer reaction was controlled by incorporating a homopolymer-inhibiting agent and three different chain-transfer agents in the reaction medium. The mechanical and thermal properties of jute fiber 'as received' and jute-graft-poly(methyl methacrylate) were also investigated. The results showed that the percentage of grafting with jute fiber has a significant effect on the properties. The kinetic parameters were evaluated from TGA thermograms by using Broido's method in the temperature range 240-350 degrees C. Scanning electron micrographs show that the structural changes on the surface of jute fibers were induced by graft copolymerization of methyl methacrylate monomer. Fiber-fiber surface friction was measured in terms of the average maximum load and the kinetic friction. SEM of jute-graft-poly(methyl methacrylate).
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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".