Ultra-sonication assisted cross-linking of cellulose polymers
Bibliographic record
Abstract
Cross-linked cellulose-epichlorohydrin polymers were synthesized by a conventional heating with stirring (C-EP heating) and a parallel process using ultra-sonication (C-EP sonication) in the presence of aqueous ammonia. Structural characterization of modified cellulose was carried out using FTIR/13C solid state NMR spectroscopy and thermal methods (DSC and TGA). Evidence of products with variable textural properties and morphology was supported by nitrogen gas adsorption, solvent swelling, and microscopy (SEM, TEM) results. C-EP sonication possess greater cross-linker content judging by the loss of the cellulose fibril structure which was facilitated by acoustic cavitation effects due to ultra-sonication. Equilibrium sorption studies in aqueous solution with 2-naphthoxy acetic acid (NAA) revealed that C-EP heating had slightly greater sorption capacity than C-EP sonication at alkaline pH. By contrast, C-EP sonication had greater uptake of NAA at acidic pH. Kinetic uptake studies at pH 3 is described by the pseudo-second order model, where the surface sites of C-EP heating became saturated within ca. 75 min; whereas, ca. 350 min occurred for C-EP sonication. This study demonstrates that the yield of sonication assisted cross-linking of cellulose is greater with improved adsorption properties. The study also reveals the utility of sonication assisted synthesis for the valorization and utilization of cellulose modified materials.
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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) | 0.002 | 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".