Polysaccharide-based superabsorbent hydrogels (SAH) as sustainable material alternatives for personal hygiene products
Bibliographic record
Abstract
Superabsorbent hydrogels (SAHs) derived from biodegradable polysaccharides—sodium carboxymethyl cellulose (Na-CMC), hydroxyethyl cellulose (HEC), and cellulose—crosslinked with epichlorohydrin (ECH) were synthesized and comprehensively characterized. Developed as environmentally friendly alternatives for absorbent hygiene products (AHPs), these hydrogels address ecological concerns associated with conventional petroleum-based materials such as sodium polyacrylate. The synthesized hydrogels were characterized using spectroscopic, analytical, and rheological techniques to confirm successful crosslinking and to assess their morphology, structural features, and viscoelastic behavior. Swelling studies in deionized water and saline solutions demonstrated high water absorption (>350 g/g hydrogel) and retention capacities (>98 % water content), with performance that met or exceeded that of commercial sodium polyacrylate-based superabsorbent polymers under specific conditions. Notably, ECH-crosslinked Na-CMC hydrogels exhibited enhanced absorption performance in saline environments. The demonstrated safety, environmental compatibility, and scalability of these polysaccharide-based hydrogels underscore their potential for widespread application in personal hygiene products.
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 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".