Citric acid - crosslinked cellulose derivatives superabsorbent hydrogels (SAH) as sustainable alternatives for personal hygiene applications
Bibliographic record
Abstract
This study explores the development of citric acid (CA)-crosslinked superabsorbent hydrogels (SAHs) based on cellulose derivatives as sustainable alternatives to conventional petroleum-based superabsorbent polymers (SAPs) used in personal hygiene products. A biodegradable and biocompatible hydrogel formulation was synthesized using CA as a green crosslinking agent, with sodium carboxymethyl cellulose (Na-CMC) as the primary polymer and hydroxyethyl cellulose (HEC) as the secondary polymer, in varying ratios. The effects of polymer composition, swelling medium, pH, and water/saline solution absorption under load (AUL) were systematically evaluated by employing thermal analysis, rheology, water absorption capacity, swelling/deswelling kinetics, and soil biodegradation tests. Biocompatibility was also assessed via indirect contact cytotoxicity assays using mouse fibroblast cells. The optimized formulation, particularly the CMC—1.5 % CA hydrogel, exhibited high equilibrium water absorption (Q eq ) of 110 g/g in saline media at 38 °C, favorable swelling/deswelling behavior, rheological robustness, significant biodegradability (72 % within 7 weeks under composting conditions), and non-cytotoxicity (>80 % cell viability). These results highlight the potential of these hydrogels as biodegradable, biocompatible materials aligned with the Sustainable Development Goals (SDGs), especially for eco-friendly hygiene applications. • Citric acid–crosslinked cellulose hydrogels showed superior water absorption, exceeding commercial superabsorbents. • Hydrogels were up to 72 % biodegradable and non-cytotoxic, meeting key safety requirements. • Green-crosslinked cellulose hydrogels offer an eco-friendly alternative to synthetic absorbent materials. • The hydrogel process is simple, high-yield (>85 %), and scalable for industrial hygiene applications.
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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 | 0.000 | 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) | 0.000 | 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".